Acute Lymphoblastic Leukemia(ALL)is a fatal malignancy that is featured by the abnormal increase of immature lymphocytes in blood or bone marrow.Early prognosis of ALL is indispensable for the effectual remediation of...Acute Lymphoblastic Leukemia(ALL)is a fatal malignancy that is featured by the abnormal increase of immature lymphocytes in blood or bone marrow.Early prognosis of ALL is indispensable for the effectual remediation of this disease.Initial screening of ALL is conducted through manual examination of stained blood smear microscopic images,a process which is time-consuming and prone to errors.Therefore,many deep learning-based computer-aided diagnosis(CAD)systems have been established to automatically diagnose ALL.This paper proposes a novel hybrid deep learning system for ALL diagnosis in blood smear images.The introduced system integrates the proficiency of autoencoder networks in feature representational learning in latent space with the superior feature extraction capability of standard pretrained convolutional neural networks(CNNs)to identify the existence of ALL in blood smears.An augmented set of deep image features are formed from the features extracted by GoogleNet and Inception-v3 CNNs from a hybrid dataset of microscopic blood smear images.A sparse autoencoder network is designed to create an abstract set of significant latent features from the enlarged image feature set.The latent features are used to perform image classification using Support Vector Machine(SVM)classifier.The obtained results show that the latent features improve the classification performance of the proposed ALL diagnosis system over the original image features.Moreover,the classification performance of the system with various sizes of the latent feature set is evaluated.The retrieved results reveal that the introduced ALL diagnosis system superiorly compete the state of the art.展开更多
Infection of leukemia in humans causes many complications in its later stages.It impairs bone marrow’s ability to produce blood.Morphological diagnosis of human blood cells is a well-known and well-proven technique f...Infection of leukemia in humans causes many complications in its later stages.It impairs bone marrow’s ability to produce blood.Morphological diagnosis of human blood cells is a well-known and well-proven technique for diagnosis in this case.The binary classification is employed to distinguish between normal and leukemiainfected cells.In addition,various subtypes of leukemia require different treatments.These sub-classes must also be detected to obtain an accurate diagnosis of the type of leukemia.This entails using multi-class classification to determine the leukemia subtype.This is usually done using a microscopic examination of these blood cells.Due to the requirement of a trained pathologist,the decision process is critical,which leads to the development of an automated software framework for diagnosis.Researchers utilized state-of-the-art machine learning approaches,such as Support Vector Machine(SVM),Random Forest(RF),Na飗e Bayes,K-Nearest Neighbor(KNN),and others,to provide limited accuracies of classification.More advanced deep-learning methods are also utilized.Due to constrained dataset sizes,these approaches result in over-fitting,reducing their outstanding performances.This study introduces a deep learning-machine learning combined approach for leukemia diagnosis.It uses deep transfer learning frameworks to extract and classify features using state-of-the-artmachine learning classifiers.The transfer learning frameworks such as VGGNet,Xception,InceptionResV2,Densenet,and ResNet are employed as feature extractors.The extracted features are given to RF and XGBoost classifiers for the binary and multi-class classification of leukemia cells.For the experimentation,a very popular ALL-IDB dataset is used,approaching a maximum accuracy of 100%.A private real images dataset with three subclasses of leukemia images,including Acute Myloid Leukemia(AML),Chronic Lymphocytic Leukemia(CLL),and Chronic Myloid Leukemia(CML),is also employed to generalize the system.This dataset achieves an impressive multi-class classification accuracy of 97.08%.The proposed approach is robust and generalized by a standardized dataset and the real image dataset with a limited sample size(520 images).Hence,this method can be explored further for leukemia diagnosis having a limited number of dataset samples.展开更多
