WO2020081698A2 - Pre-treatment planning and real-time visualization of lung volume reduction therapies - Google Patents

Abstract

Systems and methods for developing a lung volume reduction treatment plan for a patient include developing a first personalized three-dimensional pulmonary model for the patient based on a computerized tomography (CT) scan of the lung of the patient and a validated computational pulmonary system model, selecting a first lung coil design and a first lung coil placement location, developing a second personalized three-dimensional pulmonary model for the patient based on the first personalized three-dimensional pulmonary model for the patient, the first lung coil design, and the first lung coil placement location, and selecting a second lung coil design and a second lung coil placement location, where the selection of the second lung coil placement location is based on the second personalized three-dimensional pulmonary model for the patient.

Description

PRE-TREATMENT PLANNING AND REAL-TIME VISUALIZATION OF LUNG VOLUME REDUCTION THERAPIES

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] The present application claims the benefit of US Provisional Appln. No. 62/747,936 filed October 19, 2018, the full disclosure which is incorporated herein by reference in its entirety for all purposes.

BACKGROUND OF THE INVENTION

[0002] Embodiments of the present invention relate generally to the field of pulmonary therapy, and in particular to systems, devices, and methods for placing coils within a patient lung for therapeutic purposes, for example to achieve a reduction in lung volume.

[0003] Various lung conditions, such as emphysema, can be characterized by alveolar destruction, loss of the lung’s natural elastic properties, and increased lung volume, all of which can make breathing difficult.

[0004] T raditional options for treating a patient that presents with a lung condition include smoking cessation, drug therapy (e.g. inhaled steroids, bronchodilators, and antibiotics), supplemental oxygen, and pulmonary rehabilitation (e.g. breathing exercises). More recently, minimally invasive coil implants have been developed, which can be administered to a patient in order to improve exercise capacity, lung function, and quality of life in patients with various lung conditions, such as severe emphysema.

[0005] Although such treatment modalities can provide real benefits to patients in need thereof, there continues to be a need for improved approaches to treating patients presenting with various lung conditions. Embodiments of the present invention provide solutions for at least some of these outstanding needs.

BRIEF SUMMARY OF THE INVENTION

[0006] Embodiments of the present invention encompass systems and methods for pre treatment planning and for real-time visualization of pulmonary treatments, such as lung volume reduction therapies. [0007] Therapeutic and planning techniques disclosed herein can provide detailed and enhanced real time visualization in the lungs, especially in coil placement approaches. The techniques disclosed are well suited for use in procedures such as coil delivery' that result in a changing tissue morphology within the lungs that occurs throughout a duration of the treatment process. Exemplary planning techniques can account for any distortion of the airways that occurs upon deployment of one or more coils within the patient lung, for example due to incremental lung volume reduction and compression of the tissue associated with implantation of the coils.

[0008] Exemplary embodiments provide a series of three-dimensional maps or models for a corresponding series of coil placements. Advantageously, such models are well suited for use in therapeutic procedures that involve the administration, because use of the models can reduce the time required to deliver the coils, which can include up to 10 to 14 coil placements, for example. Because a full treatment can involve two procedures (implantations into each lung of a patient), such a protocol would include the placement of 20-28 coils (TO to 14, multiplied by 2). In some instances, a procedure may involve the implantation of 2 or more coils (for a total treatment of 4 coils). In some instances, a procedure may involve the implantation of up to 18 coils (for a total treatment of 36 coils).

[0009] Accordingly, the techniques disclosed herein can be associated with potentially fewer adverse events and faster procedure times, with the patient being exposed to less fluoroscopy and radiation.

[0010] In some cases, the pre-planning techniques can be used in conjunction with coil parameter engines or electromagnetic navigational systems. For example, as designated coils are calculated to distort the airways due to the incremental lung volume reduction and compression of tissue that each coil imparts, the changes in patient-specific models can be used for navigation purposes.

[0011] In a first aspect, embodiments encompass systems and methods for developing a lung volume reduction treatment plan for a patient. Exemplary' methods include obtaining a validated computational pulmonary system model, obtaining a computerized tomography (CT) scan of a lung of the patient, developing a first personalized three-dimensional pulmonary' model for the patient based on the computerized tomography (CT) scan of the lung of the patient and the validated computational pulmonary system model, selecting a first lung coil design and a first lung coil placement location, developing a second personalized

9 three-dimensional pulmonary model for the patient based on the first personalized three- dimensional pulmonary model for the patient, the first lung coil design, and the first lung coil placement location, and selecting a second lung coil design and a second lung coil placement location, where the selection of the second lung coil placement location is based on the second personalized three-dimensional pulmonary' model for the patient. In some cases, the step of developing the second personalized three-dimensional pulmonary model for the patient is based on a finite element analysis of the first personalized three-dimensional pulmonary model. In some cases, the step of developing the second personalized three- dimensional pulmonary model for the patient is based on a finite element analysis of the first lung coil design. In some cases, the step of developing the second personalized three- dimensional pulmonary_'· model for the patient is based on a finite element analysis of the first lung coil placement location

[0012] In another aspect, methods of developing a lung volume reduction treatment plan for a patient can include receiving, at a processor system, a validated computational pulmonary system model, and receiving, at the processor system, a computerized tomography (CT) scan of a lung of the patient. Methods may also include developing, with the processor system, a first personalized three-dimensional pulmonary' model for the patient based on the computerized tomography (CT) scan of the lung of the patient and the validated computational pulmonary system model, and selecting a first lung coil design and a first lung coil placement location. Further, methods may include developing, with the processor system, a second personalized three-dimensional pulmonary model for the patient based on the first personalized three-dimensional pulmonary model for the patient, the first lung coil design, and the first lung coil placement location, and selecting a second lung coil design and a second lung coil placement location, wherein the selection of the second lung coil placement location is based on the second personalized three-dimensional pulmonary' model for the patient. In some cases, the step of developing the second personalized three- dimensional pulmonary model for the patient is based on a finite element analysis of the first personalized three-dimensional pulmonary model. In some cases, the step of developing the second personalized three-dimensional pulmonary model for the patient is based on a finite element analysis of the first lung coil design. In some cases, the step of developing the second personalized three-dimensional pulmonary model for the patient is based on a finite element analysis of the first lung coil placement location. [0013] In yet another aspect, embodiments of the present invention encompass systems for developing a lung volume reduction treatment plan for a patient. Exemplary systems include a first input that receives a validated computational pulmonary system model, a second input that receives a computerized tomography (CT) scan of a lung of the patient, a third input that receives a first lung coil design selection, a fourth input that receives a first lung coil placement location, a processor, and computer executable code stored on a non-transitory tangible computer readable medium. The computer executable code can include instructions that when executed on the processor cause the processor to develop a first personalized three- dimensional pulmonary model for the patient based on the computerized tomography (CT) scan of the lung of the patient and the validated computational pulmonary' system model, and to develop a second personalized three-dimensional pulmonary model for the patient based on the first personalized three-dimensional pulmonary model for the patient, the first lung coil design selection, and the first lung coil placement location. In some cases, the instructions cause the processor to develop the second personalized three-dimensional pulmonary' model using a finite element analysis of the first personalized three-dimensional pulmonary model. In some cases, the instructions cause the processor to develop the second personalized three-dimensional pulmonary' model using a finite element analysis of the first lung coil design. In some cases, the instructions cause the processor to develop the second personalized three-dimensional pulmonary model using a finite element analysis of the first lung coil placement location

