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Kushwaha A, Mourad RF, Heist K, Tariq H, Chan HP, Ross BD, Chenevert TL, Malyarenko D, Hadjiiski LM. Improved Repeatability of Mouse Tibia Volume Segmentation in Murine Myelofibrosis Model Using Deep Learning. Tomography 2023; 9:589-602. [PMID: 36961007 PMCID: PMC10037585 DOI: 10.3390/tomography9020048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 03/02/2023] [Accepted: 03/03/2023] [Indexed: 03/09/2023] Open
Abstract
A murine model of myelofibrosis in tibia was used in a co-clinical trial to evaluate segmentation methods for application of image-based biomarkers to assess disease status. The dataset (32 mice with 157 3D MRI scans including 49 test-retest pairs scanned on consecutive days) was split into approximately 70% training, 10% validation, and 20% test subsets. Two expert annotators (EA1 and EA2) performed manual segmentations of the mouse tibia (EA1: all data; EA2: test and validation). Attention U-net (A-U-net) model performance was assessed for accuracy with respect to EA1 reference using the average Jaccard index (AJI), volume intersection ratio (AVI), volume error (AVE), and Hausdorff distance (AHD) for four training scenarios: full training, two half-splits, and a single-mouse subsets. The repeatability of computer versus expert segmentations for tibia volume of test-retest pairs was assessed by within-subject coefficient of variance (%wCV). A-U-net models trained on full and half-split training sets achieved similar average accuracy (with respect to EA1 annotations) for test set: AJI = 83-84%, AVI = 89-90%, AVE = 2-3%, and AHD = 0.5 mm-0.7 mm, exceeding EA2 accuracy: AJ = 81%, AVI = 83%, AVE = 14%, and AHD = 0.3 mm. The A-U-net model repeatability wCV [95% CI]: 3 [2, 5]% was notably better than that of expert annotators EA1: 5 [4, 9]% and EA2: 8 [6, 13]%. The developed deep learning model effectively automates murine bone marrow segmentation with accuracy comparable to human annotators and substantially improved repeatability.
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Ross BD, Malyarenko D, Heist K, Amouzandeh G, Jang Y, Bonham CA, Amirfazli C, Luker GD, Chenevert TL. Repeatability of Quantitative Magnetic Resonance Imaging Biomarkers in the Tibia Bone Marrow of a Murine Myelofibrosis Model. Tomography 2023; 9:552-566. [PMID: 36961004 PMCID: PMC10037563 DOI: 10.3390/tomography9020045] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 02/23/2023] [Accepted: 02/24/2023] [Indexed: 03/04/2023] Open
Abstract
Quantitative MRI biomarkers are sought to replace painful and invasive sequential bone-marrow biopsies routinely used for myelofibrosis (MF) cancer monitoring and treatment assessment. Repeatability of MRI-based quantitative imaging biomarker (QIB) measurements was investigated for apparent diffusion coefficient (ADC), proton density fat fraction (PDFF), and magnetization transfer ratio (MTR) in a JAK2 V617F hematopoietic transplant model of MF. Repeatability coefficients (RCs) were determined for three defined tibia bone-marrow sections (2-9 mm; 10-12 mm; and 12.5-13.5 mm from the knee joint) across 15 diseased mice from 20-37 test-retest pairs. Scans were performed on consecutive days every two weeks for a period of 10 weeks starting 3-4 weeks after transplant. The mean RC with (95% confidence interval (CI)) for these sections, respectively, were for ADC: 0.037 (0.031, 0.050), 0.087 (0.069, 0.116), and 0.030 (0.022, 0.044) μm2/ms; for PDFF: 1.6 (1.3, 2.0), 15.5 (12.5, 20.2), and 25.5 (12.0, 33.0)%; and for MTR: 0.16 (0.14, 0.19), 0.11 (0.09, 0.15), and 0.09 (0.08, 0.15). Change-trend analysis of these QIBs identified a dynamic section within the mid-tibial bone marrow in which confident changes (exceeding RC) could be observed after a four-week interval between scans across all measured MRI-based QIBs. Our results demonstrate the capability to derive quantitative imaging metrics from mouse tibia bone marrow for monitoring significant longitudinal MF changes.
