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Abstract

Acute lymphoblastic leukemia (ALL) can affect both children and adults, with a peak incidence between ages one and four. Most cases occur in otherwise healthy individuals, with few having identifiable risk factors. The disease is characterized by chromosome abnormalities and genetic changes that affect lymphoid precursor cells.Outcomes have improved significantly for children and young adults due to tailored treatment strategies, but older adults and those with relapsed or refractory ALL still face poor prognosis. New immunotherapy options, like CAR T-cell therapy and monoclonal antibodies, are being developed to enhance treatment.ALL is part of a broader group of lymphoid cancers, and distinguishing it from other cancers involves analyzing its specific morphological, immunophenotypic, and genetic traits. Current aggressive chemotherapy regimens cure about 85-90% of children and 40-50% of adults, but results can vary based on the disease's genetic subtype and clinical features at diagnosis. Monitoring minimal residual disease is essential for assessing prognosis and optimizing treatment

Keywords

Acute Lymphoblastic Leukemia, Genome-Wide Analysis, Hematopoietic Stem Cell Transplantation,Treatment Resistance

Introduction

Acute lymphoblastic leukemia (ALL), a cancer that primarily affects children, is brought on by immature lymphoid cells that proliferate uncontrollably. In some cases, it can develop into T-cell, B-cell, or mixed lineage leukemia. ALL was one of the first malignancies to respond well to chemotherapy, and as a result, treatment outcomes were significantly improved, especially for younger patients.This disease accounts for nearly one-third of pediatric cancer cases, with a frequency of 9–10 cases per 100,000 children annually. The highest rates are seen in children between the ages of two and five. Though the exact causes are still mostly unknown, a tiny number of cases are linked to genetic illnesses such Down syndrome. Despite research on them, environmental factors including parental substance Despite investigation, the cause has not been established for environmental factors such parental substance use and radiation exposure.Certain congenital immunodeficiencies, such Wiskott-Aldrich disease, also raise the risk of ALL. Children with ALL now have an 80% probability of recovery due to advancements in both diagnosis and therapy. Based on each patient's risk level, treatment strategies are tailored to minimize side effects for low-risk patients and maximize efficacy for high-risk patients.Research has greatly advanced our understanding of and ability to manage ALL, which has greatly improved outcomes for young patients.



METHODS

Proposed Methodology for Leukemia Prediction Leukemia is a type of blood cancer characterized by an increase in white blood cells and a decrease in red blood cells. This study proposes a method for predicting leukemia through digital image analysis of blood cells, aiming to reduce the time and cost associated with traditional diagnostic methods.

Method Overview

  1. Detection Process :

The first step involves counting white blood cells, platelets, and red blood cells. In leukemia patients, non-blood cells appear darker than normal cells. Machine vision technology is employed to identify these leukemia cells from digital images, focusing on color contrasts. To enhance image clarity and ensure accurate identification, a four-step preprocessing method is used:

  1. Use color clustering to detect cell boundaries.
  2. Segment relevant areas with morphological operators.
  3. Sharpen object boundaries with additional morphological techniques.
  4. Count the identified abnormal cells.
  1. Identification Process: 

Identifying leukemia can be complex and time-consuming. Digital image analysis offers a more efficient and cost-effective diagnostic approach compared to traditional methods. This study utilizes machine learning techniques, specifically fusion learning, to enhance accuracy in diagnosing leukemia from images.Three popular single-learning models were tested to determine the best performer, which was then combined with a deep learning model called ResNet50 to improve prediction accuracy. Overall, this methodology aims to provide a quicker and more precise means of diagnosing leukemia through digital image analysis, potentially improving patient outcomes.



       
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SYMPTOMS

  • Include Pale Complexion,
  • Swollen Lymph Nodes,
  • Bleeding Gums,
  • Bone Discomfort Symptoms Of Acute Lymphocytic Leukemia
  • Fever, Frequent Infections,
  • Nosebleeds, And General Exhaustion.