Acute leukemia (AL) is a malignant disease of the bone marrow in which hematopoietic precursors are arrested in an early stage of development. The diagnosis of leukemia and lymphomas, beyond morphology, is limited in ...Acute leukemia (AL) is a malignant disease of the bone marrow in which hematopoietic precursors are arrested in an early stage of development. The diagnosis of leukemia and lymphomas, beyond morphology, is limited in low-resource countries including Kenya. Morphological diagnosis includes Cytological and Histological assessment of blood, bone marrow aspirates and tissues on suspected Acute leukemia patients. The World Health Organization (WHO, 2016) international guidelines on Acute leukemia diagnosis recommend that cytogenetic analysis, appropriate molecular genetics, Fluorescent in situ Hybridization (FISH) testing, and flow cytometric immuno-phenotyping should be done in addition to a morphologic assessment of Acute Leukemia. In facilities where resources are relatively available, immunophenotypic and genetic features have resulted not only in providing a more accurate leukemia diagnosis but also in identifying antigens or genes that can then be targeted for therapy. This article will look at the gaps in the diagnosis of Acute leukemia in low-resource settings like Kenya and opportunities available to improve diagnosis.展开更多
In the present study, 98 cases of acute leukemias (AL) were diagnosed and classified based on morphologic, immunologic and cytogenetic (MIC) features to assess their diagnostic value in AL. The results showed that: th...In the present study, 98 cases of acute leukemias (AL) were diagnosed and classified based on morphologic, immunologic and cytogenetic (MIC) features to assess their diagnostic value in AL. The results showed that: the conformity rate of cytomorphologic/cytochemical classification with MIC classification was 90.8%. For ALL, the conformity rate of immunologic classification with MIC classification was 95.6% while it was only 70.8% for AML. Of the 48 AML, 10 expressed lymphoid-lineage-associated antigens and 8 of 43 ALL expressed myeloid-lineage-associated antigens. Seven cases were diagnosed as hybrid acute leukemia according to Catovsky's scoring criterion. The clonal chromosomal aberrations were found in 70 cases, of them 46 cases showed characteristic changes including t(9; 22), t(4; 11), t(11; 14), t(8; 12), t(8; 14), 6q-, 9p- and t(15; 17), t(8; 21), inv(16), etc. These data suggested that MIC classification of acute leukemias could provide more diagnostic and biologic information than traditional FAB classification.展开更多
In this study,we compared the efficacy of mitoxantrone in combination with intermediate-dose cytarabine（HAM） with that of high-dose cytarabine alone（Hi DAC） as consolidation regimens in non-acute promyelocytic leu...In this study,we compared the efficacy of mitoxantrone in combination with intermediate-dose cytarabine（HAM） with that of high-dose cytarabine alone（Hi DAC） as consolidation regimens in non-acute promyelocytic leukemia（APL） acute myeloid leukemia patients with favorable and intermediate cytogenetics.A total of 62 patients from Shenzhen People＇s Hospital were enrolled in this study.All patients enrolled received standard induction chemotherapy and achieved the first complete remission（CR1）.In these patients,24 received Hi DAC and 38 received HAM as consolidation.The median relapse free survival（RFS） and overall survival（OS） were similar between these two consolidation regimens.Even in subgroup analysis according to risk stratification,the combination regimen conferred no benefit in longterm outcome in patients with favorable or intermediate cytogenetics.However,in patients receiving HAM regimen,the lowest neutrophil count was lower,neutropenic period longer,neutropenic fever rate higher,and more platelet transfusion support was required.HAM group also tended to have higher rate of sepsis than Hi DAC group.According to our results,we suggest that combination treatment with mitoxantrone and intermediate-dose cytarabine has limited value as compared to Hi DAC,even in young non-APL AML patients with favorable and intermediate cytogenetics.展开更多
<strong>Background</strong><strong>:</strong> Chronic Myeloid Leukemia (CML) is a myeloproliferative blood neoplasia, characterized by the presence of a translocation between chromosomes 9 and ...<strong>Background</strong><strong>:</strong> Chronic Myeloid Leukemia (CML) is a myeloproliferative blood neoplasia, characterized by the presence of a translocation between chromosomes 9 and 22 leading to the formation of the Philadelphia chromosome. Data on the biological profile of patients with CML at diagnosis are still lacking in sub-Saharan Africa, particularly in Cameroon. <strong>Methods</strong><strong>:</strong> A cross-sectional study was carried out from January 2001 to July 2016 among patients recently diagnosed with CML at the Yaounde University Teaching Hospital, the Yaoundé Central Hospital and the Yaoundé General Hospital. Analyzed variables included socio-demographic, clinical presentation, the diagnosis means, biological parameters (hematological and biochemical). Sampling was consecutive. <strong>Results</strong><strong>:</strong> We included 132 (76 males) patients with CML with a median age of 39.2 years at diagnosis. The 31 - 45 years age group was the most represented, with 40.9% of the study population. A risk factor was found in only 