[0014] In still yet another aspect, embodiments of the present invention encompass computer program products for developing a lung volume reduction treatment plan for a patient. Exemplary' computer program products can be embodied on a non-transitory' tangible computer readable medium. Exemplary' computer program products can include computer code for receiving a validated computational pulmonary' system model, computer code for receiving a computerized tomography (CT) scan of a lung of the patient, computer code for developing a first personalized three-dimensional pulmonary model for the patient based on the computerized tomography (CT) scan of the lung of the patient and the validated computational pulmonary' system model, computer code for receiving a first lung coil design, computer code for receiving a first lung coil placement location, and computer code for developing a second personalized three-dimensional pulmonary model for the patient based on the first personalized three-dimensional pulmonary model for the patient, the first lung coil design, and the first lung coil placement location. In some cases, the computer code for developing a second personalized three-dimensional pulmonary model can include computer code for using a finite element analysis of the first personalized three-dimensional pulmonary model. In some cases, the computer code for developing a second personalized three- dimensional pulmonary model can include computer code for using a finite element analysis of the first lung coil design. In some cases, the computer code for developing a second personalized three-dimensional pulmonary' model can include computer code for using a finite element analysis of the first lung coil placement location.

[0015] Aspects of the disclosed methods and systems may be suitable for use following diagnosis of a lung condition such as chronic obstructive pulmonary disease (COPD) in a patient in the design of a therapeutic treatment such as lung volume reduction using coil implants.

[0016] One aspect provides a method of designing a lung volume reduction treatment, comprising: (a) obtaining CT scan data of the pulmonary system of the patient, (b ) generating a patient-specific three-dimensional lung model by providing the CT scan data to a computational model of the pulmonary system, (c) determining location parameters for placement of a first treatment coil in a lung of the patient, (cl) determining design parameters of the first treatment coil, (e) updating the patient-specific three-dimensional model to incorporate the coil location and deign parameters, (f) determining location parameters for placement of a second treatment coil in a lung of the patient, and/or (g) determining design parameters of the second treatment coil, wherein determining the location parameters and/or design parameters of the second treatment coil is based on the updated patient-specific three- dimensional model. It will further be appreciated that the method can comprise iteratively repeating any of steps (c) - (g) for third, fourth, and subsequent coils. The method can also comprise providing a desired lung volume reduction, the step being repeated until the updated patient-specific three-dimensional model reflects the desired lung volume reduction.

[0017] Determining the design parameters of the coils can comprise selecting from a database of designs available for use, or by use of a model such as a finite element analysis model of coil designs. This can be automatic, using a coil parameter engine to generate parameters based on the desired location. Alternatively, coil design parameters can be applied externally. Determining location parameters can comprise analyzing the patient-specific three-dimensional model to indicate a suitable location for placement of a coil. Alternatively, coil location parameters can be applied externally. [0018] The step of generating a patient-specific three-dimensional model can include analyzing the CT scan data by means of lung densitometry. This can include determining, for a lobar segment, the proportion of lung volume below a predetermined density value (e.g. percentage of voxels less than -950 Hounsfield units (HU) = percent low attenuation area or %LAA). The analysis can also include determining the difference in %LAA between upper and lower lung lobes (A%LAA). The resultant patient-specific three-dimensional model can include an indication of the region of the lung in which lung volume reduction coils can be placed. For example, it may be desired to place lung volume reduction coils in regions of the lung that have a threshold of 20 percent or greater %LAA. Additionally or alternatively, CT scan data can be analyzed for small airways disease by significant bronchial wall thickening. For example, it may not he desirable to place lung volume reduction coils in lungs having small airways disease per the CT analysis.

[0019] Another aspect provides a system for designing a lung volume reduction treatment, comprising: a pulmonary model generator, a coil parameter engine, and/or a communications module. The communications module is configured to receive CT scan data of the pulmonary system of the patient, and optionally external data relating to the design and location of implanted treatment coils. The coil parameter engine is configured to generate design parameters and location parameters of treatment coils to be implanted as part of the lung volume reduction treatment. The pulmonary model generator is configured to generate a patient-specific three-dimensional lung model by providing the CT scan data to a computational model of the pulmonary system, and subsequent to implantation of a coil, update the patient-specific three-dimensional model to incorporate the coil location and design parameters. The pulmonary model generator may also be configured to determine the location parameters and design parameters of the subsequent treatment coils based on the updated patient-specific three-dimensional model. The system can also include a navigation module configured to cooperate with the pulmonary model generator and the coil parameter engine to visualize the placement of coils.

BRIEF DESCRIPTION OF THE DRAWINGS

[0020] A better understanding of the features and advantages of the present invention will be obtained by reference to the attached documents that set forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings of which: [0021] FIGS. 1 A-1C illustrate the anatomy of the respiratory system;

[0022] FIG. 2 illustrates a bronchoscope in combination with a delivery_' device for a lung volume reduction device according to embodiments of the present invention,

[0023] FIGS. 3A-3C illustrate a device implanted within the lungs according to embodiments of the present invention;

[0024] FIGS 4A and 4B illustrate method steps for implanting a device according to embodiments of the present invention;

[0025] FIGS. 5 A and 5B illustrate a length change from delivery to deployed device according to embodiments of the present invention;

[0026] FIG. 6 depicts aspects of a pre-treatment planning system according to an embodiment of the present invention

[0027] FIG. 7 depicts aspect of a pulmonary' model generator for use in an embodiment of the invention.

[0028] FIG. 8 depicts aspect of a coil parameter engine for use in an embodiment of the invention.

[0029] FIG. 9 depicts method steps for use in an embodiment of the invention.

[0030] FIGS. 10 and 11 depict aspects of pre-treatment planning and/or navigation systems and methods according to embodiments of the present invention.

[0031] FIG. 12 depicts aspects of computer-implemented pre-treatment planning, real-time visualization, navigation, and/or robotic systems and methods according to embodiments of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

[0032] Aspects of exemplary validated pulmonary system models and relevant characteristics of such models are discussed in Burrowes et al.,“Computational Modeling Of The Obstructive Lung Diseases Asthma And COPD”, Journal of Translational Medicine, 12 (Suppl. 2) S5 (2014), the content of which is incorporated herein by reference. As described in Burrowes, patient-specific structural models used for three-dimensional CFD can include high-resolution computational meshes of the central airways, and imaging and image processing techniques can be used in the construction, parameterization, and validation of patient-specific computational models. Such models can be based on real human patient data. Burrowes further describes how CT scans can be used for three-dimensional reconstruction. As an example, 300 to 500 CT scan slices, each corresponding to a 1 mm thick slice of lung tissue, spanning from the top of the lung to the bottom of the lung, can be analyzed. Emphysematous regions can be identified using Hounsfield threshold techniques. For example, regions of a CT scan having a value of < -950 HU can be considered as damaged and requiring treatment. Parameters such as the percentage of voxels in a CT scan falling below this limit, and the difference in this percentage between upper and lower lung lobes can be analyzed to determine the region to be treated (for example see the QCT (quantitative computer tomography) service of BTG International Ltd.) Relevant characteristics of a model include aspects of the airway tree, regions of damage in the tissue (e.g. emphysematous). By using such models, embodiments of the present invention enable physicians to become familiar with the airway tree of a patient, and to become familiar with what effects certain coil implantation protocols may have on the patient.

