WO2023242387A1

WO2023242387A1 - Automated fluorescence-based quantification of pocked red cells

Info

Publication number: WO2023242387A1
Application number: PCT/EP2023/066205
Authority: WO
Inventors: Pierre Buffet; Abdoulaye SISSOKO; Aurélie FRICOT; Sandra MANCEAU; Laure JOSEPH; Michaël DUSSIOT; Narjis YEKKACHE; Lucie DUMAS; Camille ROUSSEL
Original assignee: Institut National de la Santé et de la Recherche Médicale; Assistance Publique-Hôpitaux De Paris (Aphp); Université Paris Cité; Université Des Antilles Et De La Guyane; Fondation Imagine
Priority date: 2022-06-17
Filing date: 2023-06-16
Publication date: 2023-12-21

Abstract

Counting vacuole-containing RBC (pocked-RBC) is a robust marker of defective spleen function but requires the expertise of fewer and fewer specialized laboratory technicians. The inventors developed an automated method using cell trace yellow, a common fluorescent cytoplasmic marker, and imaging flow cytometry (IFC) to quantify pocked-RBC in 123 adults with Sickle Cell Disease (SCD). The proportion of RBC containing one or more fluorescent dots by IFC correlated with results of the conventional method, i.e., the operator-dependent quantification of pocked-RBC by differential interference contrast microscopy. Proportions of pocked-RBC in the circulation correlated with spleen size, which varied widely from splenomegaly to atrophic spleen. Histology of post-splenectomy samples from 3 SCD children with normal, moderately, or markedly elevated pocked RBC, showed either an almost normal aspect with congestion, intense sickling, or widespread fibrosis, respectively. Electronic microscopy of the spleen from the child with normal pocked RBC count showed persistent RBC filtration through inter-endothelial slits. Intrasplenic blood was enriched in RBC displaying a peripheral fluorescent dot, highly suggestive of ongoing intrasplenic expulsion of vacuoles (pitting). Automated, operator-independent and fluorescence-based quantification of pocked RBC correlates with the reference method and confirms that spleen function is partially preserved in many adults with SCD. Accordingly, the present invention relates to the automated fluorescence-based quantification of pocked red cells and use thereof of assessing spleen function.

Description

AUTOMATED FLUORESCENCE-BASED QUANTIFICATION OF POCKED RED CELLS

FIELD OF THE INVENTION:

The present invention is in the field of medicine, in particular haematology.

BACKGROUND OF THE INVENTION:

The spleen protects against blood-borne infections, contributes to the maturation of reticulocytes¹, and filters red blood cells (RBC)^2,3. Defective spleen function (hyposplenism) is caused by splenectomy or by immunological or hematological diseases^4-6. It occurs very soon in Sickle Cell Disease (SCD)⁷, without clear correlation with spleen size⁸. Spleen function is assessed by scintigraphy, and by quantifying circulating blood cells such as marginal zone B lymphocytes, RBC containing Howell-Jolly Bodies (HJB), or vacuoles-containing RBC (pocked-RBC). These RBC subpopulations are cleared of their inclusions as they pass through the spleen in a process called pitting^9-11. Scintigraphy uses radiolabeled items^12,13 and is semi- quantitative¹⁴. Numbers of circulating IgM memory B cells are low in hyposplenism, but no threshold robustly discriminates hyposplenic from healthy subjects¹⁵. Despite recent improvements^16,17, counting HJB lacks specificity and sensitivity, likely because of their relative small number in circulation (<2%) in most asplenic subjects⁸. Circulating pocked-RBC, visualized using differential interference contrast (DIC) microscopy, are >4.5% in hyposplenic patients¹⁸, above 10% in Jamaican children with SCD¹⁹, and from 20-50% in splenectomized subjects^9,10. Pocked-RBC counts correlate with spleen intensity on scintigraphy²⁰ and display a wide window of quantification, but this method requires an expert microscopist, is timeconsuming and poorly reproducible from site to site.

