scholarly journals Bone marrow cells recognition methods in the diagnosis of minimal residual disease

2020 ◽  
Vol 169 ◽  
pp. 353-358 ◽  
Author(s):  
Valentin Nikitaev ◽  
Alexander Pronichev ◽  
Evgeney Polyakov ◽  
Olga Chernysheva ◽  
Irina Serebryakova ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Minimal Residual Disease ◽  
Bone Marrow Cells ◽  
Residual Disease ◽  
Minimal Residual ◽  
Marrow Cells

Unusual Immunophenotypes in the Bone Marrow of Infants with Acute Leukemia: Minimal Residual Disease or ATRA-Mediated Regeneration?.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 4260-4260
Author(s):  
Alexander Popov ◽  
Tatiana Verzhbitskaya ◽  
Grigory Tsaur ◽  
Egor Shorikov ◽  
Leonid Saveliev ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Flow Cytometry ◽  
Minimal Residual Disease ◽  
Bone Marrow Cells ◽  
Residual Disease ◽  
Multicolor Flow Cytometry ◽  
Acute Leukemias ◽  
Short Period ◽  
Minimal Residual ◽  
Marrow Cells

Abstract Minimal Residual Disease (MRD) monitoring is essential to predict early outcome and further optimize treatment, especially when new approaches to therapy are used. A promising new treatment is the combination of chemotherapy with all trans-retinoic acid (ATRA) for infant acute leukemias. ATRA-mediated maturation of bone marrow cells can lead to the appearance of unusual undifferentiated cells with new immunological characteristics. We investigated the immunophenotypic features of bone marrow cells in infant acute leukemias treated with traditional chemotherapy combined with ATRA. From May 2006 to July 2007, we performed initial and consecutive multicolor flow cytometry assays of bone marrow samples from 4 infants with primary ALL or AML (except M3) treated at our institution. Patient I had BII-ALL, co-expressing CD15, but the majority of his blast cells were CD10(-). Conventional cytogenetics revealed t(4;11) and MLL/AF4 was detected. Early after ATRA administration, we detected MPO(+)TdT(+)-cells and subsequently, CD19, CD10, CD34, CD99 positive cells were found. Moreover, those cells occupied the “blast region” (SSC(low)CD45(dim)) and were seen as an autonomous population on the FSC/SSC dot plot. There was no correlation with the number of CD19(+)MPO(+)-cells and either MRD, measured by multicolor flow cytometry, or the level of the fusion gene transcript performed by the quantitative real-time polymerase chain reaction. In patient II with primary AML-M2, the cells with the same phenotype were also detected after several ATRA courses. Patient III, with primary biphenotypic leukemia, demonstrated total clearance of tumor blasts after the beginning of ATRA treatment with the later appearance of two cells populations: one similar to the phenotype previously described in patients I and II, but additionally expressing CD79a. The second cell population was positive for the cortical thymocytes markers CD7, CD5, CD2, CD4, CD8 and CD1a. This phenotype was observed shortly after ATRA initiation and disappeared with further chemotherapy. Patient IV with primary AML-M7 was switched to BII-ALL after the 3rd ATRA course. Simultaneously, a minor population of biphenotypic cells was observed and later comprised 2 groups: TdT(−)CD99(−)CD45(bright) and TdT(+)CD99(+)CD45(dim) cells. We infer from this observation that the biphenotypic cells had matured. Cortical thymocytes were also detected in this patient for a short period. In all 4 patients we observed an equal distribution of biphenotypic cells on dot plots despite the differences in the primary leukemia phenotypes. This raises the question of a tumor versus an ATRA-mediated origin of the biphenotypic cells that requires further investigation in the patients treated with ATRA. Moreover, we conclude that a more extensive and specific panel of monoclonal antibodies is also required for the full immunophenotypic characterization of infant leukemia.

