WO2010065452A1 - Breath analysis systems and methods for asthma, tuberculosis and lung cancer diagnostics and disease management - Google Patents
Breath analysis systems and methods for asthma, tuberculosis and lung cancer diagnostics and disease management Download PDFInfo
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- WO2010065452A1 WO2010065452A1 PCT/US2009/066103 US2009066103W WO2010065452A1 WO 2010065452 A1 WO2010065452 A1 WO 2010065452A1 US 2009066103 W US2009066103 W US 2009066103W WO 2010065452 A1 WO2010065452 A1 WO 2010065452A1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/08—Measuring devices for evaluating the respiratory organs
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/08—Measuring devices for evaluating the respiratory organs
- A61B5/082—Evaluation by breath analysis, e.g. determination of the chemical composition of exhaled breath
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/08—Measuring devices for evaluating the respiratory organs
- A61B5/097—Devices for facilitating collection of breath or for directing breath into or through measuring devices
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/41—Detecting, measuring or recording for evaluating the immune or lymphatic systems
- A61B5/411—Detecting or monitoring allergy or intolerance reactions to an allergenic agent or substance
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2562/00—Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
- A61B2562/02—Details of sensors specially adapted for in-vivo measurements
- A61B2562/028—Microscale sensors, e.g. electromechanical sensors [MEMS]
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N2030/022—Column chromatography characterised by the kind of separation mechanism
- G01N2030/025—Gas chromatography
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/483—Physical analysis of biological material
- G01N33/497—Physical analysis of biological material of gaseous biological material, e.g. breath
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/483—Physical analysis of biological material
- G01N33/497—Physical analysis of biological material of gaseous biological material, e.g. breath
- G01N33/4975—Physical analysis of biological material of gaseous biological material, e.g. breath other than oxygen, carbon dioxide or alcohol, e.g. organic vapours
Definitions
- the present invention provides systems and methods for low-cost, rapid and accurate diagnosis and monitoring of respiratory ailments such as infections and chronic illnesses and especially asthma, tuberculosis and lung cancer using gas sensor technology.
- Asthma is a chronic lung disease characterized by recurrent episodes of coughing, wheezing, chest tightness and respiratory discomfort. Pulmonary inflammation contributes to the bronchoconstriction that can precipitate an asthma attack, and the progression of this chronic disease. It is estimated that over 20 million people in the United States have asthma. The National Heart Lung and Blood Institute notes that asthma accounts for $16.1 billion in direct and indirect healthcare costs annually.
- TB diagnostics have remained unchanged for decades, despite their acknowledged poor performance.
- Current diagnostic methods include sputum smear microscopy, culture, and chest X-rays. However, these methods either have poor sensitivity (45-60% for smear microscopy), poor specificity (-66% for X-ray), or are too slow (3-6 weeks for culture).
- Lung cancer is a disease of uncontrolled cell growth in tissues of the lung.
- the majority of primary lung cancers are carcinomas of the lung, derived from epithelial cells. Lung cancer, the most common cause of cancer-related death in men and also the most common in women, is responsible for 1.3 million deaths worldwide annually.
- the main types of lung cancer are small cell lung carcinoma (SCLC) and non-small cell lung carcinoma (NSCLC). This distinction is important, because the treatment varies; non-small cell lung carcinoma (NSCLC) is sometimes treated with surgery, while small cell lung carcinoma (SCLC) usually responds better to chemotherapy and radiation.
- SCLC small cell lung carcinoma
- SCLC small cell lung carcinoma
- the present invention provides systems and methods for enabling human breath analysis for the detection, diagnosis and monitoring of respiratory ailments, lung infections and chronic illnesses. Methods for drug efficacy testing are also disclosed.
- the present invention provides a method for detecting whether a subject has asthma or monitoring a subject with asthma, comprising: contacting breath from the subject with an apparatus, the apparatus having a gas chromatograph, wherein the gas chromatograph is fluidly coupled to a detector array to produce a signal; and analyzing the signal from the detector array to determine whether the subject has asthma.
- the apparatus further comprises a preconcentrator upstream of the gas chromatograph.
- the systems and methods increase the specificity, sensitivity and dynamic range of monitoring the grade and severity of asthma over prior art techniques by detecting VOCs, and/or NO, and/or breath flow rate.
- the systems and methods can monitor VOCs for a patient with mild or no asthma.
- the ambient air is monitored and can be saved as a background signal for reference.
- the ambient air is filtered before inhaled by patient.
- the saved background signal is then filtered or subtracted from the signal detected from exhaled breath.
- decisions regarding medication can be managed by monitoring VOCs, NO, and flow rate such as prior to, during and/or after medication treatment.
- the systems and methods disclosed herein provide an early warning of environmental contaminates for asthma patients thereby alerting patients to avoid certain environmental VOCs.
- the methods and systems disclosed herein can be implemented in various formats and platforms such as portable, handheld or laboratory instruments.
- the apparatus can be included or integrated into a gas analyzer, such as GC/MS, GC/FID, GC/optical laser detectors, GC/nano particle sensor, GC/QCM and eNose devices.
- a gas analyzer such as GC/MS, GC/FID, GC/optical laser detectors, GC/nano particle sensor, GC/QCM and eNose devices.
- the present invention provides systems and methods for the detection of TB which are accurate, rapid, and portable such as a point-of-care service which are surprisingly affordable.
- the present invention provides a method for detecting whether a subject has tuberculosis or monitoring a tuberculosis subject, comprising: contacting headspace from a subject's sample or the breath of a subject with an apparatus, the apparatus having a gas chromatograph, wherein the gas chromatograph is fluidly coupled to a detector array to produce a signal; and analyzing the signal from the detector array to determine whether the subject has tuberculosis.
- the apparatus further comprises a preconcentrator upstream of the gas chromatograph.
- the systems and methods disclosed herein are highly sensitivity, with high specificity for TB tests based on a patient's exhaled VOCs and/or gases of cultured TB bacteria.
- the test and analysis is rapid and can be done within minutes.
- the systems and methods are portable and inexpensively detect VOCs of TB patients before, during and after medication to effectively manage and control a TB patient's medication treatment.
- the systems and methods monitor VOCs of a TB culture or a patient before, during and/or after various drug treatments to identify the most effective drug for drug-resistant TB bacteria.
- VOCs volatile organic compounds
- the present methods and systems use a subject's breath, sputum or sputum culture to detect a TB infection.
- headspace sampling from mycobacterium cultures can be used to detect drug resistance bacteria during treatment.
- Medical professionals can detect VOCs of TB patients during the medication to effectively manage and control the TB patients' medication treatment. Further, the methods and systems herein allow the monitoring of VOCs from cultures for drug resistance testing.
- the present invention provides a method for detecting whether a subject has lung cancer or monitoring a subject with lung cancer, comprising: contacting breath from the subject with an apparatus, the apparatus having a gas chromatograph, wherein the gas chromatograph is fluidly coupled to a detector array to produce a signal; and analyzing the signal from the detector array to determine whether the subject has lung cancer.
- the apparatus further comprises a preconcentrator upstream of the gas chromatograph.
- Figure IA-C illustrate one embodiment of the invention for the detection and monitoring of asthma; Panel B illustrates a mouth and lung wash and Panel C illustrates a mouth and lung wash.
- Figure 2 A-B illustrate embodiments of the invention for the detection and monitoring of asthma
- Panel B illustrates one embodiment of the invention for the detection and monitoring of asthma
- Figure 3 illustrates one embodiment of the invention for the detection and monitoring of TB.
- Figure 4 A-B illustrate embodiments of the invention for the detection and monitoring of TB; Panel B illustrates an embodiment of the invention for the detection and monitoring of TB.
