EJNMMI Research最新文献

{"title":"Clinical significance of diffuse [¹⁸F] AlF-NOTA-FAPI-04 uptake in the thyroid on PET/CT imaging.","authors":"Ying Kou, Wei Diao, Zhuzhong Cheng, Yutang Yao","doi":"10.1186/s13550-025-01231-9","DOIUrl":"https://doi.org/10.1186/s13550-025-01231-9","url":null,"abstract":"<p><strong>Background: </strong>Many patients undergoing [¹⁸F] AlF-NOTA-FAPI-04 (¹⁸F-FAPI) PET/CT demonstrated diffuse thyroid uptake. These findings created challenges for accurate interpretation due to the limited understanding of physiological and non-oncologic causes of diffuse ¹⁸F-FAPI uptake in the thyroid. This retrospective study examined patients who underwent ¹⁸F-FAPI PET/CT imaging with diffuse thyroid uptake. It quantitatively assessed normal thyroid uptake, compared ¹⁸F-FAPI uptake between normal and diseased thyroids, and explored potential associations with diffuse thyroid uptake. The study may improve the accuracy of ¹⁸F-FAPI PET/CT interpretation for thyroid and facilitate appropriate management of diffuse thyroid uptake on ¹⁸F-FAPI PET/CT.</p><p><strong>Results: </strong>A total of 38 patients were included in this study based on the inclusion criteria. The mean SUVmax, SUVmean, and TBR of normal thyroid were 7.09 ± 3.83, 4.24 ± 2.25 and 3.93 ± 1.73, respectively. Quantitative analysis revealed no significant asymmetry in ¹⁸F-FAPI uptake between the right and left thyroid lobes (SUVmax: right 6.69 ± 2.96 vs. left 6.54 ± 3.28, p = 0.84; SUVmean: right 4.19 ± 1.73 vs. left 4.18 ± 1.97, p = 0.98), consistent with the diffuse uptake pattern observed. There was no significant correlation between Hashimoto thyroiditis, serum TSH levels, and the degree of diffuse thyroid uptake (all p > 0.05 for SUVmax, SUVmean, and TBR). Furthermore, no association was observed between sex, age, immunotherapy, and diffuse thyroid uptake (p > 0.05).</p><p><strong>Conclusions: </strong>Diffuse uptake of ¹⁸F-FAPI in the thyroid may not significantly relate to Hashimoto thyroiditis or abnormal serum TSH levels. Lesions on ¹⁸F-FAPI PET/CT scans might be hard to detect due to the moderate uptake in normal thyroid tissue.</p>","PeriodicalId":11611,"journal":{"name":"EJNMMI Research","volume":"15 1","pages":"47"},"PeriodicalIF":3.1,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12032088/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143973179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preoperative assessment and prognostic prediction of gastric cancer patients with peritoneal metastasis using ¹⁸F-FDG PET/CT before conversion surgery.","authors":"Yao Peng, Min Shi, Daxi Xiong, Sheng Lu, Ying Miao, Hong Yuan, Chao Yan, Zhenggang Zhu, Biao Li, Zhongyin Yang, Jiajia Hu","doi":"10.1186/s13550-025-01244-4","DOIUrl":"10.1186/s13550-025-01244-4","url":null,"abstract":"<p><strong>Background: </strong>Conversion therapy followed by conversion surgery (CS) can improve the prognosis of gastric cancer (GC) patients with peritoneal metastasis (PM). However, patients benefit differently. There is no way to confirm the prognostic benefit non-invasively and early. This retrospective study assessed the value of ¹⁸F-FDG PET/CT after conversion therapy in preoperative assessment and prognostic prediction of GC patients with PM.</p><p><strong>Results: </strong>Fifty-one GC patients with PM were enrolled. ¹⁸F-FDG PET/CT after conversion therapy helped in preoperative assessment. Its diagnostic accuracy for residual peritoneal lesions was slightly better than contrast-enhanced CT (72.5% vs. 61.2%, P = 0.229), although the difference was not statistically significant. TBR of peritoneal lesions could help preoperative assessment, with TBR of peritoneal lesions to the mediastinal blood pool SUVmax (TBRAmaxp) as the best predictor (cutoff = 0.705, specificity 80%, sensitivity 80%, AUC 0.825, P < 0.001). Additionally, PET/CT could predict prognosis and assess surgical benefit. SUVmax of peritoneal lesions (SUVmaxp) was the best predictor of 24 months survival (cutoff = 1.466, AUC 0.870, P = 0.002, Specificity 77.8%, Sensitivity 83.3%) and metabolic parameters of peritoneal lesions could predict OS and the prognosis of patients who underwent CS.</p><p><strong>Conclusion: </strong>¹⁸F-FDG PET/CT provides quantitative imaging indicators for preoperative evaluation and prognostic prediction in GC patients with PM.</p>","PeriodicalId":11611,"journal":{"name":"EJNMMI Research","volume":"15 1","pages":"46"},"PeriodicalIF":3.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12011703/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143972884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preclinical PET imaging in epileptogenesis: towards identification of biomarkers and therapeutic targets.","authors":"Nira Hernández-Martín, Ignacio Pozo-Cabanell, Rubén Fernández de la Rosa, Luis García-García, Francisca Gómez-Oliver, Miguel Ángel Pozo, Mirjam Brackhan, Pablo Bascuñana","doi":"10.1186/s13550-025-01237-3","DOIUrl":"https://doi.org/10.1186/s13550-025-01237-3","url":null,"abstract":"<p><strong>Background: </strong>Epilepsy is a neurological disorder that affects a significant portion of the global population. However, its complexity and the lack of biomarkers hinder the study of its etiology, resulting in a lack of effective treatments to slow down or halt disease development, also called epileptogenesis.