METHODS OF MULTICLASSICATION OF BONE MARROW CELLS FOR THE DIAGNOSIS OF ACUTE LEUKEMIA AND MINIMAL RESIDUAL DISEASE (ON THE MATERIALS OF THE LABORATORY OF HEMATOPOIESIS OF N. N. BLOKHIN NATIONAL MEDICAL RESEARCH CENTER OF ONCOLOGY)

2020 ◽  
pp. 155-158
Author(s):  
Валентина Викторовна Дмитриева ◽  
Николай Николаевич Тупицын ◽  
Евгений Валерьевич Поляков ◽  
Софья Сергеевна Денисюк
Keyword(s):  
Bone Marrow ◽  
Acute Leukemia ◽  
Medical Research ◽  
Bone Marrow Cells ◽  
Residual Disease ◽  
Binary Classification ◽  
National Medical ◽  
Cell Class ◽  
Minimal Residual ◽  
Marrow Cells

Применение методов и средств цифровой обработки изображений при распознавании типов клеток крови и костного мозга для повышения качества диагностики острых лейкозов является актуальной научно-технической задачей, отвечающей стратегии развития технологий искусственного интеллекта в медицине. В работе предложен подход к мультиклассификации клеток костного мозга при диагностике острых лейкозов и минимальной остаточной болезни. Для проведения экспериментальных исследований сформирована выборка из 3284 изображений клеток, представленных Лабораторией гемопоэза Национального медицинского исследовательского центра онкологии им. Н.Н. Блохина. Предложенный подход к мультиклассификации клеток костного мозга основан на бинарной модели классификации для каждого из исследуемых классов относительно остальных. В рассматриваемой работе бинарная классификация выполняется методом опорных векторов. Метод мультиклассификации был программно реализован с применением интерпретатора Python 3.6.9. Входными данными программы служат файлы формата *.csv с таблицами морфологических, цветовых, текстурных признаков для каждой из клеток используемой выборки. В выборке представлено девять типов клеток костного мозга. Выходными данными программы мультиклассификации являются значения точности классификации на тестовой выборке, которые отражают совпадение прогнозируемого класса клетки с фактическим (верифицированным) классом клетки. “Эксперимент показал следующие результаты: точность мультиклассификации рассматриваемых типов клеток в среднем составила: 87% на тестовом наборе, 88% на обучающем наборе данных. Проведенное исследование является предварительным. В дальнейшем планируется увеличить число классов клеток, объем выборок различных типов клеток и с уточнением результатов мультиклассификации The use of methods and means of digital image processing in the recognition of types of blood cells and bone marrow to improve the quality of diagnosis of acute leukemia is an urgent scientific and technical task that meets the strategy for the development of artificial intelligence technologies in medicine. The paper proposes an approach to the multiclassification of bone marrow cells in the diagnosis of acute leukemia and minimal residual disease. For experimental studies, a sample of 3284 images of cells was formed, submitted by the Hematopoiesis Laboratory of the National Medical Research Center of Oncology named after V.I. N.N. Blokhin. The proposed approach to the multiclassification of bone marrow cells is based on a binary classification model for each of the studied classes relative to the others. In the work under consideration, binary classification is performed by the support vector machine. The multiclassification method was implemented programmatically using the Python 3.6.9 interpreter. The input data of the program are * .csv files with tables of morphological, color, texture features for each of the cells of the sample used. The sample contains nine types of bone marrow cells. The output data of the multiclassification program are the classification accuracy values on the test sample, which reflect the coincidence of the predicted cell class with the actual (verified) cell class. “The experiment showed the following results: the accuracy of multiclassification of the considered types of cells on average was: 87% on the test set, 88% on the training data set. This study is preliminary. In the future, it is planned to increase the number of classes of cells, the volume of samples of various types of cells and with the refinement of the results of multiclassification

Minimal residual disease in acute lymphoblastic leukemia detected by immune selection and gene rearrangement analysis.

1989 ◽  
Vol 7 (3) ◽  
pp. 338-343 ◽  
Author(s):  
M Bregni ◽  
S Siena ◽  
A Neri ◽  
R Bassan ◽  
T Barbui ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Acute Lymphoblastic Leukemia ◽  
Minimal Residual Disease ◽  
Gene Rearrangement ◽  
Bone Marrow Cells ◽  
Residual Disease ◽  
Lymphoblastic Leukemia ◽  
Immune Selection ◽  
Gene Rearrangement Analysis ◽  
Minimal Residual

We have developed an assay for the detection of malignant residual cells in the bone marrow from patients with B- or T-lineage acute lymphoblastic leukemia (ALL) in clinical remission. This assay involves an immune selection step followed by immunoglobulin or T-cell receptor gene rearrangement analysis and allows the detection of one contaminating tumor cell out of 1,000 normal bone marrow cells. We have examined the bone marrow of 11 patients with adult ALL in remission over a 24-month period. Five patients relapsed in the bone marrow and one in the CNS. The assay allowed the detection of minimal residual disease in four of five patients that subsequently relapsed in the bone marrow, 1.5 to 9 months before the relapse became morphologically and clinically manifest. Residual disease was not found in the bone marrow from patients in continuous remission and from the single patient who relapsed in the CNS. We conclude that the ability of the assay described here to detect minimal residual disease with high specificity can provide information for further understanding of the biology of ALL and hopefully for the clinical management of patients with this disease.