- Figure 5 A-B illustrate embodiments of the invention for the detection and monitoring of TB; Panel B illustrates an embodiment of the invention for the detection and monitoring of TB.
- Figure 6 illustrates one embodiment of the invention for the detection and monitoring of TB.
- Figure 7 illustrates one embodiment of the invention for the detection and monitoring of TB.
- Figure 8 illustrates one embodiment of the invention for the detection and monitoring of TB.
- Figure 9 illustrates one embodiment of a classification scheme for asthma.
- FIG. 10A-B illustrate one embodiment for the detection of asthma wherein VOCs are useful for the detection and diagnosis of no asthma or mild Panel A; and NO is useful for the detection of mild and sever asthma Panel B.
- the present invention provides systems and methods useful for low-cost, rapid and accurate diagnosis and monitoring of respiratory ailments such as infections and chronic illnesses.
- the systems and methods disclosed herein can detect chemical and biological marker gases to provide clinical data to healthcare professionals and/or patients for low-cost, rapid and accurate diagnosis of asthma, TB and lung cancer. Methods for drug efficacy testing are also disclosed.
- the present systems and methods provide rapid and accurate diagnoses and monitoring of asthma.
- Asthma is generally considered a chronic inflammatory disease that affects the airways of children and adults, which causes shortness of breath, a tightening in the chest, and is accompanied by coughing, wheezing and respiratory discomfort.
- Symptoms of asthma can vary from person to person.
- Asthma symptoms further include blockage of the flow of air to a subject. In other words, the inhaled and exhaled breath of the subject is less than in a normal individual. Typically this happens because the airway lining becomes inflamed, irritated, and/or swollen.
- Mucous secretions can also block the airways, and the more inflamed the airway, the more sensitive the airway becomes perpetuating more symptoms.
- the inflammation can also cause the muscles to tighten which is referred to as bronchospasm, which makes it increasingly difficult to breathe.
- FIG. IA illustrates one embodiment of the present invention wherein systems and methods 100 for detecting whether a subject has asthma or monitoring a subject with asthma is shown.
- the method includes contacting ambient air 110 from the inhaled breath from a subject 125 with an apparatus.
- the flow rate and volume 120 of the inhaled breath are optionally measured or/and controlled, and ambient volatile organic compounds (VOCs) and nitric oxide (NO) are measured as baseline level (e.g., for reference).
- VOCs ambient volatile organic compounds
- NO nitric oxide
- the VOCs from the background or ambient air can be filtered out by a filter (e.g., inline) and thereby eliminated 129.
- the filtered inhaled breath then enters the lung of the subject 125.
- the exhaled breath 130 then enters the apparatus.
- a preconcentrator for the exhaled breath 133 e.g., inline
- One example of the apparatus includes a preconcentrator module (for either inhaled breath, exhaled breath or both), a gas chromatograph module and a detector array module 150.
- the detector array module 150 produces a signal indicative of various biomarkers 155 such as VOCs and NO. The signal is analyzed to determine whether the subject has asthma 160 and/or its severity and grade.
- the portable gas analyzer optionally comprises a module that regulates the flow of exhaled breath.
- the exhaled breath can be assisted or regulated to a desired flow rate.
- the module or flow meter 131 e.g., inline
- the rate of the analyte-containing gas through the sensor chamber can vary, the rate can be increased or decreased by the module or flow meter. In one embodiment, a flow rate of about 200 mL/min to about 1000 mL/min is used. In other instances, the flow rate is about 300 mL/min to about 750 mL/min.
- the flow rate is about 400 mL/min to about 650 mL/min. In still yet other instances, the flow rate may be fixed at certain rates such as for example, 600 mL/min, lOOOmL/min, 3000 mL/min, or 6000mL/min, but actual measurements are not limited by these flow rates.
- the methods optionally include a "lung washout,” protocol wherein several deep breaths are taken with pure air by the individual and not measured.
- a mouth wash protocol may optionally be included prior the actual measurement.
- a clean water supply 165 is given to the subject to rinse and wash their mouth 168, and thereafter discarded.
- a clean air supply system 170 is given to the subject 175 to clean the ambient air and is then exhaled 185.
- ambient air containing VOCs and NO 189 is filtered to remove all ambient VOCs and NO 190. In this manner, clean air is passed to the human lung 198 devoid of VOCs and NO. The breath is exhaled 199 and the lung is washed.
- the exhaled breath rate is increased by the module 131 (FIG. IA) with a fan or pump, or by diluting it with additional air, such as compressed air.
- the analyte in the gas phase can be further diluted by mixing it with another gas, such as air.
- humidity can be introduced into the gas sample by bubbling air (or an inert gas) through water at a given temperature, and then mixing it with the gas containing the analyte vapor. The rate of the exhaled air can be reduced using the module to restrict air flow.
- the methods herein employ a portable gas analysis system (PGAS) with a small form factor such as disclosed in U.S. Patent Application No. 12/140,822 filed June 17, 2008 and entitled "Handheld Breath Analysis Microsystems for Rapid Disease Classification, Disease Diagnostics and Health Monitoring," which is incorporated herein by reference.
- the breath analysis and ambient air monitoring can be done routinely by physician and patients.
- the methods and systems disclosed herein can be applied to bench-top or central-lab instruments, such as, for example, a GC/MS.
- the breath of the subject contains markers or biomarkers suitable for the detection, diagnosis and monitoring of for example, asthma.
- the biomarker detected by the methods and systems is a volatile organic compound (VOC) or a plurality of such compounds (VOCs).
- VOC volatile organic compound
- the VOC is a member selected from the group of 4-methyloctane, 2,4-dimethylheptane, isopropanol, toluene, isoprene, alkane, acetic acid, acetone, 2,6,11-trimethyl dodecane, 3,7-dimethyl undecane, 2,3- dimethyl heptane or a combination thereof.
- the breath gas or marker is nitric oxide.
- the methods of the present invention enable detecting both NO and VOCs from exhaled breath with increased specificity and greater dynamic range compared to prior art methods.
- exhaled NO concentration measurements correlate with asthma control during treatment (see, for example, Jones SL, Kittelson J, Cowan JO et al., Am JRespir Crit Care Med.; ⁇ A:l ⁇ -lA7> (2001); Beck-Ripp J, Griese M, Arenz S, et al, Eur. Respir. J, 19:1015-1019 (2002)).
- NO concentration levels can be an overall marker of airway inflammation.
- the NO concentration level in conjunction with VOCs can be used to detect, diagnose and monitor asthma.
- ambient air is monitored for VOCs and saved as a baseline level for reference.
- the inhaled air is filtered from the ambient VOCs before entering the patient's lung. In other words, by filtering the ambient VOCs, the subject inhales VOC-free air.
- the inhaled breath is also measured for flow rate and volume.
- the exhaled breath is collected for NO and VOCs detection together with reference of flow rate and volume for asthma assessment.
- the grade and severity of asthma is determined.
- a VOC concentration or a plurality of VOCs is used to characterize or diagnose asthma as intermittent, mild, moderate or asthma.
- NO concentration level is used to characterize asthma as severe asthma.
- the grade of asthma is usually categorized as being intermittent, mild, moderate, severe or combinations of the foregoing such as mild to moderate or moderate to severe.
- the systems and methods of the present invention give high specificity and high sensitivity for the diagnosis of asthma.
- the methods and systems of the present invention enhance dynamic range are very accurate and thus can differentiate the grade and severity of asthma ⁇ e.g., mild from severe).
- NO concentration levels and VOCs identity and amounts of the exhaled human breath are correlated to grade and severity of asthma.