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Affiliation(s)
- Brian D Ross
- Department of Radiology and the Center for Molecular Imaging, University of Michigan School of Medicine, Ann Arbor, MI 48109, USA
- Department of Biological Chemistry, University of Michigan School of Medicine, Ann Arbor, MI 48109, USA
| | - Dariya Malyarenko
- Department of Radiology and the Center for Molecular Imaging, University of Michigan School of Medicine, Ann Arbor, MI 48109, USA
| | - Kevin Heist
- Department of Radiology and the Center for Molecular Imaging, University of Michigan School of Medicine, Ann Arbor, MI 48109, USA
| | - Ghoncheh Amouzandeh
- Department of Radiology and the Center for Molecular Imaging, University of Michigan School of Medicine, Ann Arbor, MI 48109, USA
| | - Youngsoon Jang
- Department of Radiology and the Center for Molecular Imaging, University of Michigan School of Medicine, Ann Arbor, MI 48109, USA
| | - Christopher A Bonham
- Department of Radiology and the Center for Molecular Imaging, University of Michigan School of Medicine, Ann Arbor, MI 48109, USA
| | - Cyrus Amirfazli
- Department of Radiology and the Center for Molecular Imaging, University of Michigan School of Medicine, Ann Arbor, MI 48109, USA
| | - Gary D Luker
- Department of Radiology and the Center for Molecular Imaging, University of Michigan School of Medicine, Ann Arbor, MI 48109, USA
- Department of Microbiology and Immunology, University of Michigan School of Medicine, Ann Arbor, MI 48109, USA
| | - Thomas L Chenevert
- Department of Radiology and the Center for Molecular Imaging, University of Michigan School of Medicine, Ann Arbor, MI 48109, USA
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Góra-Tybor J, Gołos A, Mikulski D, Helbig G, Sacha T, Lewandowski K, Niesiobędzka-Krężel J, Bieniaszewska M, Wysogląd H, Grzybowska-Izydorczyk O, Seferyńska I, Sobas M, Czyżewska M, Michalska A, Sawicki W, Mazur M, Hus M, Bodzenta E, Olszewska-Szopa M, Włodarczyk M, Patkowska E, Świstek W, Jamroziak K. Analysis of Predictive Factors for Early Response to Ruxolitinib in 320 Patients with Myelofibrosis From the Polish Adult Leukemia Group (PALG) Registry. CLINICAL LYMPHOMA, MYELOMA & LEUKEMIA 2023; 23:e19-e26. [PMID: 36396583 DOI: 10.1016/j.clml.2022.10.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 10/11/2022] [Accepted: 10/13/2022] [Indexed: 11/05/2022]
Abstract
INTRODUCTION Ruxolitinib is widely used in myelofibrosis (MF). However, some patients do not optimally respond and require more efficacious treatment. Our analysis aimed to establish predictors of ruxolitinib response. PATIENTS AND METHODS We designed a multicenter, retrospective analysis of the efficacy of ruxolitinib treatment in patients with MF in 15 Polish hematology centers. As responses to ruxolitinib occur within the first 6 months, we used this point to evaluate the efficacy of treatment. Symptoms response was defined as ≥50% reduction of the MF constitutional symptoms assessed by Myeloproliferative Neoplasm Symptom Assessment Form Total Symptom Score (MPN-SAF TSS). Spleen response was defined as ≥50% reduction of the difference between the spleen's baseline length and the upper limit norm measured by ultrasonography. RESULTS 320 MF patients were enrolled. At 6 months of therapy, the spleen response was detected in 140 (50%) patients, and symptoms response in 241 patients (76%). Multivariable analysis identified leukocytosis <25 G/L (OR 2.06, 95%CI: 1.12-3.88, P = .0200), and reticulin fibrosis MF 1 (OR 2.22, 95%CI: 1.11-4.46, P = .0249) contributed to better spleen response. The time interval between MF diagnosis and ruxolitinib administration shorter than 3 months, and platelets ≥150 G/L (OR 1.69, 95% CI 1.01-2.83, P = .0466) influenced symptoms response. CONCLUSION Establishing predictive factors for ruxolitinib response is particularly important given the potential for new therapies in MF. In patients with a low likelihood of responding to ruxolitinib, using other JAK inhibitors or adding a drug with a different mechanism of action to ruxolitinib may be of clinical benefit.