Determination of Minimal Residual Disease in Patients with Acute Myeloid Leukemia by Multiparameter Flow Cytometry: Prognostic Impact at Different Checkpoints.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 400-400 ◽  
Author(s):  
Wolfgang Kern ◽  
Daniela Voskova ◽  
Claudia Schoch ◽  
Wolfgang Hiddemann ◽  
Susanne Schnittger ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Myeloid Leukemia ◽  
Bone Marrow Cells ◽  
Residual Disease ◽  
Multiparameter Flow Cytometry ◽  
Prognostic Impact ◽  
Minimal Residual ◽  
Marrow Cells

Abstract Guiding antileukemic treatment in patients with acute myeloid leukemia (AML) is increasingly based on levels of minimal residual disease (MRD) which can be quantified with high sensitivity by multiparameter flow cytometry (MFC). The optimum checkpoint for determination of MRD during the course of therapy, however, has not yet been determined. We applied MFC using a comprehensive panel of antibodies to identify leukemia-associated aberrant immunophenotypes (LAIPs) at diagnosis and to quantify MRD by individually selected antibody combinations. The prognostic impact of MRD levels was assessed in comparison to cytogenetics and age. Patients received double induction, consolidation, and maintenance therapies and underwent allogeneic stem cell transplantation if they were younger than 60 years and had a matched related donor. In 286 patients with newly diagnosed and untreated AML MFC-based assessment for the presence of LAIP has been performed. The median percentage of LAIP-positive bone marrow cells at diagnosis was 16.04% (range, 2.54%–76.14%). All individual LAIPs were applied to 26 normal bone marrow samples to estimate sensitivity based on the median percentages of LAIP-positive normal bone marrow cells which ranged from 0.00% to 1.01% (median, 0.02%). A total of 550 follow-up samples has been analyzed in these patients at different checkpoints (CP1, up to day 21 after start of therapy, n=85; CP2, day 22–60, n=122; CP3, day 61–120, n=158; CP4, day 121–365, n=137; CP5, after day 365, n=48). In order to adjust for differences in the percentages of LAIP-positive bone marrow cells at diagnosis the logarithmic difference (LD) between diagnosis and follow-up was calculated for each follow-up sample. The median LDs at the respective checkpoints were: CP1, 2.02; CP2, 2.29; CP3, 2.39; CP4, 2.53; and CP5, 2.81. Separation of patients according to the respective median LDs resulted in differences in event-free survival (EFS; CP1: 21.1 vs. 9.1 months, p=0.0711; CP2: 14.2 vs. 9.3 months, p=0.0095; CP3: 30.9 vs. 13.5 months, p=0.0055; CP4: median not reached vs. 14.1 months, p<0.0001; CP5: median not reached vs. 22.5 months, p=0.0001) and overall survival (OS; CP3: median not reached vs. 21.6 months, p=0.0332; CP4: 90% vs. 53% at 2 years, p=0.0058). Cox analysis using the LDs at the different checkpoints as continuous variables confirmed the prognostic impact on EFS (CP2, p=0.002; CP3, p=0.0003; CP4, p<0.0001; CP5, p<0.0001) and revealed an impact also on OS (CP3, p=0.003; CP4, p=0.001; CP5, p=0.029). Cox regression analysis taking into consideration cytogenetics and age as covariates proved the independent prognostic impact of LD at checkpoints 2 to 5 on both EFS and OS with the exception of LD at checkpoint 2 and OS. In fact, LD at checkpoint 5 was the only parameter independently related to EFS and OS. These data suggest that quantification of MRD by MFC in AML results in powerful and independent prognostic parameters. In particular during the first year of treatment MRD levels provide important prognostic information. Clincal trials should use MRD-based stratification in order to assess the efficacy of early treatment intensification in high-risk AML patients.

scholarly journals Integrated information and measurement system for the diagnosis of acute leukemia and minimal residual disease based on computer microscopy, flow laser cytofluorimetry and artificial intelligence