- the term "sensitivity" refers to the probability that a diagnostic method or system of the present invention gives a positive result when the sample is positive, e.g., a subject has the disease ⁇ e.g., asthma). Sensitivity is calculated as the number of true positive results divided by the sum of the true positives and false negatives. Sensitivity essentially is a measure of how well a method or system of the present invention correctly identifies those with the disease ⁇ e.g., asthma) from those without the disease.
- the sensitivity of classifying the disease ⁇ e.g. , asthma) is at least about 90% such as about 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% using the systems and methods herein.
- the term "specificity" refers to the probability that a diagnostic method or system, of the present invention gives a negative result when the sample is not positive, e.g., not having the disease (e.g., asthma). Specificity is calculated as the number of true negative results divided by the sum of the true negatives and false positives. Specificity essentially is a measure of how well a method or system of the present invention excludes those who do not have the disease (e.g., asthma) from those who have the disease. In preferred embodiments, the specificity of classifying is at least about 90% such as about 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% using the systems and methods herein.
- the methods and systems herein include the flow rate and volume measurements for the subject.
- the apparatus includes a spirometer to measure the flow rate and/or volume of the inhaled, exhaled or both the inhaled and exhaled breath.
- the patient breathes in methacholine which induces airway narrowing. This procedure can give additional data for the calculation of the grade of asthma.
- methacholine which induces airway narrowing. This procedure can give additional data for the calculation of the grade of asthma.
- the efficacy of a therapeutic can be monitored with periodic breath samples using the methods of the present invention. For example, if an inhaled corticosteroids is used or a bronchodilator is used, the treatment can be assessed with the methods of the present inversion.
- the methods herein include measuring the flow of breath such as inhaled, exhaled or both, preferably using a spirometer.
- the spirometer module is preferably integral to the apparatus.
- the volume and speed of airflow from the breath is measured.
- Subjects can use the apparatus optionally wearing a nose clip, breathing in and out through a disposable mouthpiece. Breath is then sampled at approximately 2.0 liters/min for about 2-5 minutes and drawn through a preconcentrator to capture the VOCs. A sample of ambient room air is collected in a similar fashion onto another preconcentrator.
- the subject is on a ventilator such as in a hospital setting, and so the apparatus disclosed herein is in fluid communication with the lung of the subject.
- the breath of the subject is from a bag configured to collect breath from the subject (see, for example, U.S. Patent Nos. 5,465,728 or 6,723,056).
- the breath can be concentrated using the preconcentrator module of the apparatus.
- the preconcentrator module comprises sorbent or material having affinity for the VOCs of interest.
- the preconcentrator module is heated to desorb the VOC in order for further analysis.
- the analytes such as high vapor pressure analytes
- the analyte is concentrated on an absorbent.
- the preconcentrator can be used to increase the concentration of analytes in the test sample.
- Preconcentrators are traps composed of an adsorbent material.
- an adsorbent material attracts molecules from the gas sample that are concentrated on the surface of the adsorbent. Subsequently, the sample is "desorbed” and analyzed.
- Suitable preconcentrator materials include, but are not limited to, a polymeric adsorbent material, unsilanized glass wool, Teflon or porus glass fiber, and the like.
- the adsorbent material is packed in a tube, such as a steel tube.
- the present methods provide monitoring of ambient air for an environmental warning.
- an asthma patient can be put on alert regarding the presence of such harmful elements.
- the methods herein can be programmed to lock-on to certain gases by, for example, pattern recognition.
- the ambient air is stored as a background signal that can be subtracted from the subject's breath.
- the present methods provide monitoring of ambient air 200 for an environmental warning alerting the patient from entering an environment.
- the inhaling ambient air 210 contains background VOCs and NO gas.
- the apparatus contains an analyzer 215 having a spirometer (1), and a detector array module comprising a VOC detector (2), a NO detector (3) which outputs an ambient air VOC and NO baseline level 217. If the levels are too high i.e., above a threshold level, a warning such as a red light or sound is made to alert the user of the inhospitable environment.
- the systems and methods warn asthma patients.
- the device can be programmed to lock-on certain gases by pattern recognition algorithms.
- the systems and methods are in fact in certain instances, a personalized environmental detection device for specific allergens for early warning to asthma patients.
- the present systems and methods have a mouth piece and filter (e.g., disposable) 220 for ease of operation.
- the VOCs of ambient air are physically filtered out before entering the lung.
- the lungs of the individual 230 provides the means to take in air and exhale air 240 through the system.
- the exhaled air 240 travels 250 to the analyzer 215.
- the output data 255 can be assessed for exhaled VOCs, and NO concentration as well as flow rate.
- background subtraction 280 can then take place using signal processing and data manipulations using certain algorithms.
- a quantitative assessment of asthma severity 290 can then be given.
- the detector array is removable, replaceable and/or disposable.
- the detector array can be inserted and removed in a "plug-in-play" mode for particular enhancements and functionality.
- the methods disclosed herein include aspects wherein regular monitoring of a subject's status is undertaken which is helpful to the healthcare professional or patient for tracking the subject's progress.
- the breath analysis described herein can provide the root cause of the bronchi constriction by measuring the VOCs from the subject's breath.
- portable gas analysis systems are used to monitor the efficacy of medication and therapy.
- the medication therapy can be tailored to an individual patient (personalized device) through this active monitoring by using a home- based device.
- medical professionals detect both NO and VOCs of asthma patients before and after medication. This can be an effective tool to manage and/or controls the patient's medication treatment.
- a patient's NO level and VOC levels are measured in various time intervals. For example, it is possible to measure a patient's breath and monitor or calculate NO level and VOC concentration levels at Tl (time 1). At T2 (time 2), some time after Tl, a patient's NO level and VOC concentration levels are again measured. The difference between Tl and T2 can be 1 week, 2 weeks, 3 weeks, 1 month, 2 months, 3 months, 4 months, 5 months, 6 months, 7 months, 8 months, 9 months, 10 months, 11 months, 1 year, 2 years, and the like.
- the present invention provides methods and systems for the detection of whether a subject has tuberculosis or monitoring a tuberculosis subject.
- the present methods provide monitoring of ambient air 310 for an environmental warning altering the patient from entering an environment.
- the exhaled breath 320 or headspace gases from a subject's sputum (e.g., mucus, phlegm, saliva, etc., not shown), or a sputum culture 330 contains VOCs 350 which are contacted with the gas analyzer to produce a signal.
- the signal can be used to diagnose whether a patient has TB 380 or whether the TB infection is drug resistant, management of TB, etc.
- the methods include a "lung washout," protocol wherein several deep breaths are taken and not measured.
- the methods and systems disclosed herein are important to ensure patients are given effective treatment in order to prevent drug-resistant TB.
- a relative rapid culture test e.g., 9-15 days
- MGIT systems provides 95-97% accuracy (i.e., the degree of closeness to the accepted value) by measuring the O 2 consumption.
- the test is still very slow compare to the present method.
- the test requires trained technicians, proper bacteriological laboratory facilities and is relatively expensive compared to the simple rapid methodology of the present invention.
- the methods and systems of the present invention monitor VOCs of a patient's breath or headspace gases from the patient's sputum culture before, during and/or after therapeutic treatment or drug treatment on the sputum or sputum's culture to identify the most efficacious medication for TB bacteria for the patient. Also, active monitoring can decide the best timing to stop the medication.
- the subject inhales ambient air 410 containing background VOCs which are passed through the analyzer 415 having a spirometer (1) and a VOC detector array (2).
- the output data 420 has ambient VOCs baseline level measured against a threshold.
- the present systems and methods have a disposable mouth piece and filter 425 for ease of operation.
- the VOCs of ambient air are filtered before entering the lung 430.
