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Profil bibliographique

Omid Haji Maghsoudi

Informations fournies par OpenAlex. Research Africa ne déduit ni nationalité, ni poste, ni coordonnées personnelles.

47Publications signalées
833Citations signalées
0Affiliations récentes

Les domaines associés

Radiomics and Machine Learning in Medical ImagingGastrointestinal Bleeding Diagnosis and TreatmentAI in cancer detectionDigital Radiography and Breast ImagingMuscle activation and electromyography studies

Les publications récentes

2026 conference-abstract OpenAlex

Baseline CT-derived QVT score as predictor of bevacizumab benefit in advanced non-squamous NSCLC: A retrospective biomarker analysis of SWOG S0819.

Kai Zhang, Pushkar Mutha, Omid Haji Maghsoudi, Lauren Bailey Hein et autres

8549 Background: Despite two decades of anti-angiogenic therapy in NSCLC, no predictive biomarker identifies which patients benefit. As VEGF-targeted combinations advance in clinical development, patient selection biomarkers remain a critical unmet need. QVT (Quantitative Vessel Tortuosity) Score is an automated imaging biomarker …

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0 citations Journal of Clinical Oncology
Accès ouvert 2025 conference-abstract OpenAlex

66 QVT Score, a radiomic biomarker of tumor vascularity, enables immune checkpoint inhibitor (ICI) outcome prediction and early survival assessment in NSCLC

Young Kwang Chae, Kai Zhang, Liam Il‐Young Chung, Amogh Hiremath et autres

Background Predicting ICI benefit relies primarily on PD-L1 expression, which is a poor one-dimensional measure and overlooks resistance mechanisms such as tumor angiogenesis. QVT is a radiomic approach for measuring abnormalities of the tumor-associated vasculature, which have been shown to be associated …

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0 citations Regular and Young Investigator Award Abstracts
Accès ouvert 2025 preprint OpenAlex

QVT Score, a radiomic biomarker of vascular complexity, enables prognostication and monitoring of NSCLC immunotherapy

Y.K. Chae, Vamsidhar Velcheti, Kai Zhang, Amogh Hiremath et autres

Abstract Background Immune checkpoint inhibitors (ICIs) improve survival in advanced non-small cell lung cancer (NSCLC), yet current biomarkers such as PD-L1 expression and response criteria (RECIST v1.1) align poorly with long-term survival. Radiomics has been proposed as a source of novel biomarkers, …

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0 citations medRxiv
2025 conference-abstract OpenAlex

Radiomic phenotypes of tumor angiogenesis compared with PD-L1 in pre-treatment prediction of outcomes across immunotherapy regimens in NSCLC: An external validation study.

Vamsidhar Velcheti, Young Kwang Chae, Kai Zhang, Il-Young Chung et autres

8581 Background: Tumor angiogenesis is critical to cancer progression and treatment resistance, as evidenced by the success of therapies targeting both immune activation and neoangiogenesis. Conventional biomarkers like PD-L1 unreliably predict long-term patient outcomes such as overall survival (OS). Quantitative Vessel Tortuosity …

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0 citations Journal of Clinical Oncology
2025 conference-abstract OpenAlex

Effect of fusion of radiomic, pathomic, and clinical biomarkers on multi-scale tumor biology and OS stratification in HNSCC receiving standard of care (SOC).

Omid Haji Maghsoudi, Haojia Li, Lauren Brady, Kai Zhang et autres

6046 Background: SOC immunotherapy (IO) for head and neck squamous cell carcinoma (HNSCC) has limited efficacy with inadequate biomarkers (BMs), necessitating improved strategies. Routine radiology and pathology scans provide underutilized tumor data that can address this need. BMs built from these scans …

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3 citations Journal of Clinical Oncology
Accès ouvert 2024 conference-abstract OpenAlex

112 Multimodal AI biomarker fusing radiology, pathology, and molecular information for immune checkpoint inhibitor (ICI) response prediction in lung adenocarcinoma (LUAD)

Haojia Li, Amogh Hiremath, Seyoung Lee, Liam Il‐Young Chung et autres

Background LUAD, the most common subtype of NSCLC, has benefited from ICIs, but current biomarkers (e.g. PD-L1) fail to fully identify responders. Application of AI in routinely collected radiology images and tumor tissue samples has substantially advanced, showing promise to improve guidance …

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0 citations Regular and Young Investigator Award Abstracts
2024 conference-abstract OpenAlex

An interpretable AI-derived radiology signature to identify patients at risk of progression on the PACIFIC regimen for unresectable non-small cell lung cancer.

Omid Haji Maghsoudi, Liam IL Young Chung, Seyoung Lee, Jeeyeon Lee et autres

8079 Background: Advances in the treatment of unresectable NSCLC have emerged through the combination of chemotherapy, radiotherapy, and immune checkpoint inhibitors (ICI), also known as the PACIFIC regimen. Despite this protocol’s benefits, it lacks predictive biomarkers and many patients will ultimately fail …

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1 citation Journal of Clinical Oncology
2023 conference-abstract OpenAlex

Abstract P070: Volumetric parenchymal pattern analysis for breast cancer risk estimation

Eric A. Cohen, Omid Haji Maghsoudi, Raymond J. Acciavatti, Lauren Pantalone et autres

Abstract Introduction: Mammographic breast density is among the strongest risk factors for breast cancer. However, breast density is typically assessed subjectively by the radiologist according to the Breast Imaging Reporting and Data System (BI-RADS) based on 2 dimensional (2D) digital mammography (DM) …

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0 citations Cancer Prevention Research

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