[0033] The airways of a patient’s lung include various branched configurations that include short segments, into which treatment coils can be implanted. When a coil is implanted in an airway, it can operate to bend and distort the airway, to compress tissue, to put stress on other nearby airways, and/or to move other nearby airways. Hence, in a procedure during which multiple coils are implanted into the airways of a patient’s lung, the tissue morphology can change significantly throughout the process as the coils are implanted. Embodiments of the present invention encompass systems and methods for predicting how a patient’s lung tissue will change throughout the course of a treatment where multiple coils are implanted in the patient’s lung. Relatediy, embodiments of the present invention encompass systems and methods for predicting how a patient’s lung tissue will change throughout the course of a treatment where adhesive or glues are administered to the patient’s lung. Exemplary adhesive and glues suitable for administration to a patient’s lung include those discussed in U.S. Patent Nos. 7,468,350; 7,553,810, 7,608,579; 7,678,767; 7,932,225, 8,431,537; and RE 46,209, in U.S. Patent Publication Nos. 2005/0281739; 2005/0281740; 2005/0281796; 2005/0281798; 2005/0281799; 2005/0281800; and 2014/0073588, and U.S. Patent Application No. 15/277,829, the entire contents of each of which are incorporated herein by reference for all purposes. Similarly, embodiments of the present invention encompass systems and methods for predicting how a patient’s lung tissue will change throughout the course of a treatment where anchors or other mechanical lung volume reduction devices are administered to the patient’s lung. Exemplary anchors and other mechanical lung volume reduction devices suitable for administration to a patient’s lung include those discussed in U.S. Patent Nos. 6, 174,323; 6,599,311 ; and 6,997,189, and U.S. Patent Publication Nos. 2016/0015377 and 2016/0015394, and PCI Patent Publication Nos. W02015006729 and WG2016115193, the entire contents of each of which are incorporated herein by reference for all purposes

[0034] A validated computational model of the pulmonary system can be used to create a patient specific three-dimensional pulmonary' model, for example based on computerized tomography (CT) scans obtained from a patient prior to administration of a treatment. An example of a three-dimensional pulmonary model is the pulmonary module of the MIMIC model from MATERIALISE N.V. of Belgium.

[0035] Using computational finite element models of individual coil models (for example a 100 mm, 125 mm, and 150 mm coil models, or other design configurations), it is possible to create step by step computational models that can be applied to determine and plan the placement of coils by determining the appropriate coil size in each airway, the number of coils required, and the desired implant locations in order to achieve or maximize lung volume reduction. It has been observed that increased lung volume reduction on a lobar level to the most damaged lobe is correlated with improved patient outcomes such as RV, FEVl, SGRQ, and 6MWT.

[0036] The patient specific three-dimensional pulmonary models can be used beyond planning by applying each step by step lung/coil three-dimensional model reconstruction to an electromagnetic coil parameter engine and navigational system so that coil placements can readily be visualized by the physician like an augmented reality screen. In addition to aiding a physician in coil placement, a pre-planned procedure with this augmented reality could also be programmed into a robot for an automated and precise coil delivery_' technique.

[0037] Embodiments of the present invention enable particularly effective real time visualization in the lungs, especially during coil placement procedures. In some cases, a three-dimensional model or map of the lungs, optionally in combination with use of a coil parameter engine or electromagnetic navigational system, can be relied upon as an aid during coil placement. Upon deploying a coil into the lung, the configuration of the lung can change because the implanted coil distorts the airways. By determining the incremental lung volume reduction and compression of tissue, embodiments disclosed herein are particularly effective in generating useful three-dimensional maps of the lungs, which encompass these changes and can be used for navigation and treatment planning purposes.

[0038] Pulmonary Treatment Devices

[0039] By way of background and to provide context for embodiments of the present invention, FIG. 1A illustrates the respiratory system 10 located primarily within a thoracic cavity l l. This description of anatomy and physiology is provided in order to facilitate an understanding of embodiments of the present invention. Persons of skill in the art, will appreciate that the scope and nature of the invention is not limited by the anatomy discussion provided. Further, it w ll be appreciated there can be variations in anatomical characteristics of an individual, as a result of a variety of factors, which are not described herein. The respiratory system 10 includes the trachea 12, which brings air from the nose 8 or mouth 9 into the right primary bronchus 14 and the left primary bronchus 16. From the right primary bronchus 14 the air enters the right lung 18; from the left primary bronchus 16 the air enters the left lung 20. The right lung 18 and the left lung 20, together comprise the lungs 19. The left lung 20 is comprised of only two lobes while the right lung 18 is comprised of three lobes, in part to provide space for the heart typically located in the left side of the thoracic cavity 11, also referred to as the chest cavity.

[0040] As shown in more detail in FIG. IB, the primary_' bronchus, e.g. left primary bronchus 16, that leads into the lung, e.g. left lung 20, branches into secondary bronchus 22, and then further into tertiary bronchus 24, and still further into bronchioles 26, the terminal bronchiole 28 and finally the alveoli 30. The pleural cavity 38 is the space between the lungs and the chest wall. The pleural cavity 38 protects the lungs 19 and allows the lungs to move during breathing. As shown in FIG. 1C, the pleura 40 defines the pleural cavity 38 and consists of two layers, the visceral pleurae 42 and the parietal pleurae 44, with a thin layer of pleural fluid therebetween. The space occupied by the pleural fluid is referred to as the pleural space 46. Each of the two pleurae layers 42, 44, are comprised of very porous mesenchymal serous membranes through which small amounts of interstitial fluid transude continually into the pleural space 46. The total amount of fluid in the pleural space 46 is typically slight. Under normal conditions, excess fluid is typically pumped out of the pleural space 46 by the lymphatic vessels.

lu [0041] The lungs 19 are described in current literature an elastic structure that float within the thoracic cavity 1 1. The thin layer of pleural fluid that surrounds the lungs 19 lubricates the movement of the lungs within the thoracic cavity 1 1. Suction of excess fluid from the pleural space 46 into the lymphatic channels maintains a slight suction between the visceral pleural surface of the lung pleura 42 and the parietal pleural surface of the thoracic cavity 44 This slight suction creates a negative pressure that keeps the lungs 19 inflated and floating within the thoracic cavity 11. Without the negative pressure, the lungs 19 collapse like a balloon and expel air through the trachea 12 Thus, the natural process of breathing out is almost entirely passive because of the el astic recoil of the lungs 19 and chest cage structures. As a result of this physiological arrangement, when the pleura 42, 44 is breached, the negative pressure that keeps the lungs 19 in a suspended condition disappears and the lungs 19 collapse from the elastic recoil effect.

[0042] When fully expanded, the lungs 19 completely fill the pleural cavity 38 and the parietal pleurae 44 and visceral pleurae 42 come into contact. During the process of expansion and contraction with the inhaling and exhaling of air, the lungs 19 slide back and forth within the pleural cavity 38. The movement within the pleural cavity 38 is facilitated by the thin layer of mucoid fluid that lies in the pleural space 46 between the parietal pleurae 44 and visceral pleurae 42. As discussed above, when the air sacs in the lungs are damaged 32, such as is the case with emphysema, it is hard to breathe. Thus, isolating the damaged air sacs to improve the elastic structure of the lung improves breathing.