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Affiliation(s)
- Joanna Góra-Tybor
- Department of Hematology, Medical University of Lodz, Copernicus Memorial Hospital, Lodz, Poland.
| | - Aleksandra Gołos
- Hematooncology Department, Copernicus Memorial Hospital, Lodz, Lodz, Poland
| | - Damian Mikulski
- Hematooncology Department, Copernicus Memorial Hospital, Lodz, Lodz, Poland; Department of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz Poland
| | - Grzegorz Helbig
- School of Medicine in Katowice, Department of Hematology and Bone Marrow Transplantation, Medical University of Silesia, Katowice, Poland
| | - Tomasz Sacha
- Department of Hematology, Jagiellonian University Hospital, Krakow, Ploland
| | - Krzysztof Lewandowski
- Department of Hematology and Bone Marrow Transplantation, Poznan University of Medical Sciences, Poznan, Poland
| | - Joanna Niesiobędzka-Krężel
- Department of Hematology, Transplantation and Internal Medicine, Medical University of Warsaw, Warsaw, Poland
| | - Maria Bieniaszewska
- Department of Hematology and Transplantology, Medical University of Gdansk, Gdansk, Poland
| | - Hubert Wysogląd
- Department of Hematology, Jagiellonian University Hospital, Krakow, Ploland
| | | | - Ilona Seferyńska
- Department of Hematology, Institute of Hematology and Transfusion Medicine, Warsaw, Poland
| | - Marta Sobas
- Department of Hematology, Wroclaw Medical University, Wroclaw, Wroclaw, Poland
| | - Maria Czyżewska
- Department of Hematology, Nicolaus Copernicus Specialist Municipal Hospital, Torun, Poland
| | | | - Waldemar Sawicki
- Department of Internal Diseases and Hematology, Military Institute of Medicine, Warsaw, Poland
| | - Malwina Mazur
- Department of Hematology, Teaching Hospital No 1, Rzeszow, Poland
| | - Marek Hus
- Chair and Department of Haematooncology and Bone Marrow Transplantation, Medical University of Lublin, Lublin, Poland
| | - Ewa Bodzenta
- Department of Hematology and Cancer Prevention, Chorzow, Poland
| | | | - Martyna Włodarczyk
- School of Medicine in Katowice, Department of Hematology and Bone Marrow Transplantation, Medical University of Silesia, Katowice, Poland
| | - Elżbieta Patkowska
- Department of Hematology, Institute of Hematology and Transfusion Medicine, Warsaw, Poland
| | - Wojciech Świstek
- Hematology Department, Jan Biziel University Hospital No. 2, Bydgoszcz, Poland
| | - Krzysztof Jamroziak
- Department of Hematology, Transplantation and Internal Medicine, Medical University of Warsaw, Warsaw, Poland
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Borgström EW, Edvinsson M, Pérez LP, Norlin AC, Enoksson SL, Hansen S, Fasth A, Friman V, Kämpe O, Månsson R, Estupiñán HY, Wang Q, Ziyang T, Lakshmikanth T, Smith CIE, Brodin P, Bergman P. Three Adult Cases of STAT1 Gain-of-Function with Chronic Mucocutaneous Candidiasis Treated with JAK Inhibitors. J Clin Immunol 2023; 43:136-150. [PMID: 36050429 PMCID: PMC9840596 DOI: 10.1007/s10875-022-01351-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 08/08/2022] [Indexed: 01/21/2023]
Abstract
PURPOSE The aim of this study was to characterize clinical effects and biomarkers in three patients with chronic mucocutaneous candidiasis (CMC) caused by gain-of-function (GOF) mutations in the STAT1 gene during treatment with Janus kinase (JAK) inhibitors. METHODS Mass cytometry (CyTOF) was used to characterize mononuclear leukocyte populations and Olink assay to quantify 265 plasma proteins. Flow-cytometric Assay for Specific Cell-mediated Immune-response in Activated whole blood (FASCIA) was used to quantify the reactivity against Candida albicans. RESULTS Overall, JAK inhibitors improved clinical symptoms of CMC, but caused side effects in two patients. Absolute numbers of neutrophils, T cells, B cells, and NK cells were sustained during baricitinib treatment. Detailed analysis of cellular subsets, using CyTOF, revealed increased expression of CD45, CD52, and CD99 in NK cells, reflecting a more functional phenotype. Conversely, monocytes and eosinophils downregulated CD16, consistent with reduced inflammation. Moreover, T and B cells showed increased expression of activation markers during treatment. In one patient with a remarkable clinical effect of baricitinib treatment, the immune response to C. albicans increased after 7 weeks of treatment. Alterations in plasma biomarkers involved downregulation of cellular markers CXCL10, annexin A1, granzyme B, granzyme H, and oncostatin M, whereas FGF21 was the only upregulated marker after 7 weeks. After 3 months, IFN-ɣ and CXCL10 were downregulated. CONCLUSIONS The clinical effect of JAK inhibitor treatment of CMC is promising. Several biological variables were altered during baricitinib treatment demonstrating that lymphocytes, NK cells, monocytes, and eosinophils were affected. In parallel, cellular reactivity against C. albicans was enhanced.