SUMMARY OF THE INVENTION:

The present invention is defined by the claims. In particular, the present invention relates to the automated fluorescence-based quantification of pocked red cells and use thereof of assessing spleen function. DETAILED DESCRIPTION OF THE INVENTION:

Counting vacuole-containing RBC (pocked-RBC) is a robust marker of defective spleen function but requires the expertise of fewer and fewer specialized laboratory technicians. The inventors developed an automated method using cell trace yellow, a common fluorescent cytoplasmic marker, and imaging flow cytometry (IFC) to quantify pocked-RBC in 123 adults with Sickle Cell Disease (SCD). The proportion of RBC containing one or more fluorescent dots by IFC correlated with results of the conventional method, i.e., the operator-dependent quantification of pocked-RBC by differential interference contrast microscopy. Proportions of pocked-RBC in the circulation correlated with spleen size, which varied widely from splenomegaly to atrophic spleen. Histology of post-splenectomy samples from 3 SCD children with normal, moderately, or markedly elevated pocked RBC, showed either an almost normal aspect with congestion, intense sickling, or widespread fibrosis, respectively. Electronic microscopy of the spleen from the child with normal pocked RBC count showed persistent RBC filtration through inter-endothelial slits. Intrasplenic blood was enriched in RBC displaying a peripheral fluorescent dot, highly suggestive of ongoing intrasplenic expulsion of vacuoles (pitting). Automated, operator-independent and fluorescence-based quantification of pocked RBC correlates with the reference method and confirms that spleen function is partially preserved in many adults with SCD.

The present invention relates to an automated method for detecting and counting pocked red blood cells in a blood sample comprising the steps of i) staining the blood sample with an amount of a fluorescent dye, ii) imaging the stained red blood cells and iii) automatically detecting and counting pocked red blood cells.

As used herein, the term “red blood cells” or “RBCs” has its general meaning in the art and refers to highly-specialized cells responsible for delivery of oxygen to, and removal of carbon dioxide from, metabolically-active cells via the capillary network. They are shaped as biconcave discs and average about 8-10 microns in diameter.

As used herein, the term “pocked red blood cells” or “pocked RBCs” has its general meaning in the art and refers to vacuoles-containing RBC as defined in Holroyde CP, Oski FA, Gardner FH. The "pocked" erythrocyte. Red-cell surface alterations in reticuloendothelial immaturity of the neonate. N Engl J Med. 1969 Sep 4;281(10):516-20. doi: 10.1056/NEJM196909042811002. PMID: 4895379. The term is also known as pitted or vacuolated RBCs.

As used herein, term “sample” whole blood sample, red blood cell concentrates and any other sample that contains red blood cells.

As used herein, the term "fluorescent dye" means a dye which absorbs light at a first wavelength and emits at second wavelength which is longer than the first wavelength. Fluorescent dyes typically include fluorescent compounds having a chemically reactive group that facilitates attachment of dye to a conjugate molecule. Numerous fluorescence dyes useful for selective labeling of viable cells are described in the art. For instance, the dye can also be selected from CellTrace™ dyes, such as Cell Trace Yellow CTY® (Thermo Fisher Scientific, France).

In general, the dye is provided to the red blood cells at a concentration ranging from about 0.01 pM to about IpM, preferably 0,05pM. Typically, the incubation step is carried out at 37°C and for at least 10, 15, 20, 25 or 30 minutes preferably 20 minutes. Typically, the red blood cells once stained are centrifugated and washed and then resuspended in an appropriate buffer.

After being contacted with the fluorescent dye, the composition is excited by a light source capable of producing light at or near the wavelength of maximum absorption of the fluorescent complex, such a laser, an arc lamp, an ultraviolet or visible wavelength emission lamp. Any apparatus or device that can both measure the total fluorescence of a sample and can provide imaging of the cells can be used in this invention.