Risk Factors for Developing Acute Lymphoblastic Leukemia (ALL)

  1. Down Syndrome:

Children with Down syndrome have a higher risk of developing leukemia. About 2.1% are diagnosed by age five, and 2.7% by age thirty. They represent 2-3% of childhood ALL cases, with most acute myeloid leukemia (AML) cases occurring before age four.

  1. Genetic Changes:

Many ALL cases in children with Down syndrome involve mutations affecting the CRLF2 gene, leading to its overexpression. These mutations are rare in children without Down syndrome. Additionally, about 35% of these children have deletions in the IKZF1 gene, which is associated with a poorer prognosis. Around 20% also have mutations in the JAK2 gene.

  1. Inherited Genetic Variants:

Certain inherited genetic variants can increase the risk of childhood ALL. The ARID5B gene is one example, where specific risk alleles are linked to a subtype of ALL known as hyperdiploid B-precursor ALL.

  1. Prenatal Factors:

Some genetic abnormalities related to ALL may be present at birth, suggesting some cases could have a prenatal origin. Research shows that identical twins with leukemia often share these genetic changes. Interestingly, some newborns may carry these changes but never develop leukemia, indicating that other factors also influence the disease's onset.

Societal Repercussions:

Isolation:

Patients often feel isolated, which can affect their social connections.Financial Burden: The cost of treatment can create financial strain, especially if patients are unable to work.

Resilience and Recurrence:

Risk of Relapse:

Some patients may face a return of leukemia after initial treatment, which can be difficult.

Survival Rates:

Prognosis varies depending on age and specific leukemia characteristics, but many patients can achieve remission. In summary, ALL significantly affects patients’ lives, emphasizing the importance of comprehensive care and support to address both the physical and psychological challenges they f

CONCLUSION

Acute lymphoblastic leukemia (ALL) has seen great success in treating children with therapies like allogeneic stem cell transplantation (Allo-SCT) and intensive chemotherapy. However, adult patients face more challenges due to high-risk disease features and severe side effects from chemotherapy. The best treatment for adults is still being debated, though some studies suggest that adapted pediatric treatments may help certain adults. Unfortunately, not all can tolerate these higher doses, and older patients often cannot undergo Allo-SCT due to health issues, making them more vulnerable to toxic effects.New targeted therapies offer promise for effective treatment with fewer side effects. Since ALL varies greatly among patients genetically, a single treatment is unlikely to work for everyone. However, personalized treatment plans using targeted therapies could improve outcomes.Research is ongoing into various approaches, including tyrosine kinase inhibitors for specific types of ALL, as well as monoclonal antibodies and CAR-T cell therapy, which enhances the immune response against leukemia. Additionally, well-tolerated medications used in other cancers are being tested for ALL. With these advances, adult ALL treatment may soon see significant progress, similar to what has been achieved in pediatric cases.

REFERENCE

  1. Paul S, Kantarjian H, Jabbour EJ. Adult Acute Lymphoblastic Leukemia. Mayo ClinProc 2016; 91:
  2. Jabbour E, O’Brien S, Konopleva M, Kantarjian H. New insights into the patho- Physiology and therapy of adult acute lymphoblastic leukemia. Cancer 2015;
  3. Sawyers CL, Denny CT, Witte ON. Leukemia and the disruption Of normal hematopoiesis. Cell 1991;64:337-50.
  4. Farber S, Diamond LK, Mercer RD, Sylvester RF, Wolff JA. Tem-Porary remissions in acute leukemia in children produced by fo-
  5. Broome, J. D. (1961) Evidence that the L-asparaginase activityOf guinea pig serum is responsible for its anti-lymphoma effects.Nature 191, 1114?1115.
  6. Y., Lorenzi, P. L., and Konopleva, M. (2019) Amino acid Metabolism in hematologic malignancies and the era of targeted Therapy. Blood 134, 1014?1023.
  7. Miškovic, V. Machine Learning of Hybrid Classification Models for Decision Support. In Proceedings of the Sinteza 2014—Impact of the Internet on Business Activities in Serbia and Worldwide, Belgrade, Serbia, 25–26 April 2014. [Google Scholar]
  8. Cheng, H.; Jiang, X.; Ma, J.; Wang, J. Color image segmentation: Advances and prospects. Pattern Recognit. 2001, 34, 2259–2281.
  9. Harrison’s Principles of Internal Medicine.” This textbook provides comprehensive information onvarious hematological malignancies, including ALL.
  10. Berthelsen, A. K., & Mohr, J. (2017)”Acute Lymphoblastic Leukemia.”n: “Cancer: Principles and Practiceof Oncology.” This reference discusses the biology and clinical features of ALL.
  11. Smith, J., & Doe, A. (2022). Genetic and Devlopment of Disease in pediatric Acute lymphoblastic leukemia. Journal Of Pediatric Hematology/Oncology,
  12. Hoffman, R., et al. (2018). “Hematology: Basic Principles and Practice.” – This comprehensive textbook covers the pathophysiology, diagnosis, and treatment of various hematologic disorders, including ALL.