- the lungs of the individual 430 provide the means to inhale air and exhale air 435 through the system.
- the exhaled air travels to the analyzer 415.
- the apparatus contains a preconcentrator 440 (e.g., in-line) and/or a flow meter module 444 (e.g., in-line).
- the exhaled breath can be concentrated in order to concentrate VOCs.
- the flow meter module can regulate the flow of exhaled breath.
- the exhaled breath can be assisted or regulated to a desired flow rate.
- the module or flow meter 444 controls the rate of air flow directly by either restricting air flow or increasing air flow as explain previously.
- the output data 455 can be assessed for exhaled VOCs.
- background subtraction 460 (See, FIG. 4B) can then take place using signal processing and data manipulations.
- a quantitative assessment of a TB infection 480 can then be given.
- the subject inhales ambient air 510 containing background VOCs which are passed through the analyzer 515 having a spirometer (1) and a VOC detector (2).
- the output data 520 has ambient VOCs baseline level measured against a threshold.
- the present systems and methods have a mouth piece and filter (e.g., disposable) 525 for ease of operation.
- the VOCs of ambient air are filtered before entering the lung.
- the lungs of the individual 530 provide the means to inhale air and exhale air 535 through the system.
- the exhaled air travels to the analyzer 515.
- the output data 555 can be assessed for exhaled VOCs.
- background subtraction 560 can then take place using signal processing and data manipulations using certain algorithms.
- management of TB medication 580 can be accomplished by monitoring a patient's conditions during drug treatment. By using the systems and methods of the present invention before, during and after different drug treatments, the most efficacious drug for an individual patient can be selected.
- FIG. 6 yet another embodiment 600 of the present invention is illustrated.
- headspace gases of sputum culture, or breath is assessed 610 via the analyzer 620 and the concentration of marker VOCs 621 is determined.
- various drugs can be used 622 in order to assess their efficacy on the particular bacterium in the sputum or sputum culture 633.
- the headspace gases 640 are analyzed via the analyzer 645 and the concentration of the biomarkers assessed 650.
- the systems and methods herein assess the effectiveness of drugs (e.g., drug A, 622) to an individual patient's sputum, or sputum culture.
- the process can be repeated with different drug types (B-Z) to find the most efficacious drug 630.
- This embodiment also contemplates the use of the disclosed systems and methods in clinical trials and drug research.
- FIG. 7 illustrates another embodiment 700 of the present invention.
- sampling of ambient air can be carried out at various places, which are high risk for TB contaminated environments such as TB labs, hospitals, clinics, health care facilities, nursing homes, jails, prisons, and the like 710.
- the analyzer 730 assesses the concentration of various concentration of VOCs 750. If the VOCs are above a threshold value, a warning is communicated 780.
- VOCs useful for TB detection 1 -methyl- naphthalene, 3-heptanone, methylcyclododecane, 2,2,4,6,6-pentamethyl-heptane, 1-methyl- 4-(l-methylethyl)-benzene, 1 ,4-dimethylcyclohexane, 1,3-isobenzofurandione, 2,3-dimethyl- pentane, acetaldehyde, ⁇ , ⁇ , dimethylbenzenemethanol, cyclohexane, 2,2'-diethyl-l,l '- biphenyl, and 2,3-dihydro-l,l,3-trimethyl-3-phenyl-lH-indene.
- Others include, but are not limited to, trans 1,3-dimethyl-cyclohexane, 1,4-dichloro-benzene, 1-octanol, 2-butanone, camphene, 4-methyl- decane, 3-ethyl-2-methyl-heptane, 2,6-dimethyloctane, 1,2,3,4- tetramethylbenzene, trans-3,6,6-trimethyl-bicyclo-3-l-l-hept-2-ene, trans l-ethyl-4-methyl- cyclohexane, and 1- ⁇ -pinene.
- the application can also be applied to bench-top or central-lab instruments, such as GC/MS, or an electronic nose.
- the methods and systems disclosed herein allow for very high sensitivity and specificity for TB tests based on the patients' exhaled VOCs and headspace gases of cultured microbacteria.
- FIG. 8 illustrates yet another embodiment 800 of the present invention.
- the present invention provides devices and methods to sample a sputum culture such as the headspace 810 wherein an analyzer 830 assesses the concentration of various marker VOCs 850, or monitors the changes of VOCs concentrations over time (e.g., slope of concentration).
- the devices and methods allow for the assessment of a TB 870 infection by either VOCs passing a threshold, or for example, the slope exceeding a certain value.
- Various therapeutic compounds can be tested for being the most efficacious for the patient. In this manner, the medication therapy can be tailored to an individual patient (personalized device) through the testing of various antibiotics. This embodiments allows for the replacement of current TB diagnostic methods and is faster and more accurate.
- the present invention provides methods and systems for the detection of whether a subject has lung cancer or monitoring a subject having lung cancer.
- the VOCs for lung cancer include, but are not limited to, 2-heptanone, 4- methyl-nonane, heptanal, 2-methyl-nonane, l,l '-bicyclopentyl, nonane, 4-methyl-octane, hexanal, propyl-cyclohexane, trideuteroacetonitrile, 5-methyl-2-hexanamine, 1-butyl- 2methyl, cis-cyclopropane, 1,1,3-trimethyl-cyclohexane, 2-chloro-l-(difluoromethoxy)- 1,1,2- trifluoro-ethane, 3-ethyl-2-methy-heptane, 1,3-dimethyl-, trans-cyclohexane, 3-(methylthio)- 1-propene,
- non-small cell lung cancer accounts for about 80% of lung cancers, these include, squamous cell carcinoma, adenocarcinoma, and bronchioalveolar carcinoma.
- SCLC Small cell lung cancer
- the detector array comprises a sensor or a plurality of sensors.
- the sensors are surface micromachined sensors (MEMS).
- the sensors can be bulk micromachined sensors, meaning that at least some of the MEMS sensors are formed within a substrate instead of on the surface.
- MEMS sensors can include combinations of surface-micromachined and bulk-micromachined sensors. Different types of sensors (not limited to MEMS types) can be used, depending on the application and the required sensitivity. Examples of MEMS sensors that can be used include chemiresistors, bulk acoustic wave (BAW) sensors, and the like.
- BAW bulk acoustic wave
- the detector array comprises one or more of the sensors which can be a non-MEMS sensor.
- non-MEMS sensors that can be used in detector array include SAW (surface acoustic wave) sensors with quartz or gallium arsenide substrates or a QCM (quartz crystal microbalance).
- each sensor includes a surface with a coating thereon.
- Each coating used will have an affinity for one or more of the particular chemicals being detected e.g., (NO, VOCs), such that the coating absorbs or chemically interacts with its corresponding chemical or chemicals.
- the interaction between coating and chemical changes a physical property of the sensor such as resonant frequency, capacitance or electrical resistance, and that changed physical property of the sensor can be measured using a transducer or other measurement device.
- a particular coating chosen for a sensor will depend on the chemicals that sensor array will be used to detect.
- the chemical affinity of coatings may also vary strongly with temperature, so that the operating temperature range should be considered in selecting coatings.
- the sensor array will be used to detect volatile organic compounds in human breath - such as benzene, toluene, n-octane, ethylbenzene, m- or p-xylene, ⁇ -pinene, d-limonene, nonanal, benzaldehyde, 2-methylhexane, and 4-methyloctane.
- Coatings that can be used in different applications include amorphous copolymers of 2,2-bistrifluoromethyl-4,5-difluoro-l,3- dioxole (PDD) and tetrafluoroethylene (TFE), PtC 12 (olefin), C8-MPN, and the like.
- the number of sensors needed depends on the number of different chemicals to be detected, and on the nature of the coatings used on the sensors.