In particular, imaging flow cytometry is particularly suitable for imaging stained red blood cells. In particular, imaging flow cytometer technology, embodied in an instrument marketed under the name ImageStream™ by Amnis Corporation, Seattle Wash., is particularly suitable for imaging stained blood red blood cells. Aspects of the imaging flow cytometer technology are described in the following commonly assigned patents: U.S. Pat. No. 6,249,341, issued on Jun. 19, 2001, entitled “Imaging And Analyzing Parameters of Small Moving Objects Such As Cells;” U.S. Pat. No. 6,211,955 issued on Apr. 3, 2001, also entitled “Imaging And Analyzing Parameters of Small Moving Objects Such As Cells;” U.S. Pat. No. 6,473,176, issued on Oct. 29, 2002, also entitled “Imaging And Analyzing Parameters of Small Moving Objects Such As Cells;” U.S. Pat. No. 6,583,865, issued on Jun. 24, 2003, entitled “Alternative Detector Configuration And Mode of Operation of A Time Delay Integration Particle Analyzer;” and U.S. patent application Ser. No. 09/989,031 entitled “Imaging And Analyzing Parameters of Small Moving Objects Such As Cells in Broad Flat Flow.” While the ImageStream™ platform represents a particularly preferred imaging instrument used to acquire the image data that will be processed in accord with the concepts disclosed herein, it should be understood that the concepts disclosed herein are not limited only to the use of that specific instrument.

In some embodiments, the method of the present invention comprises the steps of a) subjecting the stained red blood cells to imaging flow cytometry to collect a plurality of images of the individual red blood cells present in the sample and b) applying an algorithm configured to detect pocked red blood cells from said plurality of images and c) counting the pocked red blood cells present in the sample.

In particular, the algorithm implements one or more photometric parameters and one or more morphologic parameters that are suitable for distinguishing a pocked red blood cell from a normal red blood cell. Typically the morphologic parameters are derived from the brightfield image and/or the side scatter image, and thus typically include at least one of the cellular size, cellular aera, cellular perimeter, nuclear size, cytoplasmic size, and internal cell granularity of the specific cell. Typically, the photometric parameters can include fluorescence mean intensity and fluorescence median intensity. Therefore the algorithm involves processing the image data collected to determine if any of the imaged cells in the population exhibit one or more parameters associated with pocked red blood cells. A preferred image analysis software package is IDEAS™ (Amnis Corporation, Seattle Wash.). The IDEAS™ package evaluates 250 features for every cell, including multiple morphologic and fluorescence intensity measurements, which can be used to define and characterize cell populations. The IDEAS™ package enables the user to define biologically relevant cell subpopulations, and analyse subpopulations using standard cytometry analyses, such as gating and backgating. It should be understood, however, that other image analysis methods or software packages can be implemented to apply the concepts disclosed herein, and the preferred image analysis software package that is disclosed is intended to be exemplary, rather than limiting of the concepts disclosed herein. The method of the present invention can thus be implemented by a computing system comprising at least one processor which may include one or more Computer processing unit(s) CPU, and/or Graphical Processing Unit(s) GPU, and a non-transitory computer-readable medium storing program code that is executable by the processor, to implement the method described above. The computing system may also comprise at least one memory storing a trained model configured to detected the pocked red blood based on the plurality of photometric and morphologic parameters. The memory may be the same or be distinct from the non- transitory computer-readable medium storing the program code. The memory may for instance be random-access memory (RAM), magnetic hard disk, solid-state disk, optical disk, electronic memory or any type of computer-readable storage medium. The memory may also store other reference data obtained by application of the trained model on a reference population of pocked or normal red blood cells.

Thus, in some embodiments, the algorithm is implemented on a computer using well-known computer processors, memory units, storage devices, computer software, and other components. Typically, the computer contains a processor, which controls the overall operation of the computer by executing computer program instructions which define such operation. The computer program instructions may be stored in a storage device (e.g., magnetic disk) and loaded into memory when execution of the computer program instructions is desired. The computer also includes other input/output devices that enable user interaction with the computer (e.g., display, keyboard, mouse, speakers, buttons, etc.). One skilled in the art will recognize that an implementation of an actual computer could contain other components as well.