2021 ◽  
Vol 2058 (1) ◽  
pp. 012033
Author(s):  
V G Nikitayev ◽  
A N Pronichev ◽  
N N Tupitsin ◽  
V Yu Selchuk ◽  
V V Dmitrieva ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Bone Marrow ◽  
Acute Leukemia ◽  
Minimal Residual Disease ◽  
Measurement System ◽  
Bone Marrow Cells ◽  
Residual Disease ◽  
Computer Microscopy ◽  
Minimal Residual ◽  
Integrated Information

Abstract The article considers a new integrated information and measurement system for the diagnosis of acute leukemia and minimal residual disease based on computer microscopy and flow laser cytometry. The system is based on combining the results of computer microscopy in the analysis of bone marrow preparations and the results of flow laser cytofluorimetry. A special feature of the system is the use of artificial intelligence technologies in the recognition of images of bone marrow cells in the computer microscopy subsystem. The work was the result of joint work of the Department of Computer Medical Systems of the National Research Nuclear University "MEPhI" and the Laboratory of Hematopoietic Immunology of the National Medical Research Center of Oncology named after N. N. Blokhin.

Flow Cytometric Immunophenotyping for Minimal Residual Disease Analysis in Multiple Myeloma

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 2711-2711
Author(s):  
Ritu Gupta ◽  
Archana Bhaskar ◽  
Paresh Jain ◽  
Atul Sharma ◽  
Lalit Kumar
Keyword(s):  
Bone Marrow ◽  
Minimal Residual Disease ◽  
Bone Marrow Aspirate ◽  
Plasma Cells ◽  
Bone Marrow Cells ◽  
Residual Disease ◽  
Protein Electrophoresis ◽  
Tumor Load ◽  
Total Bone Marrow ◽  
Minimal Residual

Abstract Recent studies using multi-parametric flow cytometry (MFC) have shown frequent immunophenotypic aberrations of plasma cells (PCs) and their utility in minimal residual disease (MRD) detection in multiple myeloma (MM). Presence of normal PCs and hemodilution of the bone marrow aspirate are important considerations in MRD assessment by MFC. The purpose of present study was to characterize PCs in MM to determine the incidence of aberrant antigen expression on myeloma PCs and its role in estimation of minimal residual disease. A total of 108 patients of MM were evaluated to study the immunophenotype of PCs and 37 patients for estimation of MRD using pre-titrated volumes of the following monoclonal antibodies: CD19 FITC, CD20 FITC, CD45 FITC, CD117 PE, CD56 PE, CD38 PE-Cy5.5, CD138 APC (BD Biosciences, San Jose, CA, USA), CD52 PE, Kappa (κ) FITC and Lambda (λ) PE (Serotec). CD38 and CD138 were added to all the tubes for specific identification of PCs. 2ml of bone marrow aspirate was collected from all the subjects as per the guidelines of the institute ethics committee, processed for immunophenotyping studies using standard whole blood lysis technique and analyzed with 4-color flow cytometry. At least two antigens were aberrantly expressed in all and three in 92.6% of MM with CD19 being most frequent followed by CD56, CD45, CD52, CD117 and CD20. Using aberrant immunophenotype for identification of neoplastic PCs, MRD by MFC was detectable in all the patients of MM with ≤5% PC on bone marrow smears. The neoplastic PCs as percentage of total bone marrow cells could not differentiate protein electrophoresis (PE) + from PE− samples (Figure 1A). Assuming that in a hemodiluted bone marrow aspirate both the neoplastic and normal PCs would be proportionately reduced and normal PCs would outnumber the neoplastic clone after successful therapy; when we analyzed the tumor load i.e. the neoplastic PC as percentage of total PCs, a cut-off of 50% neoplastic PCs of total PCs could differentiate PE + samples from PE− ones (Figure 1B). To conclude, MRD detection by aberrant antigen expression is useful and evaluation of tumor load i.e. neoplastic PCs as percentage of total PC may help in better assessment of response to therapy and circumvent the problem of hemodilution in MFC based MRD assays in MM. Figure 1: Tumor load i.e. neoplastic plasma cells (NPCs) as % of total PCs (A) & of total bone marrow cells (B) in samples evaluated for minimal residual disease. The NPCs constituted ≤50% of the total PCs in protein electrophoresis (PE) & immunofixation negative samples and &gt;60% of the total PCs in PE+ samples (B). Arrow indicates two cases which were PE- but positive on immunofixation and had relatively low numbers of neoplastic PCs (B) &lt;&gt; Figure 1:. Tumor load i.e. neoplastic plasma cells (NPCs) as % of total PCs (A) & of total bone marrow cells (B) in samples evaluated for minimal residual disease. The NPCs constituted ≤50% of the total PCs in protein electrophoresis (PE) & immunofixation negative samples and &gt;60% of the total PCs in PE+ samples (B). Arrow indicates two cases which were PE- but positive on immunofixation and had relatively low numbers of neoplastic PCs (B) &lt;&gt;

scholarly journals Classification of bone marrow cells in the diagnosis of acute lymphoblastic leukemia