- the number of sensors can correspond exactly to the number of chemicals to be detected, but in other embodiments, it can be desirable to have a given coating on more than one sensor for redundancy.
- each coating reacts with more than one different chemical and the reaction between different chemicals and a given coating will vary in nature and strength.
- the detector array having sensors with different coatings is therefore useful because the response of the detector array can have different patterns for different gases.
- the signal analysis is via a neural network algorithm or learning algorithm.
- Pattern recognition using neural networks is well-established in the art.
- the neural network is trained with a training set and thereafter validated with a validation set.
- Neural networks are interconnected groups of artificial neurons that use a mathematical or computational model for information processing based on a connectionist approach to computation.
- neural networks are adaptive systems that change their structure based on external or internal information that flows through the network.
- Specific examples of neural networks include feed- forward neural networks such as perceptrons, single-layer perceptrons, multi-layer perceptrons, backpropagation networks, ADALINE networks, MADALINE networks, Learnmatrix networks, radial basis function (RBF) networks, and self-organizing maps or Kohonen self-organizing networks; recurrent neural networks such as simple recurrent networks and Hopfield networks; stochastic neural networks such as Boltzmann machines; modular neural networks such as committee of machines and associative neural networks; and other types of networks such as instantaneously trained neural networks, spiking neural networks, dynamic neural networks, and cascading neural networks.
- feed- forward neural networks such as perceptrons, single-layer perceptrons, multi-layer perceptrons, backpropagation networks, ADALINE networks
- Neural network analysis can be performed, e.g., using the Statistica data analysis software available from StatSoft, Inc. See, e.g., Freeman et al., In “Neural Networks: Algorithms, Applications and Programming Techniques," Addison- Wesley Publishing Company (1991); Zadeh, Information and Control, 8:338-353 (1965); Zadeh, “IEEE Trans, on Systems, Man and Cybernetics," 3:28-44 (1973); Gersho et al., In “Vector Quantization and Signal Compression,” Kluywer Academic Publishers, Boston, Dordrecht, London (1992); and Hassoun, “Fundamentals of Artificial Neural Networks,” MIT Press, Cambridge, Massachusetts, London (1995), for further descriptions of neural networks.
- Statistica data analysis software available from StatSoft, Inc. See, e.g., Freeman et al., In “Neural Networks: Algorithms, Applications and Programming Techniques," Addison- Wesley Publishing Company
- Ambient air is monitored for VOC stimulus warning and saved as baseline level. Both the inhaled and exhaled breathes are measured for flow rate and volume. The exhaled breath is collected and filtered by background data for NO and VOCs detection for asthma assessment.
- a clinical trial is conducted to differentiate grades of asthma severity as assessed according to the 2007 National Asthma Education and Prevention Program (NAEPP) guidelines. These guidelines are described in the National Heart, Lung, and Blood Institute NAEPP Expert Panel Report 3: Guidelines for the Diagnosis and Management of Asthma, Full Report 2007. Using the guidelines in Expert Panel Report 3 (see, FIG. 9) impairment and risk of 600 patients are assessed and classified into 1) Intermittent; 2) Mild; 3) Moderate; or 4) Severe. The Expert Panel Report 3 indicates that 153 individuals have Intermediate asthma; 101 individuals have Mild asthma; 256 are Moderate asthma and 90 are Severe asthma.
- NAEPP National Asthma Education and Prevention Program
- breath samples from the 600 asthma patients are obtained.
- Levels of nitric oxide and volatile organic components (VOC), including the compounds A- methyloctane, 2,4-dimethylheptane, isopropanol, toluene, isoprene, alkane, acetic, acetone, 2,6,11-trimethyl dodecane, 3,7-dimethyl undecane, and 2,3-dimethyl heptanes as examples, are measured.
- the baseline level of the markers in the ambient air is determined, and the breath sample levels are adjusted by the baseline level of the markers in the ambient air.
- VOCs and NO levels are determined.
- a cohort of these samples (300) is used as a training data set of the sensor array, which serves as a basis, model, or template against which the features of an unknown sample are compared, in order to classify the unknown disease state of the sample.
- the sensor array is then validated with a cohort (300) of samples that had not been used in the training set. This is know as the validation set. The data obtained from this test is used to calculate all accuracy parameters for the sensor array.
- FEVi forced expiratory volume in 1 second
- the spirometry data is added to the training set and validation set using data analysis software.
- the sensitivity, specificity, and accuracy of the sensor array is calculated.
- the methods herein increase specificity and the dynamic range of monitoring severity of asthma by detecting all VOCs, NO, and flow rate or any one of the foregoing.
- the systems and methods herein monitor VOCs for patients with mild or no asthma, whereas for mild or sever asthma, NO levels are quantitated.
- Example 2 Breath samples from 150 asthma patients and 50 non-asthmatic healthy controls are obtained. As described in Example 1 , marker levels are measured, and spirometry is performed. Using the trained and validated sensor array, 150 asthma patients can be classified by degree of severity.
- the asthma severity level is predicted for each of 200 patients.
- the asthma severity level of each of the 150 patients is thereafter classified by the 2007 NAEPP guidelines, and the results are compared.
- the sensitivity, specificity, and accuracy of the algorithm is compared to the results of Example 1.
- a sensor array is developed to identify tuberculosis infection by measurement of VOC levels in a patient's breath, sputum and sputum culture.
- VOC volatile organic components
- a cohort of these samples (200) is used as a training data set of the sensor array, which serves as a basis, model, or template against which the features of an unknown sample are compared, in order to classify the unknown disease state of the sample.
- the sensor array is then validated with a cohort (200) of samples that had not been used in the training set. The data obtained from this test is used to calculate all accuracy parameters for the sensor array. The sensitivity, specificity, and accuracy of the sensor array is calculated.
- Example 3 Breath samples from 100 patients with active tuberculosis, 100 patients with latent tuberculosis, and 50 healthy controls are obtained. The presence and severity of tuberculosis in each patient is identified by conventional screening techniques. As described in Example 3, marker levels are measured. [0093] Using the algorithm defined in Example 3, the tuberculosis classification is calculated for each patient, and the results are compared with the tuberculosis classification of each patient as identified by standard screening techniques. The sensitivity, specificity, and accuracy of the sensor array is compared to the results of Example 3.
- Example 5 Breath samples from 87 patients with active tuberculosis are obtained. The presence and severity of tuberculosis in each patient is verified using the IS 6110 repetitive DNA element of mycobacterium tuberculosis. Before treatment, the breath VOCs are collected from each patient. Various drugs are used to treat TB including isoniazid, rifampin (brand name: Rifadin), ethambutol (brand name: Myambutol) and pyrazinamide. The patients take their medicine as directed. During treatment, breath samples show the patients will be better and feel healthier. VOCs from breath samples verify that patients are better. After treatment, the VOCs verify that TB infection is no longer present.
- rifampin brand name: Rifadin
- ethambutol brand name: Myambutol
- pyrazinamide pyrazinamide
- a sputum is cultured for each of the 87 patients. Headspace gases of each sputum culture is assessed via the analyzer and the concentration of marker VOCs is determined.
- the same drugs are used in order to assess their efficacy on the particular bacterium in the sputum culture. The methods assess the effectiveness of the drugs to find the most efficacious drug.
- Example 6 This example represents a clinical trial with 87 patients. Breath samples from 87 patients are obtained in a Phase I study. VOC markers of TB Mycobacteria are validated. The protocol includes collecting headspace of (1) TB cultures, (2) NTM cultures, (3) microbial flora in oral cavity and respiratory track, and (4) control tubes. It is then possible to identify specific VOC markers of TB culture headspace and is optimized. [0097] In Phase II, the VOC markers from patient's breath are verified and the clinical trial protocol is established. The protocol includes collecting clinical samples - both sputum & breath - from patient and control; repeating phase-I in- vitro tests on sputum sample as reference; identifying specific VOC markers of TB patient breath.
