Effective dose and risk assessment in 18F-FDG PET/CT examinations of lymphoma patients using updated dose coefficients Forough Jafarian-Dehkordi, Yazdan Salimi, Esmail Jafari, Majid Assadi, Christoph Hoeschen Physica Medica, 2026 <h2>Abstract</h2><h3>Purpose</h3> The objective of this study was to estimate the total effective dose using the updated dose coefficient, and assess the associated cancer risk from radiation exposure in patients undergoing positron emission tomography (PET)/computed tomography (CT) for lymphoma indications. <h3>Methods</h3> This study included 103 patients who underwent FDG-PET/CT. The effective radiation doses to the body was calculated by summing the contribution from internal dosimetry, using the updated dose coefficients based on the ICRP approach, and external dosimetry, using the NCICT software. Based on the effective organ doses and utilizing the risk model introduced in the Biological Effects of Ionizing Radiation VII report, the lifetime attributable risk for cancer incidence (LARCI) and mortality (LARCM) were estimated on an organ-specific basis. <h3>Results</h3> The mean effective dose was 12.4 ± 2.8 mSv (range, 5.1–20.2 mSv), with CT contributing for 74% of the total dose. The LARCI and LARCM values varied by age and sex, with the most pronounced age-related declines observed in the uterus, ovary, and breast for female LARCI (R<sup>2</sup> = 0.83, 0.80, and 0.75, respectively) and in the liver, stomach, and colon for male LARCI (R<sup>2</sup> = 0.71, 0.64, and 0.60, respectively). Similarly, the strongest associations for LARCM were found in the breast, uterus, and ovary for females (R<sup>2</sup> = 0.75, 0.75, and 0.73, respectively) and in the stomach and liver for males (R<sup>2</sup> = 0.66 and 0.63, respectively). <h3>Conclusion</h3> PET/CT scans involve radiation exposure that varies with age and sex, posing higher risks to radiosensitive organs especially at younger ages.
Fibroblast Activation Protein Inhibitor Theranostics in Sarcoma Esmail Jafari, Malik E. Juweid, Narges Jokar, Nader Shakibazad, Seyed Javad Rekabpour, Majid Assadi Clinical Nuclear Medicine, 2026 Sarcomas are rare and heterogeneous cancers arising from mesenchymal tissues, presenting diagnostic and therapeutic challenges. Fibroblast activation protein (FAP), overexpressed in the tumor microenvironment of many sarcomas, has emerged as a promising theranostic target. FAP inhibitors (FAPI)-PET/CT demonstrates excellent sensitivity and specificity in detecting primary tumors, local recurrence, and distant metastases, even in low-grade sarcomas. This facilitates accurate staging and personalized treatment. Various FAPI radiotracers, including FAPI-04, FAPI-46, and FAP-2286, offer unique pharmacokinetic properties. FAPI-targeted radionuclide therapy (TRT) employs therapeutic radioisotopes to deliver targeted radiation to FAP-expressing tumor cells. Early clinical trials show promising disease control rates and manageable toxicity profiles. However, challenges remain, including FAP expression heterogeneity and the need for optimized treatment protocols. The aim of this review is to provide a comprehensive overview of the current evidence and future directions of FAPI-based theranostics in sarcoma management, highlighting its potential to improve patient outcomes.