5 (3.8%) of patients. Clinical manifestations were recorded in only 27 (20.45%) patients, with fatigue being the commonest (10.6%). Almost all patients (128, 96.9%) have performed the karyotype while 22 (16.7%) have performed fluorescence in situ hybridization (FISH) and 4 (3.0%) the PCR. At diagnosis, 66% of the patients were in the chronic phase (CP), 11.3% in accelerated phase (AP), and 22.7% in blast crisis (BC). All patients presented hyperleukocytosis, with a white blood cell mean of 128,362/mm3. Anemia was common (77.3%), usually moderate (61.4%). Thrombocytopenia was rare (8.3%), as far as basophilia (1.2%). Among those patients, mean values of creatinine, Glutamic pyruvate transaminase (GPT) and glycemia were normal while activated partial thromboplastin time (APTT), prothrombin time (PT), plasma uric acid level, gamma glutamic transferase (GGT), lactate dehydrogenase (LDH), and inflammatory parameters (ESR and CRP) were increased. <strong>Conclusion</strong><strong>:</strong> Patients with CML presented at their diagnosis hyperleukocytosis and anemia as hematological clues. Other biological anomalies include increased signs of cellular destruction (plasma uric acid level, LDH), coagulation perturbation and inflammatory syndrome. The chronic phase of the disease was common.展开更多
BACKGROUND Persistent left superior vena cava(PLSVC)is the most common venous system variant.The clinical characteristics and amniotic fluid cytogenetics of fetuses with PLSVC remain to be further explored.AIM To deve...BACKGROUND Persistent left superior vena cava(PLSVC)is the most common venous system variant.The clinical characteristics and amniotic fluid cytogenetics of fetuses with PLSVC remain to be further explored.AIM To develop reliable prenatal diagnostic recommendations through integrated analysis of the clinical characteristics of fetuses with PLSVC.METHODS Cases of PLSVC diagnosed using prenatal ultrasonography between September 2019 and November 2022 were retrospectively studied.The clinical characteristics of the pregnant women,ultrasonic imaging information,gestational age at diagnosis,pregnancy outcomes,and amniocentesis results were summarized and analyzed using categorical statistics and the chi-square test or Fisher’s exact test.RESULTS Of the 97 cases diagnosed by prenatal ultrasound,49(50.5%)had isolated PLSVC and 48(49.5%)had other structural abnormalities.The differences in pregnancy outcomes and amniocentesis conditions between the two groups were statistically significant(P<0.05).No significant differences were identified between the two groups in terms of advanced maternal age and gestational age(P>0.05).According to the results of the classification statistics,the most common intrac-ardiac abnormality was a ventricular septal defect and the most common extrac-ardiac abnormality was a single umbilical artery.In the subgroup analysis,the concurrent combination of intra-and extracardiac structural abnormalities was a risk factor for adverse pregnancy outcomes(odds ratio>1,P<0.05).Additional-ly,all abnormal cytogenetic findings on amniocentesis were observed in the comorbidity group.One case was diagnosed with 21-trisomy and six cases was diagnosed with chromosome segment duplication.CONCLUSION Examination for other structural abnormalities is strongly recommended when PLSVC is diagnosed.Poorer pregnancy outcomes and increased amniocentesis were observed in PLSVC cases with other structural abnor-malities.Amniotic fluid cytogenetics of fetuses is recommended for PLSVC with other structural abnormalities.展开更多
Immunophenotype is critical for diagnosing common B-cell acute lymphoblastic leukemia (common ALL) and detecting minimal residual disease. We developed a protocol to explore the immunophenotypic profiles of common ALL...Immunophenotype is critical for diagnosing common B-cell acute lymphoblastic leukemia (common ALL) and detecting minimal residual disease. We developed a protocol to explore the immunophenotypic profiles of common ALL based on the expression levels of the antigens associated with B lymphoid development, including IL-7Rα (CD127), cytoplasmic CD79a (cCD79a), CD19, VpreB (CD179a), and sIgM, which are successive and essential for progression of B cells along their developmental pathway. Analysis of the immunophenotypes of 48 common ALL cases showed that the immunophenotypic patterns were highly heterogeneous, with the leukemic cell population differing from case to case. Through the comprehensive analysis of immunophenotypic patterns, the profiles of patient-specific composite leukemia cell populations could provide detailed information helpful for the diagnosis, therapeutic monitoring, and individualized therapies for common ALL.展开更多