In some embodiments, the algorithm is implemented using computers operating in a clientserver relationship. Typically, in such a system, the client computers are located remotely from the server computer and interact via a network. The client-server relationship may be defined and controlled by computer programs running on the respective client and server computers. In some embodiments, the results may be displayed on the system for display, such as with LEDs or an LCD. Accordingly, in some embodiments, the algorithm can be implemented in a computing system that includes a back-end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front-end component, e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation, or any combination of one or more such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (“LAN”) and a wide area network (“WAN”), e.g., the Internet. The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

In some embodiments, the algorithm is implemented within a network-based cloud computing system. In such a network-based cloud computing system, a server or another processor that is connected to a network communicates with one or more client computers via a network. A client computer (e.g. a mobile device, such as a phone, tablet, or laptop computer) may communicate with the server via a network browser application residing and operating on the client computer, for example. A client computer may store data on the server and access the data via the network. A client computer may transmit requests for data, or requests for online services, to the server via the network. The server may perform requested services and provide data to the client computer(s). The server may also transmit data adapted to cause a client computer to perform a specified function, e.g., to perform a calculation, to display specified data on a screen, etc. For instance, the physician may register the parameters (i.e. input data) on, which then transmits the data over a long-range communications link, such as a wide area network (WAN) through the Internet to a server with a data analysis module that will implement the algorithm and finally return the output (e.g. score) to the mobile device.

In some embodiments, the output results can be incorporated in a Clinical Decision Support (CDS) system. These output results can be integrated into an Electronic Medical Record (EMR) system.

The method of the present invention is particularly suitable for assessing the spleen function of a subject. As demonstrated by the EXAMPLE, the pocked red blood cells count is correlated with the spleen function. Many diseases are associated with a dysfunctional spleen including congenital disorders (Congenital asplenia (isolated), Ivemark’s syndrome, Stormorken’s syndrome, Autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED) syndrome, Fetal hydantoin syndrome, Congenital cyanotic heart disease), sickle haemoglobinopathies (e.g. thalassemia and sickle cell disease), gastrointestinal diseases, hepatic disorders, autoimmune disorders, haematological/neoplastic disorders, sepsis and infectious diseases, and splenic diseases (e.g. splenic artery thrombosis, splenic vein thrombosis. . In particular, the method of the present invention is of a particular interest for patients suffering from haematological conditions such as P-hemoglobinopathies such as sickle cell disease or thalassemia (e.g. P-thalassemia). For patients suspected to have a spleen with diminished function, it is important to quantify their spleen function in order to assess the risk of developing overwhelming post-splenectomy infection. Subsequently, preventive measurements can be taken and, in the case of infection, therapy can be started without delay.

Accordingly, a further object of the present invention relates to a method of assessing the spleen function of a subject comprising providing a sample from the subject, counting the pocked blood cells present in the sample by implemented the automated method as above described wherein the pocked red blood cells count correlates with the spleen function of the subject.

Typically, the higher is the pocked red blood cell count, the worse is the spleen function of the subject.

In some embodiments, the method comprises the steps of i) determining the pocked red blood cells count in the sample obtained from the patient, ii) comparing the count determined at step i) with a predetermined reference value, iii) and concluding that the patient has a good spleen function when the count quantified at step i) is lower than the predetermined reference value or concluding that the patient has a poor spleen function when the count determined at step i) is higher than the predetermined reference value.