FAP-Targeted Theranostics in Advanced Sarcoma: A Pilot Study of ⁶⁸Ga-FAPI-46 Imaging and ¹⁷⁷Lu-FAPI-2286 Therapy Narges Jokar, Malik E. Juweid, Esmail Jafari, Elmira Yazdani, Ahmad A. Deylami, Seyed J. Rekabpour, Nader Shakibazad, Milad Peer-firouzjaei, Hossein Arabi, Habib Zaidi, Majid Assadi Clinical Nuclear Medicine, 2026 Purpose: Sarcomas are aggressive mesenchymal malignancies with high recurrence rates and poor prognosis, particularly in advanced, metastatic stages where conventional therapies have been exhausted. Fibroblast activation protein (FAP), highly expressed in the tumor microenvironment of sarcomas, presents a promising theranostic target. This study aimed to evaluate the safety and efficacy of ¹⁷⁷Lu-FAPI-2286 radioligand therapy (RLT) in patients with advanced metastatic sarcoma and to compare the diagnostic utility of ⁶⁸Ga-FAPI-46 PET/CT with ¹⁸F-FDG PET/CT in these patients. Methods: This single-center exploratory study enrolled 6 patients (median age, 29 y) with histologically confirmed treatment-refractory metastatic sarcoma. All patients underwent baseline ⁶⁸Ga-FAPI-46 and ¹⁸F-FDG PET/CT, followed by 2 to 4 cycles of ¹⁷⁷Lu-FAPI-2286 (3.7–7.4 GBq per cycle). Organ-level dosimetry was performed using serial planar and SPECT/CT imaging. Treatment response was evaluated using PET response criteria in solid tumors (PERCIST), and toxicity was graded according to CTCAE v5.0. Quantitative image-derived metrics, including the standardized uptake value (SUV), metabolic tumor volume (MTV), total lesion glycolysis (TLG), FAP expression tumor volume (FTV), total lesion FAP expression (TLF), and tumor-to-liver ratio (TLR) were extracted. Results: On the basis of the quantitative imaging data from the 6 sarcoma patients, there was no statistically significant difference between ⁶⁸Ga-FAPI-46 and ¹⁸F-FDG across the measured parameters (SUV mean , SUV max , MTV/FTV, TLG/TLF, and TLR). However, ¹⁸F-FDG showed slightly higher MTVs. RLT was well-tolerated, with no grade ≥3 treatment-related toxicities observed. Adverse events were limited to low-grade hematological toxicities, including grade 2 leukopenia (n=1), grade 1 anemia (n=2), and grade 1 thrombocytopenia (n=1). Among 6 patients, 3 died due to disease progression before follow-up imaging could be completed. Among the 3 evaluable patients, one patient showed a mixed response pattern with metabolic improvement, but volumetric progression [partial response (PR) based on a decrease in SUV max and SUV mean , progressive disease (PD) based on an increase in FTV, and stable disease (SD) based on minimal change in TLF], another patient showed SD, and the last patient demonstrated PD. The median overall survival was 4 months (95% CI: 0–8.8 mo). Conclusion: 177 Lu-FAPI-2286 RLT was safe, well-tolerated, and demonstrated disease stabilization in heavily pretreated sarcoma patients. 68 Ga-FAPI-46 PET/CT provides superior delineation of FAP-rich tumor areas, but smaller tumor volumes compared with 18 F-FDG PET/CT. Prospective multicenter studies are warranted to confirm these findings and optimize FAP-targeted theranostic strategies in sarcoma.
Efficacy of PSMA PET/CT radiomics analysis for risk stratification in newly diagnosed prostate cancer: a multicenter study Esmail Jafari, Amin Zarei, Habibollah Dadgar, Ahmad Keshavarz, Hamid Abdollahi, Rezvan Samimi, Reyhaneh Manafi-Farid, GhasemAli Divband, Babak Nikkholgh, Babak Fallahi, HamidReza Amini, Hojjat Ahmadzadehfar, Arman Rahmim, Farshad Zohrabi, Majid Assadi BMC Medical Imaging, 2025 Prostate-specific membrane antigen (PSMA) PET/CT plays an increasing role in prostate cancer management. Radiomics analysis of PSMA PET/CT images may provide additional information for risk stratification. This study aimed to evaluate the performance of PSMA PET/CT radiomics analysis in differentiating between Gleason Grade Groups (GGG 1–3 vs. GGG 4–5) and predicting