One case of acute megakaryoblastic leukemia （AMKL） with trisomy 21,trisomy 14 and unmutated GATA1 gene in a phenotypically normal girl was reported.The patient experienced transient myelodysplasia before the onset o...One case of acute megakaryoblastic leukemia （AMKL） with trisomy 21,trisomy 14 and unmutated GATA1 gene in a phenotypically normal girl was reported.The patient experienced transient myelodysplasia before the onset of AMKL.The bone marrow blasts manifested typical morphology of megakaryoblast both by the May-Giemsa staining and under the electronic microscopy.Leukemic cells were positive for CD13,CD33,CD117,CD56,CD38,CD41 and CD61 in flow cytometry analysis.Cytogenetic study showed karyotype of 48,XX,＋14,＋21 in 40% metaphases.Known mutations of GATA1 gene in Down syndrome or acquired trisomy 21 were not detected in this case.展开更多
文摘Acute Lymphoblastic Leukemia(ALL)is a fatal malignancy that is featured by the abnormal increase of immature lymphocytes in blood or bone marrow.Early prognosis of ALL is indispensable for the effectual remediation of this disease.Initial screening of ALL is conducted through manual examination of stained blood smear microscopic images,a process which is time-consuming and prone to errors.Therefore,many deep learning-based computer-aided diagnosis(CAD)systems have been established to automatically diagnose ALL.This paper proposes a novel hybrid deep learning system for ALL diagnosis in blood smear images.The introduced system integrates the proficiency of autoencoder networks in feature representational learning in latent space with the superior feature extraction capability of standard pretrained convolutional neural networks(CNNs)to identify the existence of ALL in blood smears.An augmented set of deep image features are formed from the features extracted by GoogleNet and Inception-v3 CNNs from a hybrid dataset of microscopic blood smear images.A sparse autoencoder network is designed to create an abstract set of significant latent features from the enlarged image feature set.The latent features are used to perform image classification using Support Vector Machine(SVM)classifier.The obtained results show that the latent features improve the classification performance of the proposed ALL diagnosis system over the original image features.Moreover,the classification performance of the system with various sizes of the latent feature set is evaluated.The retrieved results reveal that the introduced ALL diagnosis system superiorly compete the state of the art.
基金supported by the Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS),the University of Technology Sydney,the Ministry of Education of the Republic of Korea,and the National Research Foundation of Korea (NRF-2023R1A2C1007742)in part by the Researchers Supporting Project Number RSP-2023/14,King Saud University。
文摘Infection of leukemia in humans causes many complications in its later stages.It impairs bone marrow’s ability to produce blood.Morphological diagnosis of human blood cells is a well-known and well-proven technique for diagnosis in this case.The binary classification is employed to distinguish between normal and leukemiainfected cells.In addition,various subtypes of leukemia require different treatments.These sub-classes must also be detected to obtain an accurate diagnosis of the type of leukemia.This entails using multi-class classification to determine the leukemia subtype.This is usually done using a microscopic examination of these blood cells.Due to the requirement of a trained pathologist,the decision process is critical,which leads to the development of an automated software framework for diagnosis.Researchers utilized state-of-the-art machine learning approaches,such as Support Vector Machine(SVM),Random Forest(RF),Na飗e Bayes,K-Nearest Neighbor(KNN),and others,to provide limited accuracies of classification.More advanced deep-learning methods are also utilized.Due to constrained dataset sizes,these approaches result in over-fitting,reducing their outstanding performances.This study introduces a deep learning-machine learning combined approach for leukemia diagnosis.It uses deep transfer learning frameworks to extract and classify features using state-of-the-artmachine learning classifiers.The transfer learning frameworks such as VGGNet,Xception,InceptionResV2,Densenet,and ResNet are employed as feature extractors.The extracted features are given to RF and XGBoost classifiers for the binary and multi-class classification of leukemia cells.For the experimentation,a very popular ALL-IDB dataset is used,approaching a maximum accuracy of 100%.A private real images dataset with three subclasses of leukemia images,including Acute Myloid Leukemia(AML),Chronic Lymphocytic Leukemia(CLL),and Chronic Myloid Leukemia(CML),is also employed to generalize the system.This dataset achieves an impressive multi-class classification accuracy of 97.08%.The proposed approach is robust and generalized by a standardized dataset and the real image dataset with a limited sample size(520 images).Hence,this method can be explored further for leukemia diagnosis having a limited number of dataset samples.