</p><p><strong>Main body: </strong>Animal models have proven to be a crucial tool for studying epileptogenesis, many exhibiting cellular, molecular, and functional alterations that resemble those found in human patients. This review examines preclinical studies that have utilized positron emission tomography, a non-invasive neuroimaging technique that has demonstrated correlation with the pathological features and behavioral comorbidities of the disease and a high predictive value for the severity of epileptogenesis.</p><p><strong>Conclusion: </strong>Positron emission tomography imaging has fostered the knowledge of the mechanisms driving epileptogenesis. This translational technique might be crucial for identifying biomarkers of epilepsy, identifying novel treatment targets and selecting and monitoring patients for potential future therapies.</p>","PeriodicalId":11611,"journal":{"name":"EJNMMI Research","volume":"15 1","pages":"43"},"PeriodicalIF":3.1,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12008110/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144062852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of early chemotherapy response by combining static- and dynamic [¹⁸F]FDG-PET with diffusion-weighted MRI in subcutaneous patient-derived endometrial cancer mouse models.","authors":"Heidi Espedal, Jenny M Lyngstad, Hege F Berg, Marta E Hjelmeland, Kristine E Fasmer, Camilla Krakstad, Ingfrid S Haldorsen","doi":"10.1186/s13550-025-01235-5","DOIUrl":"https://doi.org/10.1186/s13550-025-01235-5","url":null,"abstract":"<p><strong>Background: </strong>The combination of carboplatin and paclitaxel is the standard chemotherapy for treatment of high-risk and recurrent endometrial cancer. Evaluation of treatment response by diagnostic imaging is routinely carried out months after start of treatment, and is based on changes in tumor size or appearance of new metastases. The aim of this study was to evaluate early chemotherapeutic response in two subcutaneous endometrial cancer mouse models generated from patient-derived organoids using static- and dynamic [¹⁸F]fluorodeoxyglucose ([¹⁸F]FDG) positron emission tomography (PET) and diffusion-weighted (DW) magnetic resonance imaging (MRI). Mice were injected bilaterally with endometrioid endometrial cancer grade 3 (EEC G3), International Federation of Gynaecology and Obstetrics (FIGO) stage 3C1 (Model A) or stage 1B (Model B) organoids (n = 15 mice). The mice were randomized into treatment (combined carboplatin and paclitaxel, n_A=8 / n_B=6 tumors) or control (saline, n_A=8 / n_B=8 tumors) groups. During tumor progression, the mice underwent T2-weighted (T2w) MRI, DW-MRI and dynamic [¹⁸F]FDG-PET at baseline/Day 0 (start of treatment), Day 3 (early) and Day 10 (endpoint) using a sequential PET-MRI small-animal scanner.</p><p><strong>Results: </strong>At endpoint, tumor volumes at T2w-MRI (vMRI) were lower in the treatment groups in both models (p ≤ 0.029). The tumor metabolic rate (MR_FDG) from dynamic PET, was significantly lower in the treatment group at the early timepoint (Day 3) and at the endpoint in Model A (p ≤ 0.042). In Model B, MR_FDG was similar for both groups at Day 3 and at endpoint (p≥0.217). The 10 tumor voxels with the highest standardised uptake value (SUV₁₀) from static [¹⁸F]-FDG-PET was significantly lower at endpoint in the treatment groups in both models (p ≤ 0.041), but not at the early timepoint (p≥0.083). Similarly, the tumor apparent diffusion coefficient (ADC_mean) was significantly higher indicating treatment response at endpoint for treatment groups in both models (p ≤ 0.036).</p><p><strong>Conclusions: </strong>Multimodal imaging is feasible for evaluation of early signs of treatment response in preclinical subcutaneous endometrial cancer models. The novel MR_FDG dynamic PET imaging parameter seems most promising for detecting very early treatment response following chemotherapy.</p>","PeriodicalId":11611,"journal":{"name":"EJNMMI Research","volume":"15 1","pages":"45"},"PeriodicalIF":3.1,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12008091/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143972877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A fully automated, expert-perceptive image quality assessment system for whole-body [18F]FDG PET/CT.","authors":"Cong Zhang, Xin Gao, Xuebin Zheng, Jun Xie, Gang Feng, Yunchao Bao, Pengchen Gu, Chuan He, Ruimin Wang, Jiahe Tian","doi":"10.1186/s13550-025-01238-2","DOIUrl":"https://doi.org/10.1186/s13550-025-01238-2","url":null,"abstract":"<p><strong>Background: </strong>The quality of clinical PET/CT images is critical for both accurate diagnosis and image-based research. However, current image quality assessment (IQA) methods predominantly rely on handcrafted features and region-specific analyses, thereby limiting automation in whole-body and multicenter evaluations. This study aims to develop an expert-perceptive deep learning-based IQA system for [18F]FDG PET/CT to tackle the lack of automated, interpretable assessments of clinical whole-body PET/CT image quality.