PSA levels (below vs. at or above 20 ng/ml) in patients with newly diagnosed prostate cancer. In this multicenter study, patients with confirmed primary prostate cancer were enrolled who underwent [68Ga]Ga-PSMA PET/CT for staging. Inclusion criteria required intraprostatic lesions on PET and the International Society of Urological Pathology (ISUP) grade information. Three different segments were delineated including intraprostatic PSMA-avid lesions on PET, the whole prostate in PET, and the whole prostate in CT. Radiomic features (RFs) were extracted from all segments. Dimensionality reduction was achieved through principal component analysis (PCA) prior to model training on data from two centers (186 cases) with 10-fold cross-validation. Model performance was validated with external data set (57 cases) using various machine learning models including random forest, nearest centroid, support vector machine (SVM), calibrated classifier CV and logistic regression. In this retrospective study, 243 patients with a median age of 69 (range: 46–89) were enrolled. For distinguishing GGG 1–3 from GGG 4–5, the nearest centroid classifier using radiomic features (RFs) from whole-prostate PET achieved the best performance in the internal test set, while the random forest classifier using RFs from PSMA-avid lesions in PET performed best in the external test set. However, when considering both internal and external test sets, a calibrated classifier CV using RFs from PSMA-avid PET data showed slightly improved overall performance. Regarding PSA level classification (< 20 ng/ml vs. ≥20 ng/ml), the nearest centroid classifier using RFs from the whole prostate in PET achieved the best performance in the internal test set. In the external test set, the highest performance was observed using RFs derived from the concatenation of PET and CT. Notably, when combining both internal and external test sets, the best performance was again achieved with RFs from the concatenated PET/CT data. Our research suggests that [68Ga]Ga-PSMA PET/CT radiomic features, particularly features derived from intraprostatic PSMA-avid lesions, may provide valuable information for pre-biopsy risk stratification in newly diagnosed prostate cancer.
Targets for Molecular Imaging of Neuroendocrine Tumors (NETs): An Overview and Update Esmail Jafari, Majid Assadi, Meysam Nasiri, Hojjat Ahmadzadehfar Seminars in Nuclear Medicine, 2025 Neuroendocrine neoplasms (NENs) represent a diverse group of tumors originating from neuroendocrine cells, characterized by their unique biological behavior and clinical manifestations. The incidence of neuroendocrine tumors (NETs) has been rising, necessitating effective diagnostic and therapeutic strategies. Molecular imaging, particularly through techniques such as PET and SPECT, plays a pivotal role in the management of NETs. This review highlights the significance of somatostatin receptor imaging in the initial diagnostic work-up, staging, and treatment planning for NETs, emphasizing the utility of radiopharmaceuticals like [68Ga]Ga-DOTATATE and [68Ga]Ga-DOTA-LM3. These agents demonstrate high sensitivity and specificity, allowing for accurate delineation of disease extent and identification of occult primary tumors. Furthermore, the review discusses the emerging role of nonsomatostatin receptor targets, such as glucose metabolism and fibroblast activation protein, in enhancing the diagnostic capabilities of molecular imaging. The integration of advanced imaging modalities, including dual-tracer approaches, is explored for their potential to refine therapeutic strategies and improve patient outcomes. As the field of molecular imaging continues to evolve, ongoing research and clinical trials are essential to validate the efficacy and safety of novel imaging agents and techniques, ultimately enhancing the management of patients with neuroendocrine tumors.