Typically, the predetermined reference value is a threshold value or a cut-off value. A "threshold value" or "cut-off value" can be determined experimentally, empirically, or theoretically. A threshold value can also be arbitrarily selected based upon the existing experimental and/or clinical conditions, as would be recognized by a person of ordinary skilled in the art. For example, retrospective quantification of pocked red blood cells in properly banked historical subject samples may be used in establishing the predetermined reference value. The threshold value has to be determined in order to obtain the optimal sensitivity and specificity according to the function of the test and the benefit/risk balance (clinical consequences of false positive and false negative). Typically, the optimal sensitivity and specificity (and so the threshold value) can be determined using a Receiver Operating Characteristic (ROC) curve based on experimental data. For example, after determining the pocked red blood cell count in a group of reference, one can use algorithmic analysis for the statistic treatment of the measured amounts of SMEs in samples to be tested, and thus obtain a classification standard having significance for sample classification. The full name of ROC curve is receiver operator characteristic curve, which is also known as receiver operation characteristic curve. It is mainly used for clinical biochemical diagnostic tests. ROC curve is a comprehensive indicator that reflects the continuous variables of true positive rate (sensitivity) and false positive rate (1 -specificity). It reveals the relationship between sensitivity and specificity with the image composition method. A series of different cut-off values (thresholds or critical values, boundary values between normal and abnormal results of diagnostic test) are set as continuous variables to calculate a series of sensitivity and specificity values. Then sensitivity is used as the vertical coordinate and specificity is used as the horizontal coordinate to draw a curve. The higher the area under the curve (AUC), the higher the accuracy of diagnosis. On the ROC curve, the point closest to the far upper left of the coordinate diagram is a critical point having both high sensitivity and high specificity values. The AUC value of the ROC curve is between 1.0 and 0.5. When AUC>0.5, the diagnostic result gets better and better as AUC approaches 1. When AUC is between 0.5 and 0.7, the accuracy is low. When AUC is between 0.7 and 0.9, the accuracy is moderate. When AUC is higher than 0.9, the accuracy is quite high. This algorithmic method is preferably done with a computer. Existing software or systems in the art may be used for the drawing of the ROC curve, such as: MedCalc 9.2.0.1 medical statistical software, SPSS 9.0, ROCPOWER.SAS, DESIGNROC.FOR, MULTIREADER POWER. SAS, CREATE-ROC.SAS, GB STAT VIO.O (Dynamic Microsystems, Inc. Silver Spring, Md., USA), etc. In some embodiments, a cut-off value consists of a range of quantification values, e.g. centered on the quantification value for which the highest statistical significance value is found. For example, on a hypothetical scale of 1 to 10, if the ideal cut-off value (the value with the highest statistical significance) is 5, a suitable (exemplary) range may be from 4-6. For example, a patient may be assessed by comparing values obtained by measuring the pocked red blood cell count, where values greater than 5 reveal that the patient has a poor spleen function and values less than 5 reveal that the patient has a good spleen function. In some embodiments, a patient may be assessed by comparing values obtained by measuring the pocked red blood cell count and comparing the values on a scale, where values above the range of 4-6 indicate that the patient is a poor spleen function and values below the range of 4-6 indicate that the patient has a good spleen function, with values falling within the range of 4-6 indicate that further explorations are needed to conclude whether the patient has or has not a good spleen function. The invention will be further illustrated by the following figures and examples. However, these examples and figures should not be interpreted in any way as limiting the scope of the present invention.

EXAMPLE:

Methods:

Patients

From March 2018 through January 2022, we enrolled seven healthy subjects, 128 adults with SCD and six children with SCD (Assistance Publique-Hopitaux de Paris, France) in a study entitled “Pathophysiological Explorations of Red Blood Cells” (ClinicalTrials.gov reference NCT03541525). Twelve of the adult SCD patients were splenectomized. Based on clinical and imaging data, spleen size was graded by two team members (LJ, SM) unaware of pocked-RBC counts into four categories: splenomegaly, normal, small and atrophic. The children with SCD had partial splenectomy for hypersplenism.

Spleen

A spleen sample from an adult who underwent splenopancreatectomy was collected as a control through Spleenvivo, a protocol approved by the French Institutional Review Board and sponsored by AP-HP. Three post-surgical partial spleens from children enrolled in the above study were retrieved and histology performed as previously described¹⁵. Venous blood samples were taken intraoperatively. Splenic blood was retrieved from spleen fragments as previously described¹.

Pocked-RBC counts by DIC microscopy were performed as previously described⁸.

Fluorescent staining

After buffy coat removal, RBCs were stained with Cell Trace Yellow (CTY; Thermo Fisher Scientific, France) according to the manufacturer’s recommendations with minor modifications. Briefly, 5 pl of the post-centrifugation (1250g, 5 min) pellet were washed twice (400g, 5 min) and incubated for 20 min in phosphate-buffered saline (PBS) with CTY 1/500 v/v. The staining reaction was stopped with PBS containing 1% Albumax (Gibco, France) for 5 min. RBCs were washed twice and resuspended in 500pl 1% Albumax-PBS at 1% hematocrit. Imaging Flow Cytometry

Imaging flow cytometry (IFC; ImageStream X Mark II, AMNIS, Luminex) was performed to acquire (INSPIRE software, Luminex) brightfield (channel 01) and fluorescence images (Laser 561nm, 20mW, Channel 03) at 60x magnification. At least 50,000 RBCs were acquired for each sample. Images were processed with the IDEAS v6.2 software (Luminex). Focused RBCs were selected using gradient root mean square values, and single cells gated using area and aspect ratio functions. The IDEAS “Spot Count” wizard was used to discriminate fluorescent spot-containing from spotless RBCs. As per software recommendations, 282 and 165 images were tagged respectively.