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Affiliation(s)
- Emilie W. Borgström
- Department of Laboratory Medicine, Clinical Microbiology, Stockholm, Sweden ,grid.24381.3c0000 0000 9241 5705Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Marie Edvinsson
- grid.412354.50000 0001 2351 3333Department of Medical Sciences, Section of Infectious Diseases, Uppsala University Hospital, Uppsala, Sweden
| | - Lucía P. Pérez
- grid.4714.60000 0004 1937 0626Department of Laboratory Medicine, Biomolecular and Cellular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Anna C. Norlin
- grid.24381.3c0000 0000 9241 5705Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden ,grid.24381.3c0000 0000 9241 5705Department of Clinical Immunology and Transfusion Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Sara L. Enoksson
- grid.24381.3c0000 0000 9241 5705Department of Clinical Immunology and Transfusion Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Susanne Hansen
- grid.24381.3c0000 0000 9241 5705Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Anders Fasth
- grid.8761.80000 0000 9919 9582Department of Pediatrics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Vanda Friman
- grid.8761.80000 0000 9919 9582Department of Infectious Diseases, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Olle Kämpe
- grid.4714.60000 0004 1937 0626Experimental Endocrinology, Department of Medicine, Karolinska Institutet, Solna, Stockholm, Sweden
| | - Robert Månsson
- grid.4714.60000 0004 1937 0626Department of Laboratory Medicine, Biomolecular and Cellular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Hernando Y. Estupiñán
- grid.4714.60000 0004 1937 0626Department of Laboratory Medicine, Biomolecular and Cellular Medicine, Karolinska Institutet, Stockholm, Sweden ,grid.411595.d0000 0001 2105 7207Departamento de Ciencias Básicas, Universidad Industrial de Santander, 680002 Bucaramanga, Colombia
| | - Qing Wang
- grid.4714.60000 0004 1937 0626Department of Laboratory Medicine, Biomolecular and Cellular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Tan Ziyang
- grid.4714.60000 0004 1937 0626Science for Life Laboratory, Department of Women’s and Children’s Health, Karolinska Institutet, Stockholm, Sweden
| | - Tadepally Lakshmikanth
- grid.4714.60000 0004 1937 0626Science for Life Laboratory, Department of Women’s and Children’s Health, Karolinska Institutet, Stockholm, Sweden
| | - Carl Inge E. Smith
- grid.24381.3c0000 0000 9241 5705Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden ,Department of Laboratory Medicine, Translational Research Center Karolinska (TRACK), Stockholm, Sweden
| | - Petter Brodin
- grid.4714.60000 0004 1937 0626Science for Life Laboratory, Department of Women’s and Children’s Health, Karolinska Institutet, Stockholm, Sweden ,grid.7445.20000 0001 2113 8111Department of Immunology and Inflammation, Imperial College London, London, UK
| | - Peter Bergman
- Department of Laboratory Medicine, Clinical Microbiology, Stockholm, Sweden ,grid.24381.3c0000 0000 9241 5705Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
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Ghit A. Myelofibrosis treatment history and future prospects. THE EGYPTIAN JOURNAL OF INTERNAL MEDICINE 2022. [DOI: 10.1186/s43162-022-00169-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
AbstractMyelofibrosis (MF) is a haematopoietic stem cell tumour caused by the lack of BCR-ABL translocation due to point mutations in Janus kinases (JAKs). In previous years, dealing with MF included several protocols such as traditional drugs that control general symptoms, splenectomy, blood transfusion, and allogeneic haematopoietic stem-cell transplantation (HSCT). Allogeneic HSCT is remaining the only treatment that has the potential to alter MF’s progression. However, clinical trials of JAK inhibitors and non-JAK targeted therapies have been increasingly carried out in earlier years. The most prominent JAK inhibitors for the treatment of MF are ruxolitinib, fedratinib, momelotinib, pacritinib, gandotinib, ilginatinib, itacitinib, and lestaurtinib. On the other hand, the non-JAK targeted therapies that showed strong efficacy and safety are alisertib, imetelstat, pembrolizumab, nivolumab, and sotatercept. In this review, we summarized the recent clinical trials carried out on these drugs to understand their efficacy and safety. Also, we talked briefly about allogeneic HSCT as powerful therapy until the present for patients suffering from MF.
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