The value of artificial intelligence in PSMA PET: a pathway to improved efficiency and results Habibollah DADGAR, Xiaotong HONG, Reza KARIMZADEH, Bulat IBRAGIMOV, Jafar MAJIDPOUR, Hossein ARABI, Akram AL-IBRAHEEM, Aysar N. KHALAF, Farah M. ANWAR, Fahad MARAFI, Mohamad HAIDAR, Esmail JAFARI, Amin ZAREI, Majid ASSADI Quarterly Journal of Nuclear Medicine and Molecular Imaging, 2025 INTRODUCTION This systematic review investigates the potential of artificial intelligence (AI) in improving the accuracy and efficiency of prostate-specific membrane antigen positron emission tomography (PSMA PET) scans for detecting metastatic prostate cancer. EVIDENCE ACQUISITION A comprehensive literature search was conducted across Medline, Embase, and Web of Science, adhering to PRISMA guidelines. Key search terms included "artificial intelligence," "machine learning," "deep learning," "prostate cancer," and "PSMA PET." The PICO framework guided the selection of studies focusing on AI's application in evaluating PSMA PET scans for staging lymph node and distant metastasis in prostate cancer patients. Inclusion criteria prioritized original English-language articles published up to October 2024, excluding studies using non-PSMA radiotracers, those analyzing only the CT component of PSMA PET-CT, studies focusing solely on intra-prostatic lesions, and non-original research articles. EVIDENCE SYNTHESIS The review included 22 studies, with a mix of prospective and retrospective designs. AI algorithms employed included machine learning (ML), deep learning (DL), and convolutional neural networks (CNNs). The studies explored various applications of AI, including improving diagnostic accuracy, sensitivity, differentiation from benign lesions, standardization of reporting, and predicting treatment response. Results showed high sensitivity (62% to 97%) and accuracy (AUC up to 98%) in detecting metastatic disease, but also significant variability in positive predictive value (39.2% to 66.8%). CONCLUSIONS AI demonstrates significant promise in enhancing PSMA PET scan analysis for metastatic prostate cancer, offering improved efficiency and potentially better diagnostic accuracy. However, the variability in performance and the "black box" nature of some algorithms highlight the need for larger prospective studies, improved model interpretability, and the continued involvement of experienced nuclear medicine physicians in interpreting AI-assisted results. AI should be considered a valuable adjunct, not a replacement, for expert clinical judgment.
A Prospective Evaluation of Chemokine Receptor-4 (CXCR4) Overexpression in High-grade Glioma Using 68Ga-Pentixafor (Pars-Cixafor™) PET/CT Imaging Habibollah Dadgar, Nasim Norouzbeigi, Majid Assadi, Esmail Jafari, Batool Al-Balooshi, Akram Al-Ibraheem, Abdulredha A. Esmail, Fahad Marafi, Mohamad Haidar, Haider Muhsin Al-Alawi, Yehia Omar, Sharjeel Usmani, Andrea Cimini, Maria Ricci, Hossein Arabi, Habib Zaidi Academic Radiology, 2025 <h3>Background</h3> While magnetic resonance imaging (MRI) remains the gold standard for morphological imaging, its ability to differentiate between tumor tissue and treatment-induced changes on the cellular level is insufficient. Notably, glioma cells, particularly glioblastoma multiforme (GBM), demonstrate overexpression of chemokine receptor-4 (CXCR4). This study aims to evaluate the feasibility of non-invasive <sup>68</sup>Ga-Cixafor™ PET/CT as a tool to improve diagnostic accuracy in patients with high-grade glioma. <h3>Methods</h3> In this retrospective analysis, a database of histopathology-confirmed glioma patients with MRI findings consistent with high-grade gliomas was utilized. Within 2 weeks of their MRI, these patients underwent <sup>68</sup>Ga-Cixafor™ PET/CT scans to assess CXCR4 expression. Both visual scoring based on established criteria and semi-quantitative measures including maximum standardized uptake value (SUV<sub>max</sub>) and tumor-to-background ratios (TBR) were calculated to analyze the PET/CT data. <h3>Results</h3> Our retrospective study enrolled 29 histologically confirmed glioma patients with MRI findings consistent with high-grade gliomas. All patients underwent <sup>68</sup>Ga-Cixafor™ PET/CT scans within 2 weeks of their MRI, specifically at one-hour post-injection time point. Visual assessment based on a standardized scoring system identified 27 positive scans out of 29 (93.1%). Median SUV<sub>max</sub> was 2.31 (range: 0.49–9.96) and median TBR was 20 (range: 6.12–124.5). Pathological analysis revealed 5 grade III (17.24%) and 24 grade IV (82.75%) lesions among the 29 patients. Notably, the median SUV<sub>max</sub> of grade IV lesions (2.85) was significantly higher than grade III lesions (1.27) (P=0.02). Conversely, there was no significant difference in median TBR between grade IV (20) and grade III (22.37). These findings support the correlation between high CXCR4 expression, particularly in high-grade gliomas, and elevated uptake of <sup>68</sup>Ga-Pentixafor. While areas with high uptake showed CXCR4 expression, areas with low uptake did not exhibit noticeable expression (data not shown). <h3>Conclusion</h3> This study demonstrated that <sup>68</sup>Ga-Cixafor™ PET exhibits a TBR with minimal cortical uptake, significantly enhancing glioma detection compared to conventional imaging methods. This, combined with the potential therapeutic capabilities of CXCR4-targeting radiopharmaceuticals, highlights the promise of <sup>68</sup>Ga-Cixafor™ as a valuable tool for not only improved glioma diagnosis but also personalized treatment strategies.