Herniated pocked-RBCs

Peripheral and splenic blood¹ from the six SCD children were CTY-labelled and the proportion of elongated RBCs containing peripheral vacuoles suggestive of ongoing pitting (“herniated pocked-RBCs”) was determined in at least 300 counted CTY-positive RBCs. Parallel quantification of this subpopulation on IFC images by three independent readers displayed <15% variation (not shown).

Results:

We counted pocked-RBCs with IFC and DIC in 216 samples (data not shown). The IDEAS script efficiently discriminated CTY-spotted from spotless RBCs on IFC images. As opposed to conventional epifluorescence microscopy, where the even staining of RBC cytoplasm by CTY results in suboptimal discrimination, the IDEAS software offers fine adjustment of fluorescence intensity and thus reproducible discrimination between background cytoplasmic fluorescence and the slightly more intense vacuole fluorescence. RBCs with one or more fluorescent vacuoles were counted as pocked-RBCs (data not shown). Fluorescence-based and manual counts were correlated (Spearman r = 0.8410, p< 0001 data not shown), although pocked-RBC counts were 20-30% lower by IFC than by DIC. Because pocked-RBC quantification correlates with splenic scintigraphy results¹⁴, this new fluorescence-based counting method is a strong candidate marker of spleen function⁸-¹⁴ that can be automated on 20pl of blood. The proportion of pocked-RBCs changed by <10% when blood was stored at 4°C for 48 hours in heparin-containing sampling tubes (not shown). The IDEAS software also quantifies RBC morphological features¹⁶ on brightfield IFC images, a potentially useful asset in medical hematology. Some experts consider that adults with SCD are almost constantly asplenic with an atrophic spleen¹⁷-¹⁸. However, among our 128 SCD adults, we observed large variations in spleen size, including approximately 50% of normally-sized or enlarged spleens. Pocked-RBC counts with either DIC or IFC correlated strongly with spleen size (data not shown). Pocked-RBC counts in SCD patients with either atrophic or removed spleens were similarly high, suggesting that splenic atrophy corresponds to complete asplenia. Conversely, patients with either enlarged, normal or small spleens had more variable counts, suggesting that splenic filtering function is often preserved in SCD, at least partially, even in adulthood. Management of SCD at reference centers, including early use of hydroxyurea and transfusion programs, may contribute to this preservation of spleen function⁸.

We retrieved spleen fragments from an adult splenectomized patient without underlying RBC disease as a control, and from three SCD children partially splenectomized for hypersplenism. The adult patient had a low pocked-RBC count (0.7%), and normal spleen histology with preserved structures, a balanced red/white pulp distribution, and normally-shaped RBCs exclusively (data not shown). The three spleens from SCD children displayed variable damage, consistent with the pocked-RBC counts. The SCD child with a normal pocked-RBC count (2.3%) showed red pulp congestion. Mild to moderate sickling (data not shown) was observed in arterioles and sinuses by electron microscopy (data not shown). Normal sinuses were observed on histology and electron microscopy, with typical images of RBCs crossing an intact sinus wall (data not shown). The spleen from the child with a mildly elevated pocked- RBC count (13.9%) had marked and non-homogeneous sickling in the red pulp as well as intense congestion (data not shown). The spleen from the SCD child with a high pocked-RBC count (31.4%) had a dissolution of white pulp structures, widespread fibrosis and sickling (data not shown).

Because histology and electron microscopy suggested the persistence of pitting in some SCD spleens, we quantified elongated RBCs harboring a peripheral, “herniated” vacuole, a morphology highly suggestive of ongoing pitting¹⁹ (data not shown). Compared to circulating blood, the splenic blood from the six SCD children showed a 1.9 to 5-fold enrichment in these “herniated” pocked-RBCs, strongly suggesting that RBCs with CTY-positive vacuoles are indeed pitted in the spleen (data not shown). Conclusions:

In our study, this new fluorescence-based quantification of pocked-RBCs, employing the spontaneous accumulation of CTY dye in vacuoles, correlated with the reference DIC counts. It thus lays a path to robust, operator-independent quantification of spleen function. We showed that spleen function is partially preserved in many adults with SCD and that the fluorescent vacuoles that accumulate in RBCs from SCD patients are indeed expelled by the spleen-specific pitting process, as long as sinus structures persist in the partially damaged SCD spleens. Measuring residual spleen function is useful for major therapeutic decisions such as splenectomy, hematopoietic stem cell transplantation, or gene therapy.