[0043] FIG. 2 illustrates a bronchoscope 50 having a lung volume reduction delivery device 80 and a working head 52. The lung volume reduction delivery device can be used for delivering a lung volume reduction device comprising an implantable device. The lung volume reduction system, as described in further detail elsewhere herein, is adapted and configured to he delivered to a lung airway of a patient in a delivered configuration and then changed to a deployed configuration. By deploying the device, tension can be applied to the surrounding tissue which can facilitate restoration of the elastic recoil of the lung. The device is designed to be used by an interventionaiist or surgeon. Exemplary aspects of such bronchoscopes, delivery devices, and/or reduction devices can be found in US Patent Publication No. 2016/0113657, the content of which is incorporated herein by reference.

[0044] FIGS. 3A-C illustrate aspects of an exemplary process of implanting a device 17 within a lung. As is evidence, a device 17 is advanced in a configuration where the device adapts to the anatomy of the lungs through the airways and into, for example, the bronchioles until it reaches a desired location relative to the damaged tissue 32. The device 17 can then he activated, for example, by engaging an actuation device, causing the device to curve and pull the lung tissue toward the activated device (see, FIG. 3B). The device 17 continues to be activated until the lung tissue is withdrawn a desired amount, such as depicted in FIG. 3C. As will be appreciated by those skilled in the art, withdrawing the tissue can be achieved by, for example, curving and compressing a target section of lung tissue upon deployment of one of the configurable devices disclosed herein. Once activated sufficiently, the deployment device is withdrawn from the lung cavity.

[0045] A variety of steps for performing a method according to the invention would be appreciated by those skilled in the art upon review of this disclosure. A non-limiting example of a method according to embodiments of the invention is described with reference to the diagram of FIG. 4A. Firstly, the device is inserted, at step 111. The device is then activated, at step 113. This activation may be achieved, by way of example, by activating an actuator. The device may then be bent, at step 115, into a desired configuration. The bending into a desired configuration may involve locking the device into a deployed condition. As will be appreciated the step of bending the device can be achieved by further activating the actuator, as described above, or by the implant being restored into a preconfigured shape.

[0046] In one embodiment, the device operation includes the step of inserting a bronchoscope into a patient’s lungs and then inserting an intra-bronchial device or lung volume reduction device into the bronchoscope. The intra-bronchial device is then allowed to exit the distal end of the bronchoscope where it is pushed into the airway. A variety of methods can then be used to verify the positioning of the device to determine if the device is in the desired location. Suitable methods of verification include, for example, visualization via visualization equipment, such as fluoroscopy, CT scanning, and the like. Thereafter the device is activated by pulling the pull wire proxima!ly (i.e., toward the user and toward the exterior of the patient's body). At this point, another visual check can be made to determine whether the device has been positioned and deployed desirably. Thereafter, the device can be fully actuated and the ratchet can be allowed to lock and hold the device in place. Thereafter, the implant is decoupled from the delivery catheter and the deliver}_' catheter is removed.

[0047] A non-limiting example of a method according to embodiments of the invention is described with reference to the diagram of FIG. 4B. Firstly, the device is strained into a deliverable shape, at step 112. In some cases, step 112 can involve applying bending loads or force to strain a device from a first shape into a deliverable shape without plastically or permanently bending the device. The device is then inserted into a patient, at step 114. In some cases, step 114 can involve delivering the device into the patient using the bronchoscope or other delivery system components to hold the device in a deliverable shape while it is being introduced. The device may then be released from constraint, at step 1 16, to allow the device to recover to the original shape. In some cases, step 1 16 can involve removing the constraint used to hold the device to allow it to recover back to its first shape. Elastic recover of the device will drive the device to a more bent condition that wall apply force to nearby lung tissue. The bending forces locally compress tissue near the implant and apply tension on lung tissue in surrounding regions to restore lung recoil and enhance breathing efficiency. The first shape is adapted to be elastically constrained by a delivery device to a deliverable configuration whereby removal of the delivery device allows the implant to recoil and be reshaped closer to its first shape.

[0048] FIGS. 5A and SB illustrate how a device length can be reduced when the device is deployed in situ. The device shown in the delivery configuration 121 in FIG. 5A is also shown in the deployed configuration 123 in FIG. SB The distance A between the device ends 122 is large while the device is constrained by a constraining cartridge device 125. Distance A is similar when the device is constrained by a loading cartridge, catheter or bronchoscope. FIG. SB shows the same device in a deployed configuration 123 in an airway 127 that has been deformed by the shape recovery of the implant device. FIG. SB shows that the distance B between the device ends 122 is substantially shorter after the device is deployed.

[0049] Treatment Planning

[0050] FIG. 6 depicts aspects of an exemplary system for developing a lung volume reduction treatment plan for a patient, according to embodiments of the present invention. As shown here, system 200 includes networked elements in connectivity with one another, such as a pulmonary model generator 202, a communications module 204, and a coil parameter engine 206. The pulmonary model generator 202 is configured to generate a three- dimensional pulmonary model using and previously acquired images such as CT slices.

[0051] The coil parameter engine 206 is configured to determine the appropriate coil parameters required for a coil to achieve the desired effect. The coil parameter engine 206 is connected to pulmonary model generator 202 and communications module 204. The coil parameter engine 206 is configured to receive inputs such as the desired lung volume reduction (LVR) and other parameters set by the physician from the communications module 204, patient parameters from communications module 204 and pulmonary model generator 204, and pulmonary model details from pulmonary model generator 204. The coil parameter engine 204 is configured to provide outputs such as recommended coil size and recommended coil location to the pulmonary model generator 204 and communications module 204.

[0052] The communications module 204 is connected to the pulmonary model generator 202 and coil parameter engine 206 and enables input into the system of externally provided information, such as imaging data and user commands. The communications 204 module enables output to the user of data provided by the pulmonary model generator 202 and coil parameter engine 206.

[0053] The pulmonary model generator 202 is configured to generate a personalized three- dimensional pulmonary model using CT data, and to generate modified versions of the personalized model to reflect changes in the geometry of the pulmonary model as coils are deployed therein. The pulmonary model generator 202 is connected to the communications module 204 and the coil parameter engine 206.

[0054] FIG. 7 depicts aspects of an exemplary pulmonary model generator 202 that can be used in systems and methods for developing a lung volume reduction treatment plan for a patient, according to embodiments of the present invention. As shown here, the pulmonary model generator 202 can be configured to receive a validated computational model of the pulmonary system, as shown in step 204, to receive a CT scan of the patient lung, as shown in step 206, to generate a patient-specific three-dimensional model for the lung, as shown in step 208, to determine whether there has been a coil placement, as shown in step 210, to receive a coil design and location, as shown in step 212, and to generate a next iteration of a patient-specific three-dimensional model for the lung, as shown in step 214.

[0055] FIG. 8 depicts aspects of an exemplary coil parameter engine 206 that can be used in systems and methods for developing a lung volume reduction treatment plan for a patient, according to embodiments of the present invention. In some instances, a coil parameter can include a coil location. In some instances, a coil parameter can include a coil design or size. Hence, a coil parameter engine can be used to determine a coil location, a coil design, or a coil location and a coil design. As shown here, the coil parameter engine 206 can be configured to receive a latest patient-specific three-dimensional model for a lung, as shown in step 216, to receive physician input, as shown in step 218, to generate recommended coil parameters, as shown in step 220, to determine whether there has been a coil placement, as shown in step 222, to receive parameters of a used coil, as shown in step 224, and to determine whether an additional coil placement is required, as shown in step 226.