Differential privacy preserved federated transfer learning for multi-institutional 68Ga-PET image artefact detection and disentanglement Isaac Shiri, Yazdan Salimi, Mehdi Maghsudi, Elnaz Jenabi, Sara Harsini, Behrooz Razeghi, Shayan Mostafaei, Ghasem Hajianfar, Amirhossein Sanaat, Esmail Jafari, Rezvan Samimi, Maziar Khateri, Peyman Sheikhzadeh, Parham Geramifar, Habibollah Dadgar, Ahmad Bitrafan Rajabi, Majid Assadi, François Bénard, Alireza Vafaei Sadr, Slava Voloshynovskiy, Ismini Mainta, Carlos Uribe, Arman Rahmim, Habib Zaidi European Journal of Nuclear Medicine and Molecular Imaging, 2023
Deep Adaptive Transfer Learning for Site-Specific PET Attenuation and Scatter Correction from Multi-National/Institutional Datasets Isaac Shiri, Yazdan Salimi, Mehdi Maghsudi, Ghasem Hajianfar, Esmail Jafari, Rezvan Samimi, Maziar Khateri, Peyman Sheikhzadeh, Parham Geramifar, Habibollah Dadgar, Ahmad Bitrafan Rajabi, Majid Assadi, Francois Benard, Carlos Uribe, Arman Rahmim, Habib Zaidi 2022 IEEE NSS Mic Rtsd IEEE Nuclear Science Symposium Medical Imaging Conference and Room Temperature Semiconductor Detector Conference, 2022
An Introduction to Boron Neutron Therapy (BNCT): Current Status and Future Outlook Malehe Omrani, Department of Biotechnology, Persian Gulf Research Studies Center, Persian Gulf University, Bushehr, Iran, Esmaeil Jafari, The Persian Gulf Nuclear Medicine Research Center, The Persian Gulf Biomedical Sciences Research Institute, Bushehr University of Medical Sciences, Bushehr, Iran, Zenab Alipour, Department of Infectious Diseases, School of Medicine, Bushehr University of Medical Sciences, Bushehr, Iran, Hajar Zarei, Department of Radiation Biotechnology, School of Nanoscience, Biotechnology, Persian Gulf University Iranian South Medical Journal, 2021
Deep Active Learning Model for Adaptive PET Attenuation and Scatter Correction in Multi-Centric Studies Isaac Shiri, Amirhossein Sanaat, Esmail Jafari, Rezvan Samimi, Maziar Khateri, Peyman Sheikhzadeh, Parham Geramifar, Habibollah Dadgar, Hossein Arabi, Majid Assadi, Carlos Uribe, Arman Rahmim, Habib Zaidi 2021 IEEE Nuclear Science Symposium and Medical Imaging Conference Record NSS Mic 2021 and 28th International Symposium on Room Temperature Semiconductor Detectors Rtsd 2022, 2021
Fibroblast activation protein-targeted molecular imaging in interstitial lung disease: a systematic review AG Olya, M Bahtouee, E Jafari, M Ravanipour, A Hamidi, N Aram, ... Annals of Nuclear Medicine, 1-18 , 2026 2026
Effective dose and risk assessment in 18F-FDG PET/CT examinations of lymphoma patients using updated dose coefficients F Jafarian-Dehkordi, Y Salimi, E Jafari, M Assadi, C Hoeschen Physica Medica 142, 105712 , 2026 2026
Machine Learning based Radiomics Analysis of SPECT Images in Predicting Neuroendocrine Tumors M Ghazizadeh, M Amoui, MR Deevband, K Aryana, F Karamian, ... Biomedical Engineering Advances, 100197 , 2025 2025
Efficacy of PSMA PET/CT radiomics analysis for risk stratification in newly diagnosed prostate cancer: a multicenter study E Jafari, A Zarei, H Dadgar, A Keshavarz, H Abdollahi, R Samimi, ... BMC Medical Imaging 25 (1), 375 , 2025 2025 Citations: 2