文摘Acute leukemia (AL) is a malignant disease of the bone marrow in which hematopoietic precursors are arrested in an early stage of development. The diagnosis of leukemia and lymphomas, beyond morphology, is limited in low-resource countries including Kenya. Morphological diagnosis includes Cytological and Histological assessment of blood, bone marrow aspirates and tissues on suspected Acute leukemia patients. The World Health Organization (WHO, 2016) international guidelines on Acute leukemia diagnosis recommend that cytogenetic analysis, appropriate molecular genetics, Fluorescent in situ Hybridization (FISH) testing, and flow cytometric immuno-phenotyping should be done in addition to a morphologic assessment of Acute Leukemia. In facilities where resources are relatively available, immunophenotypic and genetic features have resulted not only in providing a more accurate leukemia diagnosis but also in identifying antigens or genes that can then be targeted for therapy. This article will look at the gaps in the diagnosis of Acute leukemia in low-resource settings like Kenya and opportunities available to improve diagnosis.
文摘In the present study, 98 cases of acute leukemias (AL) were diagnosed and classified based on morphologic, immunologic and cytogenetic (MIC) features to assess their diagnostic value in AL. The results showed that: the conformity rate of cytomorphologic/cytochemical classification with MIC classification was 90.8%. For ALL, the conformity rate of immunologic classification with MIC classification was 95.6% while it was only 70.8% for AML. Of the 48 AML, 10 expressed lymphoid-lineage-associated antigens and 8 of 43 ALL expressed myeloid-lineage-associated antigens. Seven cases were diagnosed as hybrid acute leukemia according to Catovsky's scoring criterion. The clonal chromosomal aberrations were found in 70 cases, of them 46 cases showed characteristic changes including t(9; 22), t(4; 11), t(11; 14), t(8; 12), t(8; 14), 6q-, 9p- and t(15; 17), t(8; 21), inv(16), etc. These data suggested that MIC classification of acute leukemias could provide more diagnostic and biologic information than traditional FAB classification.
基金supported by grants from the Basic Research Project of Shenzhen Science and Technology Program(No.JYCJ20150403101146307,No.JCYJ20150403101028195 and No.JCYJ20160422145031770)the National Natural Science Foundation of China(No.81600168)
文摘In this study,we compared the efficacy of mitoxantrone in combination with intermediate-dose cytarabine（HAM） with that of high-dose cytarabine alone（Hi DAC） as consolidation regimens in non-acute promyelocytic leukemia（APL） acute myeloid leukemia patients with favorable and intermediate cytogenetics.A total of 62 patients from Shenzhen People＇s Hospital were enrolled in this study.All patients enrolled received standard induction chemotherapy and achieved the first complete remission（CR1）.In these patients,24 received Hi DAC and 38 received HAM as consolidation.The median relapse free survival（RFS） and overall survival（OS） were similar between these two consolidation regimens.Even in subgroup analysis according to risk stratification,the combination regimen conferred no benefit in longterm outcome in patients with favorable or intermediate cytogenetics.However,in patients receiving HAM regimen,the lowest neutrophil count was lower,neutropenic period longer,neutropenic fever rate higher,and more platelet transfusion support was required.HAM group also tended to have higher rate of sepsis than Hi DAC group.According to our results,we suggest that combination treatment with mitoxantrone and intermediate-dose cytarabine has limited value as compared to Hi DAC,even in young non-APL AML patients with favorable and intermediate cytogenetics.
文摘<strong>Background</strong><strong>:</strong> Chronic Myeloid Leukemia (CML) is a myeloproliferative blood neoplasia, characterized by the presence of a translocation between chromosomes 9 and 22 leading to the formation of the Philadelphia chromosome. Data on the biological profile of patients with CML at diagnosis are still lacking in sub-Saharan Africa, particularly in Cameroon. <strong>Methods</strong><strong>:</strong> A cross-sectional study was carried out from January 2001 to July 2016 among patients recently diagnosed with CML at the Yaounde University Teaching Hospital, the Yaoundé Central Hospital and the Yaoundé General Hospital. Analyzed variables included socio-demographic, clinical presentation, the diagnosis means, biological parameters (hematological and biochemical). Sampling was consecutive. <strong>Results</strong><strong>:</strong> We included 132 (76 males) patients with CML with a median age of 39.2 years at diagnosis. The 31 - 45 years age group was the most represented, with 40.9% of the study population. A risk factor was found in only 5 (3.8%) of patients. Clinical manifestations were recorded in only 27 (20.45%) patients, with fatigue being the commonest (10.6%). Almost all patients (128, 96.9%) have performed the karyotype while 22 (16.7%) have performed fluorescence in situ hybridization (FISH) and 4 (3.0%) the PCR. At diagnosis, 66% of the patients were in the chronic phase (CP), 11.3% in accelerated phase (AP), and 22.7% in blast crisis (BC). All patients presented hyperleukocytosis, with a white blood cell mean of 128,362/mm3. Anemia was common (77.3%), usually moderate (61.4%). Thrombocytopenia was rare (8.3%), as far as basophilia (1.2%). Among those patients, mean values of creatinine, Glutamic pyruvate transaminase (GPT) and glycemia were normal while activated partial thromboplastin time (APTT), prothrombin time (PT), plasma uric acid level, gamma glutamic transferase (GGT), lactate dehydrogenase (LDH), and inflammatory parameters (ESR and CRP) were increased. <strong>Conclusion</strong><strong>:</strong> Patients with CML presented at their diagnosis hyperleukocytosis and anemia as hematological clues. Other biological anomalies include increased signs of cellular destruction (plasma uric acid level, LDH), coagulation perturbation and inflammatory syndrome. The chronic phase of the disease was common.