[0056] FIG. 9 depicts aspects of an exemplary method for developing a lung volume reduction treatment plan for a patient, according to embodiments of the present invention. As illustrated in FIG. 9, method 300 includes obtaining a validated computational pulmonary system model, as indicated by step 302, and obtaining a computerized tomography (CT) scan of a lung of the patient, as indicated by step 304. A computerized tomography scan can include information that can be represented in three dimensions, related to for example the size of the lungs, the density of the lungs, the shape of the lungs, the presence of any holes in the lungs, the thickness of any airway walls within the lungs, the presence of any tissue collapse within the lungs, and the like.

[0057] According to some embodiments, a validated computational model of the pulmonary system can be a generic model (e.g. MIMIC pulmonary module). According to some embodiments, a validated computational model of the pulmonary system can be an open source model. In some cases, a validated computational model of the pulmonary system can reflect that the lung tissue has certain properties, for example the alveoli have certain mechanical properties, the lungs function in a certain way due to their location within a ribcage, or due to the presence of a beating heart (with associated vessels) in close proximity with the lungs. In some instances, the validated computational model of the pulmonary system can reflect the presence of physical interactions between the lungs and other organs in the patient’s body.

[0058] In some cases, the validated computational pulmonary' system model can incorporate information related to the strength of the lung tissue, the mechanical properties of the lung tissue, and the like. Such information can be applied to the computerized tomography (CT) scan, so as to obtain a finite element analysis model of the patient’s lung.

[0059] As shown here, it is possible to create a patient specific three-dimensional model of a pulmonary system (three-dimensional pulmonary model) based on CT scan(s) of a lung of the patient. A CT scan of the lung can be obtained prior to a coil implantation treatment procedure. In some embodiments, a software algorithm can be used to create a three- dimensional image or model of the lung based on a CT scan.

[0060] Method 300 can also include developing a first personalized three-dimensional pulmonary model for the patient based on the computerized tomography (CT) scan of the lung of the patient and the validated computational pulmonary system model, as indicated by step 304.

[0061] Further, method 300 can include selecting a first lung coil design and a first lung coil placement location, as indicated by steps 308 and 310, respectively, and developing a second personalized three-dimensional pulmonary model for the patient, as indicated by step 312, based on the first personalized three-dimensional pulmonary model for the patient 306, the computational finite element model of the first lung coil design 308, and the first lung coil placement location 310. Optionally, the selection of the first lung coil placement location 310 can be based on the first personalized three-dimensional pulmonary model for the patient 306. In addition to or instead of selecting the first coil location 310 based on the first model 306, is it also possible to select the first coil design 308 based on the first model 306.

[0062] In this way, it is possible to use a CT scan to prepare a three-dimensional reconstruction of the airway map of a patient, using a validated computational mode, that takes into account tissue changes that are imparted due to the implantation of a coil. Hence, it is possible to predict how the patient’s lung will appear following a coil implantation.

[0063] According to some embodiments, systems and methods disclosed herein can incorporate any of a variety of coil designs, including without limitation, coil designs such as those described in U.S. Patent Nos. 8,157,823; 8,721,734; 9,402,633; and 9,474,533, and U.S. Patent Publication Nos. 2017/0027584 and 2017/0065282, the entire contents of each of which are incorporated herein by reference for all purposes.

[0064] In some instances, selection of the first coil design and/or first coil placement location can be performed independently fro any information related to the validated computational model. In some cases, selection of the first coil design and/or first coil placement location can be performed using information from the patient’s CT scan.

[0065] In some cases, it is possible to use a computational finite element model for a coil design or model (for example a 100 mm coil design, 125 mm coil design, or a 150 mm coil design) when developing a second (or subsequent) personalized three-dimensional pulmonary model for the patient. A step by step computational model can be made and applied to find and plan the appropriate coil sizes per airway, the number of coils, and the desired location in order achieve a desired lung volume reduction

[0066] As depicted here, method 300 can also include selecting a second lung coil design and a second lung coil placement location, as indicated by steps 314 and 316, respectively. According to some embodiments, the selection of the second lung coil placement location can be based on the second personalized three-dimensional pulmonary' model for the patient. In addition to or instead of selecting the second location 316 based on the second model 312, is it also possible to select the second design 314 based on the second model 312. In some embodiments, it is possible to select all coil design sizes ahead of time, based on which airways a physician wants to treat and then measuring the lengths of the airways from a three- dimensional reconstructed model (e.g. CT) of the patient’s lungs.

[0067] In this way, the treatment plan can include a series of coil designs and placement locations (e.g. first coil design and placement location, second coil design and placement location, third coil design and placement location, and so on). In some cases, the first pulmonary model depicted in step 306 can be considered as a first baseline, which is then updated based on information concerning the first coil so as to obtain a second baseline, as depicted in step 312. In turn, the second baseline can then be updated based on information concerning the second coil so as to obtain a third baseline, as depicted in step 318, and so on. Accordingly, each successive baseline can take into account information based on the previously implanted coil (or the previously designated coil for implantation), and each baseline can provide a representation of the whole tissue morphology of the lung and can reflect how that whole tissue morphology changes each time additional coils are implanted (or designated for implantation).

[0068] According to some embodiments, the successive series of baseline representations (patient specific pulmonary model) can effectively provide an alternative to live imaging of the lungs.

[0069] Method 300 can further include developing a third personalized three-dimensional pulmonary model for the patient, as indicated by step 318, based on the second personalized three-dimensional pulmonary model for the patient, the second lung coil design, and the second lung coil placement location. [0070] In this way, it is possible to develop a series of computational models in a step by step fashion, and the models can be applied to find and plan the appropriate coil sizes per airway, the number of coils, and the desired location in order to treat the patient (e.g. by targeting and achieving a desired lung volume reduction). In some cases, the models can be used to help determine the order and/or position of placement of the various selected coil designs (e.g. 100 mm coil design at first location followed by 150 mm coil design at second location). In some cases, the coil locations may be selected based on an evaluation of the ease of access. In some cases, the models can be used to help determine a desired number of coils to use (e.g. a sufficient number of coils to provide a threshold of lung volume reduction that should result in maximum benefit in terms of response to the patient, but also not an excessive number of coils which could lead to tissue damage occurs due to too much tensioning). In some cases, the coils may be selected based on an evaluation of the morphology' of the tissue (e.g. amount of emphysema destruction, nodules or dense areas to be avoided, or fibrotic or bronchiectatis areas to be avoided).

[0071] Hence, a CT scan can be used to develop a coil by coil computational series of models (e.g. steps 306, 312, 318), and the models can be used to determine coil placement locations and other coil parameters. An exemplary treatment plan can include designating a first coil (design, placement location), and then performing a three-dimensional construction of what the finite element model looks like using that coil (e.g. step 312). Thereafter, a designated second coil can be used to perform a three-dimensional construction of what the finite element model looks like using the first and second coils (e.g. step 318).

[0072] The series of computational patient-specific models (e.g. 10 models) can constitute a virtual treatment plan and can be used by a physician or operator to perform a pulmonary therapy procedure. The series of models can also be used to illustrate or visualize what a desired surgical outcome might look like.

[0073] In some cases, a treatment procedure may involve the implantation of 10, 11, or 12 coils into one side of the lung (i.e. right or left). In some cases, a treatment procedure may involve the implantation of a total of 20 to 28 coils into both sides (i.e. right and left) of the lungs. In some cases, a treatment procedure may involve the implantation of a total of less than 20 coils overall.