Targets for molecular imaging of neuroendocrine tumors (NETs): an overview and update E Jafari, M Assadi, M Nasiri, H Ahmadzadehfar Seminars in Nuclear Medicine 55 (5), 740-753 , 2025 2025 Citations: 5
Beyond cancer: the role of radiolabeled fibroblast activation protein inhibitors (FAPI) in non-oncological molecular imaging E Jafari, ME Juweid, M Bahtouee, M Pourbehi, K Esmaeilinejad, N Jokar, ... Academic Radiology , 2025 2025 Citations: 7
Durable responses to frontline 177Lu-PSMA radioligand therapy in patients with metastatic castration resistant prostate cancer (mCRPC) N Jokar, E Jafari, SJ Rekabpour, F Zohrabi, H Ahmadzadehfar, M Assadi Clinical and Translational Imaging 13 (4), 421-428 , 2025 2025 Citations: 1
Current practice of nuclear medicine in Iran E Jafari, N Jokar, S Bagheri, M Assadi Clinical Nuclear Medicine Open 2 (2), e0034 , 2025 2025 Citations: 1
The value of artificial intelligence in PSMA PET: a pathway to improved efficiency and results. H Dadgar, X Hong, R Karimzadeh, B Ibragimov, J Majidpour, H Arabi, ... The Quarterly Journal of Nuclear Medicine and Molecular Imaging: Official … , 2025 2025 Citations: 10
A prospective evaluation of chemokine receptor-4 (CXCR4) overexpression in high-grade glioma using 68Ga-Pentixafor (Pars-Cixafor™) PET/CT imaging H Dadgar, N Norouzbeigi, M Assadi, E Jafari, B Al-Balooshi, ... Academic radiology 32 (4), 2247-2256 , 2025 2025 Citations: 8
Correction: The role of [68Ga] Ga-PSMA PET/CT in primary staging of newly diagnosed prostate cancer: predictive value of PET-derived parameters for risk stratification through … E Jafari, H Dadgar, A Zarei, R Samimi, R Manafi-Farid, G Divband, ... Clinical and Translational Imaging 13 (1), 93-93 , 2025 2025 Citations: 1
Exploring the potential value of [68Ga] Ga-FAPI-46 PET/CT for molecular assessment of fibroblast activation in interstitial lung disease: A Single-Center pilot study M Bahtouee, E Jafari, M Khazaei, N Aram, A Amini, N Jokar, ... Clinical Nuclear Medicine 50 (1), e17-e25 , 2025 2025 Citations: 18
The role of [68Ga] Ga-PSMA PET/CT in primary staging of newly diagnosed prostate cancer: predictive value of PET-derived parameters for risk stratification through machine learning E Jafari, H Dadgar, A Zarei, R Samimi, R Manafi-Farid, G Divband, ... Clinical and Translational Imaging 12 (6), 669-682 , 2024 2024 Citations: 4
Prognostic significance of baseline clinical and [68Ga] Ga-PSMA PET derived parameters on biochemical response, overall survival, and PSA progression-free survival in … E Jafari, R Manafi-Farid, H Ahmadzadehfar, F Salek, N Jokar, ... Nuklearmedizin-NuclearMedicine 63 (06), 347-358 , 2024 2024 Citations: 7
Automated classification of Alzheimer's disease, mild cognitive impairment, and cognitively normal patients using 3D convolutional neural network and radiomic features from T1 … A Zarei, A Keshavarz, E Jafari, R Nemati, A Farhadi, ... Clinical Imaging 115, 110301 , 2024 2024 Citations: 17
Exploring the Potential Value of [68Ga] Ga-FAPI-46 PETCT for Molecular Assessment of Fibroblast Activation in Interstitial Lung Disease: a single-center pilot study M Assadi, M Bahtouee, E Jafari, M Khazaei, N Aram, A Amini, N Jokar, ... EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING 51, S55-S55 , 2024 2024