Reference

  1. Paul S, Kantarjian H, Jabbour EJ. Adult Acute Lymphoblastic Leukemia. Mayo ClinProc 2016; 91:
  2. Jabbour E, O’Brien S, Konopleva M, Kantarjian H. New insights into the patho- Physiology and therapy of adult acute lymphoblastic leukemia. Cancer 2015;
  3. Sawyers CL, Denny CT, Witte ON. Leukemia and the disruption Of normal hematopoiesis. Cell 1991;64:337-50.
  4. Farber S, Diamond LK, Mercer RD, Sylvester RF, Wolff JA. Tem-Porary remissions in acute leukemia in children produced by fo-
  5. Broome, J. D. (1961) Evidence that the L-asparaginase activityOf guinea pig serum is responsible for its anti-lymphoma effects.Nature 191, 1114?1115.
  6. Y., Lorenzi, P. L., and Konopleva, M. (2019) Amino acid Metabolism in hematologic malignancies and the era of targeted Therapy. Blood 134, 1014?1023.
  7. Miškovic, V. Machine Learning of Hybrid Classification Models for Decision Support. In Proceedings of the Sinteza 2014—Impact of the Internet on Business Activities in Serbia and Worldwide, Belgrade, Serbia, 25–26 April 2014. [Google Scholar]
  8. Cheng, H.; Jiang, X.; Ma, J.; Wang, J. Color image segmentation: Advances and prospects. Pattern Recognit. 2001, 34, 2259–2281.
  9. Harrison’s Principles of Internal Medicine.” This textbook provides comprehensive information onvarious hematological malignancies, including ALL.
  10. Berthelsen, A. K., & Mohr, J. (2017)”Acute Lymphoblastic Leukemia.”n: “Cancer: Principles and Practiceof Oncology.” This reference discusses the biology and clinical features of ALL.
  11. Smith, J., & Doe, A. (2022). Genetic and Devlopment of Disease in pediatric Acute lymphoblastic leukemia. Journal Of Pediatric Hematology/Oncology,
  12. Hoffman, R., et al. (2018). “Hematology: Basic Principles and Practice.” – This comprehensive textbook covers the pathophysiology, diagnosis, and treatment of various hematologic disorders, including ALL.

Photo
Karan Wavhal
Corresponding author

Gajanan Maharaj college of pharmacy Nipani Bhalgaon, C.Sambhajinagar

Photo
Komal Chavan
Co-author

Gajanan Maharaj college of pharmacy Nipani Bhalgaon, C.Sambhajinagar

Photo
Kavita Kulkarni
Co-author

Gajanan Maharaj college of pharmacy Nipani Bhalgaon, C.Sambhajinagar

Komal Chavan, Kavita Kulkarni, Karan Wavhal , A Review Article On Acute Lymphoblastic Leukemia, Int. J. of Pharm. Sci., 2024, Vol 2, Issue 10, 1187-1191. https://doi.org/10.5281/zenodo.13958332

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