[0074] According to some embodiments, a treatment plan can be developed in order to target or achieve a desired patient outcome, for example RV (residual volume), SGRQ (St. George Respiratory Quotient), a 6 minute walk test for chronic obstructive pulmonary disease (COPD), or a forced expiratory volume (FEV1) test.

[0075] In some cases, a treatment plan can include a designation of a certain number of coils (e.g. seven coils having a 100 mm design and three coils having a 150 mm design) prescribed for certain implantation positions within the lung.

[0076] In some cases, a physician or operator may develop a series of treatment plans, and then select one plan from the series of plans for administration to the patient. In some cases, the plan can be selected on the basis of any of a variety of patient outcome targets, such as lung volume reduction, RV, SGRQ (St. George Respiratory- Quotient), a six minute walk test (6MWT) for chronic obstructive pulmonary' disease (CGPD), a forced expiratory' volume (FEV1) test, or the like. In some cases, the selected plan can be implemented using a coil parameter engine or navigational system, as disclosed elsewhere herein.

[0077] Hence, prior to the actual placement of a coil within a patient’s lung, it is possible to map out, coil by coil, a treatment plan that includes the location and types or sizes of coils, as well as the sequence of administration. In some cases, a treatment plan may include multiple coils to be multiply implanted in one lobe of the lung at a time.

[0078] In some cases, the series of successive models may change depending on the size, location, and/or order of the coils which are designated for implantation. In some cases, a treatment protocol can specify multiple coils, at multiple placement locations. Once the implantation process begins and coils are being implanted, the tissue morphology of the patient’s lung continues to change throughout the procedure. The change in tissue morphology can be influenced by the order in which the coils are implanted, the locations at which the coils are implanted, and the types of coils that are implanted. Such changes in tissue morphology can be modeled using the patient-specific three-dimensional models for the patient lung discussed herein. Hence, a series of models or maps can be different from another series, depending on the order, location, and/or type of the coils designated for implantation.

[0079] A therapeutic pulmonary' procedure can involve the implantation of 10 to 12 coils, for example. The patient can be subjected to a fluoroscopy and radiation procedure throughout a portion or all of the implantation procedure, and the implantation procedure can occur over the course of 35 to 60 minutes, for example. In some cases, it is desirable to limit the amount of radiation to which the patient is exposed. Hence, it can be advantageous and more time effective to provide a pre-treatment plan that includes a series of patient-specific models, rather than searching for the next airway to implant during the procedure after each coil is deployed or more onerously obtaining a CT scan each time a coil is implanted and the patient’s lung morphology changes.

[0081] In some eases, the step 312 of developing the second personalized three- dimensional pulmonary model for the patient can be based on a finite element analysis of the first personalized three-dimensional pulmonary model. In some cases, the step 312 of developing the second personalized three-dimensional pulmonary model for the patient can be based on a finite element analysis of the first lung coil design. In some cases, the step 312 of developing the second personalized three-dimensional pulmonary' model for the patient can be based on a finite element analysis of the first lung coil placement location. In this way, it is possible to obtain a finite element analysis related to the patient tissue and/or coil implant, and use the finite element analysis to determine how much lung volume reduction can be achieved for each treatment plan that is developed.

[0082] Similarly, the step 318 of developing the third personalized three-dimensional pulmonary' model for the patient can be based on a finite element analysis of the second personalized three-dimensional pulmonary model. In some cases, the step 318 of developing the third personalized three-dimensional pulmonary model for the patient can be based on a finite element analysis of the second lung coil design. In some cases, the step 318 of developing the third personalized three-dimensional pulmonary model for the patient can be based on a finite element analysis of the second lung coil placement location.

[0083] As noted elsewhere, a CT scan can be used to develop a coil by coil computational series of models (e.g. steps 306, 312, 318), and the models can be used to determine coil placement locations and other coil parameters. In some cases, the coil by coil computational series of models (or series of patient specific three-dimensional reconstructions) can be calculated in an offline manner, and prior to administration of the treatment method to the patient

[0084] Hence, one option for determining a patient-specific three-dimensional pulmonary model involves the use of a finite element analysis of the lung and/or the coil(s) designated for implantation. A finite element analysis can incorporate mechanical properties of the patient’s lung and the coil(s), and in this way can be based on a physical understanding of the lung and coi!(s). A computational analysis can be performed to assess how the patient’s lung and the coil(s) interact.

[0086] In some cases, selection of the first coil design and/or first coil placement location can be performed using information from the patient’s original CT scan. The original CT scan can be processed to provide a map of the airway, and electromagnetic navigation can be used to locate the position in the airway, to assist in accessing the airway, and to place the coil.

[0087] FIG, 10 depicts aspects of an exemplary pre-treatment planning method 400 according to embodiments of the present invention. As shown here, an initial patient-specific model 406 can be developed based on a validated computational model of a pulmonary' system (e.g. generic model) 402 and a pre-treatment CT scan of a patient 404. A desired patient outcome (e.g. lung volume reduction) 208 can be used to determine design and location parameters for a first coil 410 using a coil parameter engine 430. The parameters can include the coil design, type, size, and/or shape, the coil location, the coil order of placement, or any combination thereof A navigation system 440 can be used to visualize and/or determine coil placements or to assist in the placement of the coils within the patient tissue (e.g. first coil 410). As shown here, in some cases a first coil location 409 can be determined using the coil parameter engine 430 and the navigational system 440, and the selection of the first coil 410 can be based on the patient-specific three-dimensional pulmonary model (initial) 406, the first coil location 409, and the desired patient outcome (e.g. lung volume reduction) 408 and coil parameter engine 430.

[0088] A first updated patient-specific three-dimensional pulmonary model 414 can be developed based on the first coil location 409. In some cases, the first updated patient- specific three-dimensional pulmonary model 414 can be developed based on the first coil 410, coil information 412, and the validated computational model of a pulmonary system 402. The desired patient outcome (e.g. lung volume reduction) 408 and coil parameter engine 430 can be used to determine parameters for a. second coil 416. The parameters can include the coil design, type, size, and/or shape, the coil location, the coil order of placement, or any combination thereof. The navigation system 440 can be used to visualize and/or determine coil placements or to assist in the placement of the coils within the patient tissue (e.g. second coil 416) As shown here, in some cases a second coil location 415 can be determined using the coil parameter engine 230 and navigation system 440, and the selection of the second coil 416 can be based on the patient-specific three-dimensional pulmonary model (updated- 1) 414, the second coil location 415, and the desired patient outcome (e.g lung volume reduction) 408.

[0089] A second updated patient-specific three-dimensional pulmonary model 420 can be developed based on the second coil location 415. In some cases, the second updated patient- specific three-dimensional pulmonary model 420 can be developed based on the second coil 416, coil information 418, and the validated computational model of a pulmonary' system 402. The desired patient outcome (e.g. lung volume reduction) 408 can be used to determine parameters for a third coil 422. The parameters can include the coil design, type, size, and/or shape, the coil location, the coil order of placement, or any combination thereof. The coil parameter engine 430 and navigation system 440 can be used to visualize and/or determine coil placements or to assist in the placement of the coils within the patient tissue (e.g. third coil 422). As shown here, in some cases a third coil location 421 can be determined using the coil parameter engine 430 and navigation system 440, and the selection of the third coil 422 can be based on the patient-specific three-dimensional pulmonary model (updated-2) 414, the third coil location 421, and the desired patient outcome (e.g. lung volume reduction) 408.