Innovative quantitative analysis of left ventricular axis from cardiac SPECT images: XCAT phantom study and clinical validation F Salahshourinejad, A Keshavarz, E Jafari, M Assadi Iranian Journal of Nuclear Medicine 32 (2), 102-111 , 2024 2024
Pulmonary perfusion deficiency detection in lung subsegments of spect/ct images using radiomics and machine learning algorithms G Hajianfar, Y Salimi, E Jafari, H Zareian, M Ahadi, M Amini, SA Mousavi, ... Journal of Nuclear Medicine 65 (supplement 2), 241915-241915 , 2024 2024 Citations: 2
Machine learning-assisted pulmonary emboly diagnosis from SPECT/CT images G Hajianfar, Y Salimi, E Jafari, H Zareian, M Ahadi, M Amini, SA Mousavi, ... Journal of Nuclear Medicine 65 (supplement 2), 241902-241902 , 2024 2024
Exploring the efficacy of FAPI PET/CT in the diagnosis and treatment management of colorectal cancer: a comprehensive literature review and initial experience H Dadgar, N Norouzbeigi, E Jafari, B Al-balooshi, A Al-Ibraheem, ... Clinical and Translational Imaging 12 (3), 235-252 , 2024 2024 Citations: 17
MOST CITED SCHOLAR PUBLICATIONS
Feasibility and therapeutic potential of 177Lu–fibroblast activation protein inhibitor–46 for patients with relapsed or refractory cancers: a preliminary study M Assadi, SJ Rekabpour, E Jafari, GA Divband, B Nikkholgh, H Amini, ... Clinical nuclear medicine 46 (11), e523-e530 , 2021 2021 Citations: 170
Theranostic approach in breast cancer: a treasured tailor for future oncology N Jokar, I Velikyan, H Ahmadzadehfar, SJ Rekabpour, E Jafari, HH Ting, ... Clinical nuclear medicine 46 (8), e410-e420 , 2021 2021 Citations: 106
Effect of pulsed electromagnetic field on mandibular fracture healing: A randomized control trial,(RCT) H Mohajerani, F Tabeie, F Vossoughi, E Jafari, M Assadi Journal of stomatology, oral and maxillofacial surgery 120 (5), 390-396 , 2019 2019 Citations: 50
177Lu-PSMA and 177Lu-DOTATATE Therapy in a patient with metastatic castration-resistant prostate cancer and neuroendocrine differentiation M Assadi, E Pirayesh, SJ Rekabpour, F Zohrabi, E Jafari, I Nabipour, ... Clinical nuclear medicine 44 (12), 978-980 , 2019 2019 Citations: 36
Differential privacy preserved federated transfer learning for multi-institutional 68 Ga-PET image artefact detection and disentanglement I Shiri, Y Salimi, M Maghsudi, E Jenabi, S Harsini, B Razeghi, S Mostafaei, ... European journal of nuclear medicine and molecular imaging 51 (1), 40-53 , 2023 2023 Citations: 34
Feasibility and therapeutic potential of combined peptide receptor radionuclide therapy with intensive chemotherapy for pediatric patients with relapsed or refractory … G Fathpour, E Jafari, A Hashemi, H Dadgar, M Shahriari, S Zareifar, ... Clinical Nuclear Medicine 46 (7), 540-548 , 2021 2021 Citations: 34
Potential application of lutetium-177-labeled prostate-specific membrane antigen-617 radioligand therapy for metastatic castration-resistant prostate cancer in a limited … M Assadi, S Rezaei, E Jafari, SJ Rekabpour, M Ravanbod, F Zohrabi, ... World Journal of Nuclear Medicine 19 (01), 15-20 , 2020 2020 Citations: 31
An update on PET-based molecular imaging in neuro-oncology: challenges and implementation for a precision medicine approach in cancer care H Shooli, H Dadgar, YXJ Wang, MS Vafaee, SR Kashuk, R Nemati, ... Quantitative imaging in medicine and surgery 9 (9), 1597 , 2019 2019 Citations: 31