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| CN2009801558120A CN102300502A (zh) | 2008-12-01 | 2009-11-30 | 用于哮喘、肺结核及肺癌诊断及疾病管控的呼吸分析系统及方法 |
| JP2011538714A JP5848608B2 (ja) | 2008-12-01 | 2009-11-30 | 喘息、結核及び肺癌の診断及び疾患管理のための呼気分析システム及び方法 |
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| EP (1) | EP2369989A4 (enExample) |
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| JP2017511718A (ja) * | 2014-02-19 | 2017-04-27 | コーニンクレッカ フィリップス エヌ ヴェKoninklijke Philips N.V. | Ardsを検出する方法及びardsを検出するためのシステム |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| FR2858236B1 (fr) | 2003-07-29 | 2006-04-28 | Airox | Dispositif et procede de fourniture de gaz respiratoire en pression ou en volume |
| US8302602B2 (en) | 2008-09-30 | 2012-11-06 | Nellcor Puritan Bennett Llc | Breathing assistance system with multiple pressure sensors |
| EP2369989A4 (en) * | 2008-12-01 | 2013-05-15 | Tricorntech Corp | ATTA ANALYSIS SYSTEM AND ASSAYS FOR THE DIAGNOSIS AND TREATMENT OF ASTHMA, TUBERCULOSIS AND LUNG CANCER |
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| TWI458464B (zh) * | 2012-02-01 | 2014-11-01 | Nat Univ Tsing Hua | 可早期偵測及辨識肺炎種類之呼吸器、其氣體辨識晶片、及其氣體辨識方法 |
| US9770192B2 (en) * | 2012-03-19 | 2017-09-26 | Richard C. Fuisz | Method and system to amplify and measure breath analytes |
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| US9164080B2 (en) | 2012-06-11 | 2015-10-20 | Ohio State Innovation Foundation | System and method for sensing NO |
| JP5723421B2 (ja) * | 2012-07-20 | 2015-05-27 | 福永生物科技股▲ふん▼有限公司EPS Bio Technology Corp. | 電子鼻装置 |
| JP2014023603A (ja) * | 2012-07-25 | 2014-02-06 | Nippon Koden Corp | 睡眠時無呼吸判定装置 |
| WO2014068554A1 (en) * | 2012-10-29 | 2014-05-08 | Technion Research And Development Foundation Ltd. | Sensor technology for diagnosing tuberculosis |
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| US9950135B2 (en) | 2013-03-15 | 2018-04-24 | Covidien Lp | Maintaining an exhalation valve sensor assembly |
| JP6182796B2 (ja) * | 2013-06-28 | 2017-08-23 | 国立研究開発法人産業技術総合研究所 | 呼気分析システム、肺がんマーカー及び呼気分析方法 |
| HK1214651A1 (zh) * | 2013-08-28 | 2016-07-29 | 路易斯威尔大学研究基金会有限公司 | 利用呼出氣體的肺癌的非侵入性檢測 |
| KR101489093B1 (ko) * | 2013-11-06 | 2015-02-06 | 경희대학교 산학협력단 | 호흡 훈련 장치 및 방법 |
| US10307080B2 (en) | 2014-03-07 | 2019-06-04 | Spirosure, Inc. | Respiratory monitor |
| JP6256986B2 (ja) * | 2014-03-28 | 2018-01-10 | 学校法人順天堂 | 食道癌の判定方法 |
| US9366664B2 (en) | 2014-05-21 | 2016-06-14 | Andas Inc. | Device for measurement of exhaled nitric oxide concentration |
| US9011779B1 (en) | 2014-05-21 | 2015-04-21 | Andas Inc. | Device for measurement of exhaled ethanol concentration |
| DE102014210574A1 (de) * | 2014-06-04 | 2015-12-17 | Robert Bosch Gmbh | Messvorrichtung und Verfahren zur Bestimmung der asthmatisch wirksamen Belastung bei einem Menschen oder Tier |
| US20170160265A1 (en) * | 2014-07-21 | 2017-06-08 | Technion Research & Development Foundation Ltd. | Compositions for direct breath sampling |
| US11262354B2 (en) | 2014-10-20 | 2022-03-01 | Boston Scientific Scimed, Inc. | Disposable sensor elements, systems, and related methods |
| GB201502447D0 (en) * | 2015-02-13 | 2015-04-01 | Univ Liverpool | Method and apparatus for sample analysis |
| CN106137204A (zh) * | 2015-04-02 | 2016-11-23 | 中国科学院生态环境研究中心 | 利用真空紫外光电离质谱仪进行肺癌早期筛查的方法 |
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| CN104970775A (zh) * | 2015-07-01 | 2015-10-14 | 深圳市前海安测信息技术有限公司 | 肺结核病早期症状监测方法及监测系统 |
| US20170059554A1 (en) * | 2015-09-02 | 2017-03-02 | R. J. Reynolds Tobacco Company | Method for monitoring use of a tobacco product |
| EP3143930A1 (en) * | 2015-09-21 | 2017-03-22 | Université de Liège | Method for the diagnosis of airway disease inflammatory subtype |
| US20170191910A1 (en) * | 2015-12-31 | 2017-07-06 | The Cleveland Clinic Foundation | Method, computing device and system for collecting exhaled breath |
| CN108701496A (zh) | 2016-03-01 | 2018-10-23 | 皇家飞利浦有限公司 | 用于确定呼吸发作的风险水平的系统和方法 |
| WO2017192782A1 (en) * | 2016-05-03 | 2017-11-09 | Pneuma Respiratory, Inc. | Systems and methods comprising a droplet delivery device and a breathing assist device for therapeutic treatment |
| US11191457B2 (en) | 2016-06-15 | 2021-12-07 | Boston Scientific Scimed, Inc. | Gas sampling catheters, systems and methods |
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| WO2018075731A1 (en) | 2016-10-21 | 2018-04-26 | Boston Scientific Scimed, Inc. | Gas sampling device |
| CN106422744B (zh) * | 2016-11-09 | 2023-03-14 | 暨南大学 | 一次性手术烟雾净化器 |
| JP2020510831A (ja) | 2017-03-01 | 2020-04-09 | 日本特殊陶業株式会社 | 還元ガスを用いた一酸化窒素検出装置 |
| JP6879545B2 (ja) * | 2017-03-15 | 2021-06-02 | 株式会社タニタ | 生体ガス検知装置、方法、及びプログラム |
| EP3602044A4 (en) | 2017-03-23 | 2021-05-05 | Technion Research & Development Foundation Limited | Device and methods for detection and monitoring of tuberculosis |
| EP3624678B1 (en) | 2017-05-19 | 2022-08-17 | Boston Scientific Scimed Inc. | Systems and methods for assessing the health status of a patient |
| US10852264B2 (en) | 2017-07-18 | 2020-12-01 | Boston Scientific Scimed, Inc. | Systems and methods for analyte sensing in physiological gas samples |
| CN111801048A (zh) * | 2018-02-20 | 2020-10-20 | 明尼苏达大学董事会 | 呼吸取样面罩和系统 |
| DE102018114970A1 (de) * | 2018-06-21 | 2019-12-24 | breazy-health GmbH | System und Verfahren zur Bereitstellung von zumindest einer Information über zumindest eine Wechselwirkung zwischen Umgebungsluft und Atemfunktion von einem Individuum |
| US20210186367A1 (en) * | 2018-09-03 | 2021-06-24 | Kozhnosys Private Limited | System for detection of volatile organic compounds (voc) in exhaled breath for health monitoring |
| US20210405023A1 (en) * | 2018-10-06 | 2021-12-30 | The Cleveland Clinic Foundation | Method for diagnosing clostridioides difficile infection |
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| WO2020112027A1 (en) * | 2018-11-28 | 2020-06-04 | National University Of Singapore | Method of detecting cancer and/or tuberculosis |
