Browsing by Author "Alkashash, Ahmad Mahmoud"

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    Artificial intelligence reveals features associated with breast cancer neoadjuvant chemotherapy responses from multi-stain histopathologic images
    (Springer Nature, 2023-01-27) Huang, Zhi; Shao, Wei; Han, Zhi; Alkashash, Ahmad Mahmoud; De la Sancha, Carlo; Parwani, Anil V.; Nitta, Hiroaki; Hou, Yanjun; Wang, Tongxin; Salama, Paul; Rizkalla, Maher; Zhang, Jie; Huang, Kun; Li, Zaibo; Electrical and Computer Engineering, School of Engineering and Technology
    Advances in computational algorithms and tools have made the prediction of cancer patient outcomes using computational pathology feasible. However, predicting clinical outcomes from pre-treatment histopathologic images remains a challenging task, limited by the poor understanding of tumor immune micro-environments. In this study, an automatic, accurate, comprehensive, interpretable, and reproducible whole slide image (WSI) feature extraction pipeline known as, IMage-based Pathological REgistration and Segmentation Statistics (IMPRESS), is described. We used both H&E and multiplex IHC (PD-L1, CD8+, and CD163+) images, investigated whether artificial intelligence (AI)-based algorithms using automatic feature extraction methods can predict neoadjuvant chemotherapy (NAC) outcomes in HER2-positive (HER2+) and triple-negative breast cancer (TNBC) patients. Features are derived from tumor immune micro-environment and clinical data and used to train machine learning models to accurately predict the response to NAC in breast cancer patients (HER2+ AUC = 0.8975; TNBC AUC = 0.7674). The results demonstrate that this method outperforms the results trained from features that were manually generated by pathologists. The developed image features and algorithms were further externally validated by independent cohorts, yielding encouraging results, especially for the HER2+ subtype.
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    Upper Gastrointestinal Cancer: Delays in Diagnosis and Treatment Caused by Barriers to Healthcare in the Latino Community
    (Elmer Press, 2022) Montalvan-Sanchez, Eleazar E.; Beas, Renato; Norwood, Dalton Argean; Alkashash, Ahmad Mahmoud; Rodriguez Murillo, Aida A.; Calderon, Gerardo; Medicine, School of Medicine
    We report a case of an 81-year-old male immigrant from a Latin American developing country with a high burden of upper gastrointestinal neoplasms, who presented with a small bowel gastrointestinal stromal tumor (GIST) after 2 years of delay in the diagnosis due to multiple barriers to healthcare. The patient presented with a partial intestinal obstruction in an abdominal computed tomography (CT) scan suggestive of a GIST. Surgical resection was performed, and adjuvant therapy was initiated with imatinib (a tyrosine kinase inhibitor) after the diagnosis was confirmed. The patient had a successful outcome. Due to his migratory status, the patient planned to follow up with different health providers in two different countries, which constitutes a common challenge in the immigrant population.