Neurology India, Год журнала: 2023, Номер 71(5), С. 872 - 874
Опубликована: Сен. 1, 2023
Язык: Английский
Cancer Reports, Год журнала: 2024, Номер 7(4)
Опубликована: Апрель 1, 2024
Abstract Background Iatrogenesis is an inevitable global threat to healthcare that drastically increases morbidity and mortality. Cancer a fatal pathological condition affects people of different ages, sexes, races around the world. In addition detrimental cancer pathology, one most common contraindications challenges observed in patients severe adverse drug effects hypersensitivity reactions induced by chemotherapy. Chemotherapy‐induced cognitive neurotoxicity clinically referred as impairment (CICI), chemobrain, or chemofog. CICI, chemotherapy also causes neuropsychiatric issues, mental disorders, hyperarousal states, movement disorders. A synergistic regimen Doxorubicin (Anthracycline‐DOX) Cyclophosphamide (Alkylating Cytophosphane‐CPS) indicated for management various cancers (breast cancer, lymphoma, leukemia). Nevertheless, there are limited research studies on Cyclophosphamide's pharmacodynamic toxicological dopaminergic neuronal function. Aim This study evaluated neurotoxic Cyclophosphamide. Methods Results were incubated with (N27) neurons. Neuronal viability was assessed using MTT assay. The effect prooxidants, antioxidants, mitochondrial Complex‐I & IV activities, BAX expression Spectroscopic, Fluorometric, RT‐PCR methods, respectively. Prism‐V software (La Jolla, CA, USA) used statistical analysis. Chemotherapeutics dose‐dependently inhibited proliferation mechanism attributed significant increase decrease augmented apoptosis without affecting Conclusion first reports reveal induce neurotoxicity. Thus, reaction issues substantially persist during after treatment sometimes never be completely resolved clinically. Consequently, failure adopt adequate patient care measures treated certain chemotherapeutics might raise incidence numerous
Язык: Английский
Процитировано
2
Exploration of Targeted Anti-tumor Therapy, Год журнала: 2023, Номер unknown, С. 344 - 354
Опубликована: Апрель 28, 2023
Oncologic emergencies are a wide spectrum of oncologic conditions caused directly by malignancies or their treatment. may be classified according to the underlying physiopathology in metabolic, hematologic, and structural conditions. In latter, radiologists have pivotal role, through an accurate diagnosis useful provide optimal patient care. Structural involve central nervous system, thorax, abdomen, emergency know characteristics imaging findings each one them. The number is growing due increased incidence general population also improved survival these patients thanks advances cancer Artificial intelligence (AI) could solution assist with this rapidly increasing workload. To our knowledge, AI applications setting mostly underexplored, probably relatively low difficulty training algorithms. However, defined cause not specific pattern radiological symptoms signs. Therefore, it can expected that algorithms developed for detection non-oncological field transferred clinical emergency. review, craniocaudal approach was followed thoracic, abdominal been addressed regarding reported literature. Among system emergencies, brain herniation spinal cord compression. thoracic district were pulmonary embolism, cardiac tamponade pneumothorax. Pneumothorax most frequently described application AI, improve sensibility reduce time-to-diagnosis. Finally, hemorrhage, intestinal obstruction, perforation, intussusception described.
Язык: Английский
Процитировано
4
Radiologic Clinics of North America, Год журнала: 2023, Номер 62(2), С. 355 - 370
Опубликована: Ноя. 18, 2023
Язык: Английский
Процитировано
4
North American Spine Society Journal (NASSJ), Год журнала: 2024, Номер 19, С. 100513 - 100513
Опубликована: Июль 3, 2024
Metastasis to the spinal column is a common complication of malignancy, potentially causing pain and neurologic injury. An automated system identify refer patients with metastases can help overcome barriers timely treatment. We describe training, optimization validation natural language processing algorithm presence vertebral metastasis metastatic epidural cord compression (MECC) from radiology reports MRIs.
Язык: Английский
Процитировано
1
Cureus, Год журнала: 2024, Номер unknown
Опубликована: Сен. 24, 2024
Metastatic epidural spinal cord compression (MESCC) is a critical oncologic emergency caused by the invasion of metastatic tumors into space, leading to cord. If not promptly diagnosed and treated, MESCC can result in irreversible neurological deficits, including paralysis, significantly impacting patient's quality life. Early detection timely intervention are crucial prevent permanent damage. Imaging modalities play pivotal role diagnosis, assessment disease extent, treatment planning for MESCC. Magnetic resonance imaging (MRI) current gold standard due its superior ability visualize cord, lesions. However, recent advances technologies have enhanced management Innovations such as functional MRI, diffusion-weighted (DWI), hybrid techniques like positron emission tomography-computed tomography (PET-CT) PET-MRI improved accuracy particularly detecting early changes guiding therapeutic interventions. This review provides comprehensive analysis evolution MESCC, focusing on their roles detection, planning. It also discusses impact these clinical outcomes future research directions Understanding advancements optimizing improving patient prognosis.
Язык: Английский
Процитировано
1
Diagnostics, Год журнала: 2024, Номер 14(21), С. 2458 - 2458
Опубликована: Ноя. 3, 2024
Objectives: The integration of machine learning and radiomics in medical imaging has significantly advanced diagnostic prognostic capabilities healthcare. This study focuses on developing validating an artificial intelligence (AI) model using U-Net architectures for the accurate detection segmentation spinal metastases from computed tomography (CT) images, addressing both osteolytic osteoblastic lesions. Methods: Our methodology employs multiple variations architecture utilizes two distinct datasets: one consisting 115 polytrauma patients vertebra another comprising 38 with documented lesion detection. Results: demonstrated strong performance segmentation, achieving Dice Similarity Coefficient (DSC) values between 0.87 0.96. For metastasis achieved a DSC 0.71 F-beta score 0.68 lytic lesions but struggled sclerotic lesions, obtaining 0.61 0.57, reflecting challenges detecting dense, subtle bone alterations. Despite these limitations, successfully identified isolated metastatic beyond spine, such as sternum, indicating potential broader skeletal Conclusions: concludes that AI-based models can augment radiologists’ by providing reliable second-opinion tools, though further refinements diverse training data are needed optimal performance, particularly segmentation. annotated CT dataset produced shared this research serves valuable resource future advancements.
Язык: Английский
Процитировано
1
World Neurosurgery, Год журнала: 2023, Номер 175, С. e823 - e831
Опубликована: Апрель 13, 2023
Язык: Английский
Процитировано
3
European Spine Journal, Год журнала: 2023, Номер 32(11), С. 3815 - 3824
Опубликована: Апрель 24, 2023
Язык: Английский
Процитировано
3
Neuroimaging Clinics of North America, Год журнала: 2023, Номер 33(3), С. 443 - 457
Опубликована: Май 10, 2023
Язык: Английский
Процитировано
3
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
0