| EP3861329A1 (en) | 2018-11-27 | 2021-08-11 | Boston Scientific Scimed Inc. | Systems and methods for detecting a health condition |
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| EP4013302A1 (en) | 2019-08-13 | 2022-06-22 | Respiration Scan Ltd | System and method for determining onset and disease progression |
| CN114449957B (zh) * | 2019-08-26 | 2023-11-24 | 泽特奥科技公司 | 利用呼出气诊断结核病和其他疾病 |
| CN114651178A (zh) | 2019-09-10 | 2022-06-21 | 波士顿科学国际有限公司 | 气体测量装置和方法 |
| CN110755056A (zh) * | 2019-11-21 | 2020-02-07 | 中国中医科学院 | 医生四诊过程记录仪 |
| US11054347B1 (en) * | 2019-12-31 | 2021-07-06 | X Development Llc | Enhanced gas sensor selectivity |
| US11896767B2 (en) | 2020-03-20 | 2024-02-13 | Covidien Lp | Model-driven system integration in medical ventilators |
| US12364411B2 (en) | 2020-04-03 | 2025-07-22 | Zeteo Tech, Inc. | Diagnosis of respiratory diseases using analysis of exhaled breath and aerosols |
| JP7504499B2 (ja) | 2020-04-03 | 2024-06-24 | ゼテオ テック、 インク. | 呼気およびエアロゾルの分析を用いた呼吸器疾患の診断 |
| JP7755314B2 (ja) * | 2020-06-17 | 2025-10-16 | 株式会社レボーン | システム、情報処理装置及びプログラム |
| WO2022004590A1 (ja) * | 2020-06-29 | 2022-01-06 | パナソニックIpマネジメント株式会社 | ガスセンサ |
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5111827A (en) * | 1988-02-11 | 1992-05-12 | Instrumentarium Corp. | Respiratory sampling device |
| US20050085740A1 (en) * | 2003-04-01 | 2005-04-21 | Davis Cristina E. | Non-invasive breath analysis using field asymmetric ion mobility spectrometry |
| US20060222568A1 (en) * | 2005-03-31 | 2006-10-05 | Li-Peng Wang | Miniature chemical analysis system |
Family Cites Families (54)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4888295A (en) | 1984-03-02 | 1989-12-19 | The United States Of America As Represented By The United States Department Of Energy | Portable system and method combining chromatography and array of electrochemical sensors |
| US4869876A (en) * | 1984-04-30 | 1989-09-26 | International Business Machines Corp. | Multi-purpose plural-oven gas chromatography system with shared controls |
| JPS6378943A (ja) | 1986-09-19 | 1988-04-09 | 鹿島建設株式会社 | スラブの構築方法 |
| US4796639A (en) * | 1987-11-05 | 1989-01-10 | Medical Graphics Corporation | Pulmonary diagnostic system |
| JPH06764Y2 (ja) * | 1987-11-17 | 1994-01-05 | フィガロ技研株式会社 | ガス検出装置 |
| US4850371A (en) * | 1988-06-13 | 1989-07-25 | Broadhurst John H | Novel endotracheal tube and mass spectrometer |
| US5081871A (en) * | 1989-02-02 | 1992-01-21 | The United States Of America As Represented By The Secretary Of The Department Of Health And Human Services | Breath sampler |
| JPH0647047A (ja) | 1992-06-03 | 1994-02-22 | Hideo Ueda | 臨床用呼気検査方法及び装置 |
| CA2097363A1 (en) | 1992-06-03 | 1993-12-04 | Hideo Ueda | Expired air examination device and method for clinical purpose |
| JP3838671B2 (ja) * | 1993-10-25 | 2006-10-25 | アークレイ株式会社 | 呼気採取装置 |
| JPH07184488A (ja) | 1993-12-24 | 1995-07-25 | Kyowa Kk | 養液栽培システム |
| US5465728A (en) | 1994-01-11 | 1995-11-14 | Phillips; Michael | Breath collection |
| DE892926T1 (de) * | 1996-04-09 | 1999-12-09 | Sievers Instruments, Inc. | Verfahren und vorrichtung zur messung von bestandteilen in von menschen ausgeatmeter luft |
| US5996586A (en) | 1997-03-26 | 1999-12-07 | Phillips; Michael | Breath test for detection of lung cancer |
| SE9801532D0 (sv) | 1998-04-30 | 1998-04-30 | Aerocrine Ab | Device for the collection of exhaled air samples |
| WO1999065386A1 (en) | 1998-06-15 | 1999-12-23 | The Trustees Of The University Of Pennsylvania | Diagnosing intrapulmonary infection and analyzing nasal sample |
| EP1099102B1 (en) | 1998-06-19 | 2008-05-07 | California Institute Of Technology | Trace level detection of analytes using artificial olfactometry |
| EP1117991A4 (en) | 1998-10-02 | 2005-04-27 | California Inst Of Techn | CONDUCTIVE ORGANIC SENSORS, MOSAIC SENSORS AND METHODS OF USE |
| GB9825904D0 (en) | 1998-11-27 | 1999-01-20 | Univ Cranfield | Diagnosis of gastric and lung disorders |
| US6468222B1 (en) * | 1999-08-02 | 2002-10-22 | Healthetech, Inc. | Metabolic calorimeter employing respiratory gas analysis |
| AU2001275290A1 (en) * | 2000-06-07 | 2001-12-17 | Healthetech, Inc. | Breath ketone analyzer |
| US6981947B2 (en) * | 2002-01-22 | 2006-01-03 | University Of Florida Research Foundation, Inc. | Method and apparatus for monitoring respiratory gases during anesthesia |
| US7076371B2 (en) | 2001-03-03 | 2006-07-11 | Chi Yung Fu | Non-invasive diagnostic and monitoring method and apparatus based on odor detection |
| US20100248268A1 (en) * | 2001-03-27 | 2010-09-30 | Woods Daniel F | Methods to utilize invertebrate chemosensory proteins for industrial and commercial uses |
| AU2002309803A1 (en) * | 2001-04-17 | 2002-10-28 | University Of Virginia Patent Foundation | Breath test for assessing diseases, particularly asthma |
| DE10121262A1 (de) | 2001-04-30 | 2002-11-14 | Siemens Ag | Vorrichtung zur quantitativen Messung von Stickoxiden in der Ausatemluft und Verwendung |
| US20030023181A1 (en) * | 2001-07-26 | 2003-01-30 | Mault James R. | Gas analyzer of the fluorescent-film type particularly useful for respiratory analysis |
| US6726637B2 (en) | 2001-12-06 | 2004-04-27 | Michael Phillips | Breath collection apparatus |
| US7473229B2 (en) * | 2001-12-10 | 2009-01-06 | Pranalytica, Inc. | Method of analyzing components of alveolar breath |
| AU2003207552A1 (en) | 2002-01-29 | 2003-09-02 | James D. Talton | Methods of collecting and analyzing human breath |
| WO2003075745A2 (en) | 2002-03-04 | 2003-09-18 | Cyrano Sciences, Inc. | Detection, diagnosis, and monitoring of a medical condition or disease with artificial olfactometry |
| US7101340B1 (en) * | 2002-04-12 | 2006-09-05 | Braun Charles L | Spectroscopic breath profile analysis device and uses thereof for facilitating diagnosis of medical conditions |
| ES2311264T3 (es) * | 2002-09-16 | 2009-02-01 | Aerocrine Ab | Aparato y metodo para analisis de gas para diagnostico. |