The evaluation of protective and mitigating effects of vitamin C against side effects induced by radioiodine therapy E Jafari, M Alavi, F Zal Radiation and Environmental Biophysics 57 (3), 233-240 , 2018 2018 Citations: 30
A convolutional neural network–based system for fully automatic segmentation of whole-body [ 68 Ga]Ga-PSMA PET images in prostate cancer E Jafari, A Zarei, H Dadgar, A Keshavarz, R Manafi-Farid, H Rostami, ... European journal of nuclear medicine and molecular imaging 51 (5), 1476-1487 , 2024 2024 Citations: 28
Predictive and prognostic potential of pretreatment 68 Ga-PSMA PET tumor heterogeneity index in patients with metastatic castration-resistant prostate cancer … M Assadi, R Manafi-Farid, E Jafari, A Keshavarz, GA Divband, MM Moradi, ... Frontiers in Oncology 12, 1066926 , 2022 2022 Citations: 26
An aggressive functioning pituitary adenoma treated with peptide receptor radionuclide therapy M Assadi, R Nemati, H Shooli, SJ Rekabpour, I Nabipour, E Jafari, ... European Journal of Nuclear Medicine and Molecular Imaging 47 (4), 1015-1016 , 2020 2020 Citations: 26
Assessment of the prevalence of diabetic gastroparesis and validation of gastric emptying scintigraphy for diagnosis Z Alipour, F Khatib, SM Tabib, H Javadi, E Jafari, L Aghaghazvini, ... Molecular Imaging and Radionuclide Therapy 26 (1), 17 , 2017 2017 Citations: 26
Artificial intelligence-based analysis of whole-body bone scintigraphy: the quest for the optimal deep learning algorithm and comparison with human observer performance G Hajianfar, M Sabouri, Y Salimi, M Amini, S Bagheri, E Jenabi, S Hekmat, ... Zeitschrift für Medizinische Physik 34 (2), 242-257 , 2024 2024 Citations: 24
Feasibility and therapeutic potential of the 68Ga/177Lu-DOTATATE theranostic pair in patients with metastatic medullary thyroid carcinoma H Dadgar, E Jafari, H Ahmadzadehfar, SJ Rekabpour, MR Ravanbod, ... Annales d'Endocrinologie 84 (1), 45-51 , 2023 2023 Citations: 24
Theranostics in brain tumors H Shooli, R Nemati, H Ahmadzadehfar, M Aboian, E Jafari, N Jokar, ... PET clinics 16 (3), 397-418 , 2021 2021 Citations: 19
Application of [ 68 Ga]PSMA PET/CT in Diagnosis and Management of Prostate Cancer Patients H Dadgar, F Emami, N Norouzbeigi, MS Vafaee, E Jafari, ... Molecular Imaging and Biology 22 (4), 1062-1069 , 2020 2020 Citations: 19
Exploring the potential value of [68Ga] Ga-FAPI-46 PET/CT for molecular assessment of fibroblast activation in interstitial lung disease: A Single-Center pilot study M Bahtouee, E Jafari, M Khazaei, N Aram, A Amini, N Jokar, ... Clinical Nuclear Medicine 50 (1), e17-e25 , 2025 2025 Citations: 18
Automated classification of Alzheimer's disease, mild cognitive impairment, and cognitively normal patients using 3D convolutional neural network and radiomic features from T1 … A Zarei, A Keshavarz, E Jafari, R Nemati, A Farhadi, ... Clinical Imaging 115, 110301 , 2024 2024 Citations: 17
Exploring the efficacy of FAPI PET/CT in the diagnosis and treatment management of colorectal cancer: a comprehensive literature review and initial experience H Dadgar, N Norouzbeigi, E Jafari, B Al-balooshi, A Al-Ibraheem, ... Clinical and Translational Imaging 12 (3), 235-252 , 2024 2024 Citations: 17