REFERENCES:

Throughout this application, various references describe the state of the art to which this invention pertains. The disclosures of these references are hereby incorporated by reference into the present disclosure.

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2. Buffet PA, Safeukui I, Deplaine G, et al. The pathogenesis of Plasmodium falciparum malaria in humans: insights from splenic physiology. Blood. 2011;117(2):381— 392.

3. Safeukui I, Buffet PA, Deplaine G, et al. Quantitative assessment of sensing and sequestration of spherocytic erythrocytes by the human spleen. Blood. 2012;120(2):424-430.

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6. Eraklis AJ, Kevy SV, Diamond LK, Gross RE. Hazard of Overwhelming Infection after Splenectomy in Childhood. N Engl J Med. 1967;276(22): 1225-1229.

7. Emond AM, Collis R, Darvill D, et al. Acute splenic sequestration in homozygous sickle cell disease: Natural history and management. The Journal of Pediatrics. 1985;107(2):201-206.

8. Rogers ZR, Wang WC, Luo Z, et al. Biomarkers of splenic function in infants with sickle cell anemia: baseline data from the BABY HUG Trial. Blood. 2011;117(9):2614-2617. 9. Holroyde CP, Gardner FH. Acquisition of Autophagic Vacuoles by Human Erythrocytes Physiological Role of the Spleen. Blood. 1970;36(5):566-575.

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13. Rogers DW, Serjeant BE, Seijeant GR. Early rise in “pitted” red cell count as a guide to susceptibility to infection in childhood sickle cell anaemia. 5.

14. Pearson HA, Gallagher D, Chilcote R, et al. Developmental Pattern of Splenic Dysfunction in Sickle Cell Disorders. Pediatrics. 1985;76(3):392-397.

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Claims

CLAIMS:

1. An automated method for detecting and counting pocked red blood cells in a blood sample comprising the steps of i) staining the blood sample with an amount of a fluorescent dye, ii) imaging the stained red blood cells and iii) automatically detecting and counting pocked red blood cells.

2. The method of claim 1 wherein the fluorescent dye is CTY.

3. The method of claim 1 that comprises the steps of a) subjecting the stained red blood cells to imaging flow cytometry to collect a plurality of images of the individual red blood cells present in the sample and b) applying an algorithm configured to detect pocked red blood cells from said plurality of images and c) counting the pocked red blood cells present in the sample.

4. The method according to any one of preceding claims wherein the algorithm implements one or more photometric parameters and one or more morphologic parameters that are suitable for distinguishing a pocked red blood cell from a normal red blood cell.

5. The method of claim 4 wherein the morphologic features are derived from the brightfield image and/or the side scatter image, and thus typically include at least one of the cellular size, cellular aera, cellular perimeter, nuclear size, cytoplasmic size, and internal cell granularity of the specific cell.

6. The method of claim 4 wherein the photometric parameters include fluorescence mean intensity and fluorescence median intensity.

7. The method of claim 4 wherein the algorithm involves processing the image data collected to determine if any of the imaged cells in the population exhibit one or more parameters associated with pocked red blood cells.

8. A method of assessing the spleen function of a subject comprising providing a sample from the subject, counting the pocked blood cells present in the sample by implemented the automated method according to any one of claims 1 to 7 wherein the pocked red blood cells count correlates with the spleen function of the subject. The method of claim 8 wherein the higher is the pocked red blood cell count, the worse is the spleen function of the subject. The method of claim 8 that comprises the steps of i) determining the pocked red blood cells count in the sample obtained from the patient, ii) comparing the count determined at step i) with a predetermined reference value, iii) and concluding that the patient has a good spleen function when the count quantified at step i) is lower than the predetermined reference value or concluding that the patient has a poor spleen function when the count determined at step i) is higher than the predetermined reference value.