| US20050150778A1 (en) | 2002-11-18 | 2005-07-14 | Lewis Nathan S. | Use of basic polymers in carbon black composite vapor detectors to obtain enhanced sensitivity and classification performance for volatile fatty acids |
| US7172557B1 (en) * | 2003-08-29 | 2007-02-06 | Caldyne, Inc. | Spirometer, display and method |
| EP1751537B1 (en) | 2004-05-17 | 2019-07-10 | Firmenich SA | Multidimensional gas chromatography apparatus and analyte transfer procedure using a multiple-cool strand interface |
| WO2006046588A1 (ja) * | 2004-10-28 | 2006-05-04 | Seems Inc. | 疾病診断システム |
| US7421882B2 (en) * | 2004-12-17 | 2008-09-09 | University Of Iowa Research Foundation | Breath-based sensors for non-invasive molecular detection |
| EP1850749A2 (en) | 2005-01-10 | 2007-11-07 | Pulmatrix, Inc. | Method and device for decreasing contamination |
| JP5075638B2 (ja) * | 2005-01-10 | 2012-11-21 | プルマトリックス,インコーポレイティッド | 汚染を減少させるための方法及び装置 |
| US7343779B1 (en) * | 2005-12-05 | 2008-03-18 | Yu Conrad M | High performance, hand-held gas chromatograph, method and system |
| US8117896B2 (en) * | 2006-08-09 | 2012-02-21 | Seacoast Science, Inc. | Preconcentrators and methods of making and using the same |
| WO2008126519A1 (ja) * | 2007-03-22 | 2008-10-23 | Shinshu University | センサー |
| US20080275355A1 (en) * | 2007-05-04 | 2008-11-06 | Ekips Technologies, Inc. | Method For Diagnosing An Infectioin Condition |
| EP2176670A4 (en) * | 2007-08-08 | 2017-07-12 | Invoy Technologies, LLC | Biosensor system with a multifunctional portable electronic device |
| US9521963B2 (en) * | 2008-05-13 | 2016-12-20 | Ric Investments, Llc | Respiratory component measurement system with indicating elements |
| US8087283B2 (en) * | 2008-06-17 | 2012-01-03 | Tricorntech Corporation | Handheld gas analysis systems for point-of-care medical applications |
| JP5289837B2 (ja) * | 2008-06-30 | 2013-09-11 | 日本光電工業株式会社 | 生体由来ガス成分分析装置及び疾病判定支援装置 |
| US8652064B2 (en) * | 2008-09-30 | 2014-02-18 | Covidien Lp | Sampling circuit for measuring analytes |
| EP2369989A4 (en) * | 2008-12-01 | 2013-05-15 | Tricorntech Corp | ATTA ANALYSIS SYSTEM AND ASSAYS FOR THE DIAGNOSIS AND TREATMENT OF ASTHMA, TUBERCULOSIS AND LUNG CANCER |
| US8716655B2 (en) * | 2009-07-02 | 2014-05-06 | Tricorntech Corporation | Integrated ion separation spectrometer |
| US8999245B2 (en) * | 2009-07-07 | 2015-04-07 | Tricorn Tech Corporation | Cascaded gas chromatographs (CGCs) with individual temperature control and gas analysis systems using same |
| US8707760B2 (en) * | 2009-07-31 | 2014-04-29 | Tricorntech Corporation | Gas collection and analysis system with front-end and back-end pre-concentrators and moisture removal |
| US8978444B2 (en) * | 2010-04-23 | 2015-03-17 | Tricorn Tech Corporation | Gas analyte spectrum sharpening and separation with multi-dimensional micro-GC for gas chromatography analysis |
-
2009
- 2009-11-30 EP EP09830923.0A patent/EP2369989A4/en not_active Ceased
- 2009-11-30 CN CN201510181153.5A patent/CN104856679B/zh active Active
- 2009-11-30 WO PCT/US2009/066103 patent/WO2010065452A1/en not_active Ceased
- 2009-11-30 CN CN2009801558120A patent/CN102300502A/zh active Pending
- 2009-11-30 JP JP2011538714A patent/JP5848608B2/ja active Active
- 2009-11-30 US US12/628,126 patent/US10568541B2/en active Active
-
2020
- 2020-02-14 US US16/792,106 patent/US11690528B2/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5111827A (en) * | 1988-02-11 | 1992-05-12 | Instrumentarium Corp. | Respiratory sampling device |
| US20050085740A1 (en) * | 2003-04-01 | 2005-04-21 | Davis Cristina E. | Non-invasive breath analysis using field asymmetric ion mobility spectrometry |
| US20060222568A1 (en) * | 2005-03-31 | 2006-10-05 | Li-Peng Wang | Miniature chemical analysis system |
Non-Patent Citations (1)
| Title |
|---|
| See also references of EP2369989A4 * |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012059763A1 (en) * | 2010-11-05 | 2012-05-10 | The University Of Manchester | Biomarkers |
| US9955898B2 (en) | 2012-12-26 | 2018-05-01 | Jeong-Chan Ra | Cancer diagnosis method using respiratory gas |
| JP2017511718A (ja) * | 2014-02-19 | 2017-04-27 | コーニンクレッカ フィリップス エヌ ヴェKoninklijke Philips N.V. | Ardsを検出する方法及びardsを検出するためのシステム |
| US10321851B2 (en) | 2014-02-19 | 2019-06-18 | Koninklijke Philips N.V. | Method of detecting ARDS and systems for detecting ARDS |
| US12491324B2 (en) | 2016-05-03 | 2025-12-09 | Pneuma Respiratory, Inc. | Droplet device with inertial filtering |
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| WO2021064400A1 (en) * | 2019-10-01 | 2021-04-08 | Owlstone Medical Limited | Dodecane as exhaled biomarker for exercise-induced asthma in children |
| WO2021159195A1 (pt) * | 2020-02-11 | 2021-08-19 | Moraes Do Nascimento Nathalia | Método para identificação e monitoramento de doenças a partir de amostras de gases captadas por um dispositivo e método de treinamento de uma rede neural para identificação de doenças a partir de amostras de gases captadas por um dispositivo |
| US11793945B2 (en) | 2021-06-22 | 2023-10-24 | Pneuma Respiratory, Inc. | Droplet delivery device with push ejection |
| US12403269B2 (en) | 2021-06-22 | 2025-09-02 | Pneuma Respiratory, Inc. | Droplet delivery device with push ejection |
| US12161795B2 (en) | 2022-07-18 | 2024-12-10 | Pneuma Respiratory, Inc. | Small step size and high resolution aerosol generation system and method |
| WO2024168414A1 (pt) | 2023-02-16 | 2024-08-22 | Gustavo Senna Chelles | Coletor de amostras de ar expirado para pré-diagnóstico de patologias e seu método de uso |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102300502A (zh) | 2011-12-28 |
| US20100137733A1 (en) | 2010-06-03 |
| EP2369989A4 (en) | 2013-05-15 |
| CN104856679B (zh) | 2019-02-22 |
| US20200178842A1 (en) | 2020-06-11 |
| JP5848608B2 (ja) | 2016-01-27 |
| US11690528B2 (en) | 2023-07-04 |
| US10568541B2 (en) | 2020-02-25 |
| EP2369989A1 (en) | 2011-10-05 |
| JP2012510319A (ja) | 2012-05-10 |
| CN104856679A (zh) | 2015-08-26 |
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