文摘BACKGROUND Persistent left superior vena cava(PLSVC)is the most common venous system variant.The clinical characteristics and amniotic fluid cytogenetics of fetuses with PLSVC remain to be further explored.AIM To develop reliable prenatal diagnostic recommendations through integrated analysis of the clinical characteristics of fetuses with PLSVC.METHODS Cases of PLSVC diagnosed using prenatal ultrasonography between September 2019 and November 2022 were retrospectively studied.The clinical characteristics of the pregnant women,ultrasonic imaging information,gestational age at diagnosis,pregnancy outcomes,and amniocentesis results were summarized and analyzed using categorical statistics and the chi-square test or Fisher’s exact test.RESULTS Of the 97 cases diagnosed by prenatal ultrasound,49(50.5%)had isolated PLSVC and 48(49.5%)had other structural abnormalities.The differences in pregnancy outcomes and amniocentesis conditions between the two groups were statistically significant(P<0.05).No significant differences were identified between the two groups in terms of advanced maternal age and gestational age(P>0.05).According to the results of the classification statistics,the most common intrac-ardiac abnormality was a ventricular septal defect and the most common extrac-ardiac abnormality was a single umbilical artery.In the subgroup analysis,the concurrent combination of intra-and extracardiac structural abnormalities was a risk factor for adverse pregnancy outcomes(odds ratio>1,P<0.05).Additional-ly,all abnormal cytogenetic findings on amniocentesis were observed in the comorbidity group.One case was diagnosed with 21-trisomy and six cases was diagnosed with chromosome segment duplication.CONCLUSION Examination for other structural abnormalities is strongly recommended when PLSVC is diagnosed.Poorer pregnancy outcomes and increased amniocentesis were observed in PLSVC cases with other structural abnor-malities.Amniotic fluid cytogenetics of fetuses is recommended for PLSVC with other structural abnormalities.
基金supported by grants from the National Basic Research Program of China (No.2007CB947802)the Natural Science Foundation of China to H.X. (No.30771228) and to X.M. (No.30771227)
文摘Immunophenotype is critical for diagnosing common B-cell acute lymphoblastic leukemia (common ALL) and detecting minimal residual disease. We developed a protocol to explore the immunophenotypic profiles of common ALL based on the expression levels of the antigens associated with B lymphoid development, including IL-7Rα (CD127), cytoplasmic CD79a (cCD79a), CD19, VpreB (CD179a), and sIgM, which are successive and essential for progression of B cells along their developmental pathway. Analysis of the immunophenotypes of 48 common ALL cases showed that the immunophenotypic patterns were highly heterogeneous, with the leukemic cell population differing from case to case. Through the comprehensive analysis of immunophenotypic patterns, the profiles of patient-specific composite leukemia cell populations could provide detailed information helpful for the diagnosis, therapeutic monitoring, and individualized therapies for common ALL.
文摘One case of acute megakaryoblastic leukemia （AMKL） with trisomy 21,trisomy 14 and unmutated GATA1 gene in a phenotypically normal girl was reported.The patient experienced transient myelodysplasia before the onset of AMKL.The bone marrow blasts manifested typical morphology of megakaryoblast both by the May-Giemsa staining and under the electronic microscopy.Leukemic cells were positive for CD13,CD33,CD117,CD56,CD38,CD41 and CD61 in flow cytometry analysis.Cytogenetic study showed karyotype of 48,XX,＋14,＋21 in 40% metaphases.Known mutations of GATA1 gene in Down syndrome or acquired trisomy 21 were not detected in this case.