[0090] According to some embodiments, the approach depicted in FIG, 9 can be used with a navigation system 440.

[0091] As shown in FIG. 10, it is possible to avoid the repetitive use of a CT scan. Put another way, a CT scan can be used only at an early stage to help determine an initial patient- specific model. Thereafter, successive patient-specific models are developed without using successive CT scans. Advantageously, the successive patient-specific models reflect the tissue morphology of the patient lung tissue associated with a series of designated coil implants. In this way, a series of three-dimensional visuals can be provided and used by a coil parameter engine and/or navigational system to assist with the placement of individual coils during a pulmonary treatment method.

[0092] In some embodiments, model information can be input into the navigational system. For example, as illustrated here, information regarding the patient-specific three-dimensional pulmonary model (initial) 406 can be input into the coil parameter engine 430 Similarly, information regarding the patient-specific three-dimensional pulmonary model (updated-!) 414 can be input into the navigational system 440. Likewise, information regarding the patient-specific three-dimensional pulmonary model (updated-2) 420 can be input into the coil parameter engine 430.

[0093] In some embodiments, a navigation system 440 can be a system such as the superDimension™ navigation system (Medtronic Public Limited Company, Dublin, Ireland). In some embodiments, a navigation system 440 can be a system such as the SpiN Thoracic Navigation System™ (Veran Medical Technologies, Inc., St. Louis, MO). In some instances, a patient-specific three-dimensional pulmonary' model (e.g. 406, 414, 420) can be integrated into a system such as a system that incorporates sofiware for detecting, evaluating, and planning treatments for lung diseases, such as VIDAjvision (VIDA Diagnostics, Inc., Coralville, LA), which is a visualization software platform for computed tomography (CT) lung quantification and procedural planning.

[0095] FIG. 11 depicts aspects of an exemplary' pre-treatment planning method 500, as viewed from a user perspective, according to embodiments of the present invention. The method 500 includes inputting a CT scan of a patient lung, as depicted in step 505. Further, the method includes receiving a latest patient-specific three-dimensional model, as depicted in step 510. Method 500 also includes inputting a desired outcome, as depicted in step 515, and receiving recommended coil parameters, as depicted in step 520. As shown in step 525, the method 500 includes determining whether there has been a coil placement. If there w'as a coil placement, then the parameters of the coil that was used can be input, as depicted in step 530. If there was not a coil placement, then the method can end, as depicted at step 540 As shown in step 535, the method 500 can include receiving an updated patient-specific three- dimensional model. As shown in step 535, the method 500 can include determining whether an additional coil is desired. If an additional coil is desired, then the method 500 can further include inputting a CT scan of a patient lung, as depicted in step 510. If an additional coil is not desired, then the method 500 can end, as depicted at step 540.

[0097] In some cases, it is possible to administer a treatment plan to a patient by using a robotic system that operates to deliver the coils to the patient lung tissue. The robotic system can be programmed with the information concerning the coils (e.g. coil type, placement location, order of placement) and the patient models, and therefore the robotic system can be configured to implement a treatment plan. With an automated motorized robotic system, it is possible to rapidly and precisely deliver a therapeutic protocol, to a patient which can help to reduce side effects such as pneumothorax, unwanted bleeding, and the like, and can deliver the protocol in a reduced amount of time (e.g as compared to manual implantation of the coils).

[0098] In some embodiments, a robotic system can be, or include aspects of, a system such as the Auris Robotic Endoscopy System (Auris Surgical Robotics, Inc , San Carlos, CA). In some embodiments, a robotic system can be, or include aspects of, a system such as the da Vinci ® Surgical System (Intuitive Surgical, Inc., Sunnyvale, CA) or a digital surgery platform (Verb Surgical, Inc., Mountain View, CA). In some embodiments, a robotic system can be, or include aspects of, a system such as that described in U.S. Patent Publication No. 2017/0156732, the entire content of which is incorporated herein by reference for all puiposes.

[0099] FIG, 12 is a simplified block diagram of an exemplary computer system 622 that may be used in conjunction with or as part of an implant device delivery system, a navigation system, and/or a robotic system, according to embodiments of the present invention.

[0100] Computer system 622 typically includes at least one processor 652 winch may communicate with a number of peripheral devices via a bus subsystem 654. These peripheral devices may include a storage subsyste 656, comprising a memory subsystem 658 and a file storage subsystem 660, user interface input devices 662, user interface output devices 664, and a network interface subsystem 666. Network interface subsystem 666 provides an interface to outside networks 668 and/or other devices, such as an implant delivery system, a navigation system, and/or a robotic system.

[0101] User interface input devices 662 may include a keyboard, pointing devices such as a mouse, trackball, touch pad, or graphics tablet, a scanner, foot pedals, a joystick, a touchscreen incorporated into the display, audio input devices such as voice recognition systems, microphones, and other types of input devices. User input devices 662 will often be used to download a computer executable code from a tangible storage media embodying any of the methods of the present invention. In general, use of the term“input device” is intended to include a variety of conventional and proprietary devices and ways to input information into computer system 622. [0102] User interface output devices 664 may include a display subsystem, a printer, a fax machine, or non-visual displays such as audio output devices. The display subsystem may be a cathode ray tube (CRT), a flat-panel device such as a liquid crystal display (LCD), a projection device, or the like. The display subsystem may also provide a non-visual display such as via audio output devices. In general, use of the term“output device” is intended to include a variety of conventional and proprietary devices and ways to output information from computer system 622 to a user

[0103] Storage subsystem 656 can store the basic programming and data constructs that provide the functionality of the various embodiments of the present invention. For example, a database and modules implementing the functionality of the methods of the present invention, as described herein, may be stored in storage subsystem 656. These software modules are generally executed by processor 652. In a distributed environment, the software modules may be stored on a plurality of computer systems and executed by processors of the plurality of computer systems. Storage subsystem 656 typically comprises memory subsystem 658 and file storage subsystem 660.

[0104] Memory subsystem 658 typically includes a number of memories including a main random access memory (RAM) 670 for storage of instructions and data during program execution and a read only memory (ROM) 672 in which fixed instructions are stored. File storage subsystem 660 provides persistent (non-volatile) storage for program and data files, and may include tangible storage media. File storage subsystem 660 may include a hard disk drive, a floppy disk drive along with associated removable media, a Compact Digital Read Only Memory (CD-ROM) drive, an optical drive, DVD, CD-R, CD-RW, solid-state removable memory', and/or other removable media cartridges or disks. One or more of the drives may be located at remote locations on other connected computers at other sites coupled to computer system 622. The modules implementing the functionality of the present invention may be stored by file storage subsystem 660.

[0105] Bus subsystem 654 provides a mechanism for letting the various components and subsystems of computer system 622 communicate with each other as intended. The various subsystems and components of computer system 622 need not be at the same physical location but may be distributed at various locations within a distributed network. Although bus subsystem 654 is shown schematically as a single bus, alternate embodiments of the bus subsystem may utilize multiple busses. [0106] Computer system 622 itself can be of varying types including a personal computer, a portable computer, a workstation, a computer terminal, a network computer, a control system in a wavefront measurement system or laser surgical system, a mainframe, or any other data processing system. Due to the ever-changing nature of computers and networks, the description of computer system 622 depicted in FIG. 12 is intended only as a specific example for purposes of illustrating one embodiment of the present invention. Many other configurations of computer sy stem 622 are possible having more or less components than the computer system depicted in FIG. 12.

