Elmira Yazdani

Ms. Elmira Yazdani

Medical Physics Department, School of Medicine, Iran University of Medical Sciences, Tehran, Tehrān, Iran

Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 January 2024 in Diagnostics
Verified
Journal Article
Open access
PDF file
EYElmira Yazdani
Elmira Yazdani
PGParham Geramifar
Parham Geramifar
NKNajme Karamzade-Ziarati
Najme Karamzade-Ziarati
Mahdi SadeghiMahdi Sadeghi
Mahdi Sadeghi
PAPayam Amini
Payam Amini
ARArman Rahmim
Arman Rahmim
Radiotheranostics refers to the pairing of radioactive imaging biomarkers with radioactive therapeutic compounds that deliver ionizing radiation. Given the introduction of very promising radiopharmaceuticals, the radiotheranostics approach is creating a novel paradigm in personalized, targeted radionuclide therapies (TRTs), also known as radiopharmaceuticals (RPTs). Radiotherapeutic pairs targeting somatostatin receptors (SSTR) and prostate-specific membrane antigens (PSMA) are increasingly being used to diagnose and treat patients with metastatic neuroendocrine tumors (NETs) and prostate cancer. In parallel, radiomics and artificial intelligence (AI), as important areas in quantitative image analysis, are paving the way for significantly enhanced workflows in diagnostic and theranostic fields, from data and image processing to clinical decision support, improving patient selection, personalized treatment strategies, response prediction, and prognostication. Furthermore, AI has the potential for tremendous effectiveness in patient dosimetry which copes with complex and time-consuming tasks in the RPT workflow. The present work provides a comprehensive overview of radiomics and AI application in radiotheranostics, focusing on pairs of SSTR- or PSMA-targeting radioligands, describing the fundamental concepts and specific imaging/treatment features. Our review includes ligands radiolabeled by 68Ga, 18F, 177Lu, 64Cu, 90Y, and 225Ac. Specifically, contributions via radiomics and AI towards improved image acquisition, reconstruction, treatment response, segmentation, restaging, lesion classification, dose prediction, and estimation as well as ongoing developments and future directions are discussed.

15 July 2025 in Journal of Medical Imaging and Radiation Sciences
Verified
Journal Article
Closed access
EYElmira Yazdani
Elmira Yazdani
ANAryan Neizehbaz
Aryan Neizehbaz
NKNajme Karamzade-Ziarati
Najme Karamzade-Ziarati
SKSaeed Reza Kheradpisheh
Saeed Reza Kheradpisheh

2 December 2025 in Radiation Oncology
Verified
Journal Article
Open access
PDF file
AMAtefeh Mahmoudi
Atefeh Mahmoudi
AZArash Zare-Sadeghi
Arash Zare-Sadeghi
HIHamed Iraji
Hamed Iraji
MBMaedeh Barahman
Maedeh Barahman
PSPegah Saadatmand
Pegah Saadatmand
SMseied rabi mehdi mahdavi
seied rabi mehdi mahdavi
Tumor heterogeneity is a significant factor contributing to the marked differences in survival rates among glioblastoma multiforme (GBM) patients, who face

27 November 2023 in Preprints.org
Verified
Preprint
Open access
PDF file
EYElmira Yazdani
Elmira Yazdani
PGParham Geramifar
Parham Geramifar
NKNajme Karamzade-Ziarati
Najme Karamzade-Ziarati
Mahdi SadeghiMahdi Sadeghi
Mahdi Sadeghi
PAPayam Amini
Payam Amini
ARArman Rahmim
Arman Rahmim
Radiotheranostics refers to pairing of radioactive imaging biomarkers with radioactive therapeutic compounds that deliver ionizing radiation. Given the introduction of very promising radio-pharmaceuticals, the radiotheranostics approach is creating a novel paradigm in personalized, targeted radionuclide therapies (TRTs), also known as radiopharmaceuticals (RPTs). Radiother-apeutic pairs targeting somatostatin receptors (SSTR) and prostate-specific membrane antigens (PSMA) are increasingly used to diagnose and treat patients with metastatic neuroendocrine tumors (NETs) and prostate cancer. In parallel, radiomics and artificial intelligence (AI) as important areas in quantitative image analysis are paving the way for significantly enhanced workflows in diagnostic and theranostic fields, from data and image processing to clinical decision support, improving patient selection, personalized treatment strategies, response prediction, and prognostication. Furthermore, AI has the potential for tremendous effectiveness in patient dosimetry which copes with complex and time-consuming tasks in the RPT workflow. The present work provides a comprehensive overview of radiomics and AI application in radio-theranostics, focusing on pairs of SSTR- or PSMA‑targeting radioligands, describing the funda-mental concepts and specific imaging/treatment features. Our review includes ligands radio-labeled by 68Ga, 18F, 177Lu, 64Cu, 90Y, and 225Ac. Specifically, contributions by radiomics and AI towards improved image acquisition, reconstruction, treatment response, segmentation, restag-ing, lesion classification, dose prediction, and estimation as well as ongoing developments and future directions are discussed.