2021 ◽  
Vol 2058 (1) ◽  
pp. 012043
Author(s):  
V G Nikitayev ◽  
A N Pronichev ◽  
N N Tupitsin ◽  
V Yu Selchuk ◽  
V V Dmitrieva ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Acute Lymphoblastic Leukemia ◽  
Bone Marrow Cells ◽  
Residual Disease ◽  
Lymphoblastic Leukemia ◽  
Automated Classification ◽  
Classification Methods ◽  
Minimal Residual ◽  
Marrow Cells

Abstract The paper presents approaches to automated classification of bone marrow cells in the diagnosis of acute lymphoblastic leukemia and minimal residual disease using image recognition procedures. The classification methods that show the best accuracy in the recognition of eight types of bone marrow cells were experimentally determined. Recommendations for their use are given.

Minimal Residual Disease by Next-Generation Sequencing: Pros and Cons

2016 ◽  
pp. e425-e430 ◽  
Author(s):  
Herve Avet-Loiseau
Keyword(s):  
Bone Marrow ◽  
Minimal Residual Disease ◽  
Bone Marrow Cells ◽  
Residual Disease ◽  
Meta Analysis ◽  
Event Free Survival ◽  
Free Survival ◽  
Pros And Cons ◽  
Generation Sequencing ◽  
Minimal Residual

The wealth of data recently generated highlights that minimal residual disease (MRD)–negative status can be achieved in a large proportion of patients. These studies, in addition to a meta-analysis, clearly suggest significant improvement in both event-free survival (EFS) and overall survival (OS) among those patients achieving MRD–negative status, especially with sensitivity of one cell in 1 million bone marrow cells. There is an evolving consensus that achieving MRD–negative status should become the ultimate goal of therapeutic intervention. Further future efforts should now be directed at determining how MRD status can be used to guide and personalize further therapy including type of consolidation and maintenance therapy.

scholarly journals Co-culture model of B-cell acute lymphoblastic leukemia recapitulates a transcription signature of chemotherapy-refractory minimal residual disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Stephanie L. Rellick ◽  
Gangqing Hu ◽  
Debra Piktel ◽  
Karen H. Martin ◽  
Werner J. Geldenhuys ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Acute Lymphoblastic Leukemia ◽  
B Cell ◽  
Tumor Cells ◽  
Minimal Residual Disease ◽  
Residual Disease ◽  
Lymphoblastic Leukemia ◽  
Adherent Cells ◽  
Cell Acute Lymphoblastic Leukemia ◽  
Minimal Residual

AbstractB-cell acute lymphoblastic leukemia (ALL) is characterized by accumulation of immature hematopoietic cells in the bone marrow, a well-established sanctuary site for leukemic cell survival during treatment. While standard of care treatment results in remission in most patients, a small population of patients will relapse, due to the presence of minimal residual disease (MRD) consisting of dormant, chemotherapy-resistant tumor cells. To interrogate this clinically relevant population of treatment refractory cells, we developed an in vitro cell model in which human ALL cells are grown in co-culture with human derived bone marrow stromal cells or osteoblasts. Within this co-culture, tumor cells are found in suspension, lightly attached to the top of the adherent cells, or buried under the adherent cells in a population that is phase dim (PD) by light microscopy. PD cells are dormant and chemotherapy-resistant, consistent with the population of cells that underlies MRD. In the current study, we characterized the transcriptional signature of PD cells by RNA-Seq, and these data were compared to a published expression data set derived from human MRD B-cell ALL patients. Our comparative analyses revealed that the PD cell population is markedly similar to the MRD expression patterns from the primary cells isolated from patients. We further identified genes and key signaling pathways that are common between the PD tumor cells from co-culture and patient derived MRD cells as potential therapeutic targets for future studies.

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