[0107] All features of the described systems and/or devices are applicable to the described methods mutatis mutandis , and vice versa. Each of the calculations discussed herein may be performed using a computer or other processor having hardware, software, and/or firmware. The various method steps may be performed by modules, and the modules may comprise any of a wide variety of digital and/or analog data processing hardware and/or software arranged to perform the method steps described herein. The modules optionally comprising data processing hardware adapted to perform one or more of these steps by having appropriate machine programming code associated therewith, the modules for two or more steps (or portions of two or more steps) being integrated into a single processor board or separated into different processor boards in any of a wide variety of integrated and/or distributed processing architectures. These methods and systems will often employ a tangible media embodying machine-readable code with instructions for performing the method steps described above. Suitable tangible media may comprise a memory (including a volatile memory and/or a non volatile memory), a storage media (such as a magnetic recording on a floppy disk, a hard disk, a tape, or the like; on an optical memory such as a CD, a CD-R/W, a CD-ROM, a DVD, or the like; or any other digital or analog storage media), or the like. While the exemplary embodiments have been described in some detail, by way of example and for clarity of understanding, those of skill in the art will recognize that a variety of modification, adaptations, and changes may be employed.

[0108] The methods and apparatuses of the present invention may be provided in one or more kits for such use. The kits may comprise a system for delivering a device implant to a patient, and instructions for use. Optionally, such kits may further include any of the other system components described in relation to the present invention and any other materials or items relevant to the present invention. The instructions for use can set forth any of the methods as described herein . [0109] All patent filings, scientific journals, books, treatises, and other publications and materials discussed in this application are hereby incorporated by reference for all purposes. A variety of modifications are possible within the scope of the present invention. A variety of parameters, variables, factors, and the like can be incorporated into the exemplary method steps or system modules. While the specific embodiments have been described in some detail, by way of example and for clarity of understanding, a variety of adaptations, changes, and modifications will be obvious to those of skill in the art.

[0110] While the above provides a full and complete disclosure of exemplary' embodiments of the present invention, various modifications, alternate constructions and equivalents may be employed as desired. Consequently, although the embodiments have been described in some detail, by way of example and for clarity of understanding, a variety of modifications, changes, and adaptations will be obvious to those of skill in the art. Accordingly, the above description and illustrations should not be construed as limiting the invention, which can be defined by the claims.

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Claims

WHAT IS CLAIMED IS:

1. A method of developing a lung volume reduction treatment plan for a patient, the method comprising:

obtaining a validated computational pulmonary system model; obtaining a computerized tomography (CT) scan of a lung of the patient;

developing a first personalized three-dimensional pulmonary model for the patient based on the computerized tomography (CT) scan of the lung of the patient and the validated computational pulmonary system model;

selecting a first lung coil design and a first lung coil placement location;

developing a second personalized three-dimensional pulmonary model for the patient based on the first personalized three-dimensional pulmonary- model for the patient, the first lung coil design, and the first lung coil placement location; and

selecting a second lung coil design and a second lung coil placement location, wherein the selection of the second lung coil placement location is based on the second personalized three-dimensional pulmonary model for the patient.

2. The method according to claim 1 , wherein the step of developing the second personalized three-dimensional pulmonary model for the patient is based on a finite element analysis of the first personalized three-dimensional pulmonary_' model.

3. The method according to claim 1, wherein the step of developing the second personalized three-dimensional pulmonary model for the patient is based on a finite element analysis of the first lung coil design.

4. The method according to claim 1, wherein the step of developing the second personalized three-dimensional pulmonary model for the patient is based on a finite element analysis of the first lung coil placement location.

5. A method of developing a lung volume reduction treatment plan for a patient, the method comprising:

receiving, at a processor system, a validated computational pulmonary- system model; receiving, at the processor system, a computerized tomography (CT) scan of a lung of the patient; developing, with the processor system, a first personalized three-dimensional pulmonary model for the patient based on the computerized tomography (CT) scan of the lung of the patient and the validated computational pulmonary system model;

selecting a first lung coil design and a first lung coil placement location;

developing, with the processor system, a second personalized three- dimensional pulmonary model for the patient based on the first personalized three- dimensional pulmonary model for the patient, the first lung coil design, and the first lung coil placement location; and

selecting a second lung coil design and a second lung coil placement location, wherein the selection of the second lung coil placement location is based on the second personalized three-dimensional pulmonary model for the patient.

6. The method according to claim 5, wherein the step of developing the second personalized three-dimensional pulmonary' model for the patient is based on a finite element analysis of the first personalized three-dimensional pulmonary' model.

7. The method according to claim 5, wherein the step of developing the second personalized three-dimensional pulmonary model for the patient is based on a finite element analysis of the first lung coil design.

8. The method according to claim 5, wherein the step of developing the second personalized three-dimensional pulmonary' model for the patient is based on a finite element analysis of the first lung coil placement location.

9. A system for developing a lung volume reduction treatment plan for a patient, the system comprising:

a first input that receives a validated computational pulmonary' system model; a second input that receives a computerized tomography (CT) scan of a lung of the patient;

a third input that receives a first lung coil design selection;

a fourth input that receives a first lung coil placement location; a processor; and

computer executable code stored on a non-transitory tangible computer readable medium, the computer executable code comprising instructions that when executed on the processor causes the processor to develop a first personalized three-dimensional pulmonary model for the patient based on the computerized tomography (CT) scan of the lung of the patient and the validated computational pulmonary system model, and to develop a second personalized three-dimensional pulmonary model for the patient based on the first personalized three-dimensional pulmonary model for the patient, the first lung coil design selection, and the first lung coil placement location.

10. The system according to claim 9, wherein the instructions cause the processor to develop the second personalized three-dimensional pulmonary model using a finite el ement analysis of the first personali zed three-dimensional pulmonary model.

11. The system according to claim 9, wherein the instructions cause the processor to develop the second personalized three-dimensional pulmonary model using a finite element analysi s of the first lung coil design.

12. The system according to claim 9, wherein the instructions cause the processor to develop the second personalized three-dimensional pulmonary model using a finite element analysis of the first lung coil placement location.

13. A computer program product for developing a lung volume reduction treatment plan for a patient, the product embodied on a non -transitory tangible computer readable medium, comprising:

computer code for receiving a validated computational pulmonary system model;

computer code for receiving a computerized tomography (CT) scan of a lung of the patient;

computer code for developing a first personalized three-dimensional pulmonary model for the patient based on the computerized tomography (CT) scan of the lung of the patient and the validated computational pulmonary' system model;

computer code for receiving a first lung coil design;

computer code for receiving a first lung coil placement location; and computer code for developing a second personalized three-dimensional pulmonary model for the patient based on the first personalized three-dimensional pulmonary model for the patient, the first lung coil design, and the first lung coil placement location.

14. The computer program product according to claim 13, wherein the computer code for developing a second personalized three-dimensional pulmonary model comprises computer code for using a finite element analysis of the first personalized three- dimensional pulmonary model.

15. The computer program product according to claim 13, wherein the computer code for developing a second personalized three-dimensional pulmonary' model comprises computer code for using a finite element analysis of the first lung coil design.

16. The computer program product according to claim 13, wherein the computer code for developing a second personalized three-dimensional pulmonary model comprises computer code for using a finite element analysis of the first lung coil placement location.