</p><p><strong>Methods: </strong>This retrospective multicenter study included clinical whole-body [18F]FDG PET/CT scans from 718 patients. Automated identification and localization algorithms were applied to select predefined pairs of PET and CT slices from whole-body images. Fifteen experienced experts, trained to conduct blinded slice-level subjective assessments, provided average visual scores as reference standards. Using the MANIQA framework, the developed IQA model integrates the Vision Transformer, Transposed Attention, and Scale Swin Transformer Blocks to categorize PET and CT images into five quality classes. The model's correlation, consistency, and accuracy with expert evaluations on both PET and CT test sets were statistically analysed to assess the system's IQA performance. Additionally, the model's ability to distinguish high-quality images was evaluated using receiver operating characteristic (ROC) curves.</p><p><strong>Results: </strong>The IQA model demonstrated high accuracy in predicting image quality categories and showed strong concordance with expert evaluations of PET/CT image quality. In predicting slice-level image quality across all body regions, the model achieved an average accuracy of 0.832 for PET and 0.902 for CT. The model's scores showed substantial agreement with expert assessments, achieving average Spearman coefficients (ρ) of 0.891 for PET and 0.624 for CT, while the average Intraclass Correlation Coefficient (ICC) reached 0.953 for PET and 0.92 for CT. The PET IQA model demonstrated strong discriminative performance, achieving an area under the curve (AUC) of ≥ 0.88 for both the thoracic and abdominal regions.</p><p><strong>Conclusions: </strong>This fully automated IQA system provides a robust and comprehensive framework for the objective evaluation of clinical image quality. Furthermore, it demonstrates significant potential as an impartial, expert-level tool for standardised multicenter clinical IQA.</p>","PeriodicalId":11611,"journal":{"name":"EJNMMI Research","volume":"15 1","pages":"42"},"PeriodicalIF":3.1,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12008089/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143969093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PET-based response assessment criteria for diffuse gliomas (PET RANO 1.0): methodological application in [¹⁸F]-FDOPA PET imaging.","authors":"Guilhem Stien, Adeline Zinsz, Shamimeh Ahrari, Luc Taillandier, Marie Blonski, Laetitia Imbert, Timothée Zaragori, Antoine Verger","doi":"10.1186/s13550-025-01239-1","DOIUrl":"https://doi.org/10.1186/s13550-025-01239-1","url":null,"abstract":"<p><strong>Background: </strong>The Response Assessment in Neuro-Oncology (RANO) group recently reported PET-based response assessment criteria for diffuse gliomas (PET RANO 1.0). The objective of this study was to evaluate the methodological application of these criteria for the amino acid [¹⁸F]-FDOPA radiotracer. Patients with confirmed glioma who underwent at least one baseline [¹⁸F]-FDOPA PET scan were retrospectively included. The PET RANO 1.0 criteria were evaluated regarding their methodological application. Patients with at least one follow-up PET scan were evaluated with the PET RANO 1.0 criteria as compared to the routine interpretation of two experts not using the PET RANO 1.0 criteria, defined as the reference. The different PET parameters included in the PET RANO 1.0 criteria were evaluated separately regarding their contribution.</p><p><strong>Results: </strong>Ninety patients (52.0 ± 15.3 years old, 56% women) were included in this study regards to the methodology of application of the PET RANO 1.0 criteria, with 86% of patients presenting measurable diseases. Among these patients, 65 patients were evaluated for the comparison between the PET RANO 1.0 criteria and the expert interpretation: a concordance of 80%, equivalent for newly diagnosed and recurrent gliomas, as well as IDH-mutant vs. IDH-wildtype gliomas was found. The metabolic tumor volume represented the most contributive parameter (71% of cases) to the definition of response according to the PET RANO 1.0 criteria. Striatum infiltration, post-treatment related effects, measurable diseases criteria and thresholds for PET RANO 1.0 criteria were related to the cases discordances.</p><p><strong>Conclusion: </strong>The PET RANO 1.0 criteria can be applied with [¹⁸F]-FDOPA imaging, with a reasonable concordance with results of an expert interpretation. Description of discordant cases should help to improve future PET RANO 1.0 criteria updating.</p>","PeriodicalId":11611,"journal":{"name":"EJNMMI Research","volume":"15 1","pages":"44"},"PeriodicalIF":3.1,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12008083/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143983982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of early response to neoadjuvant chemotherapy in multi-site high-grade serous ovarian cancer using hyperpolarized-¹³C MRI.","authors":"Lucian Beer, Vlad Bura, Stephan Ursprung, Ramona Woitek, Mary A McLean, Joo Ern Ang, Mercedes Jimenez-Linan, Andrew B Gill, Joshua Kaggie, Matthew Locke, Amy Frary, Johanna Field-Rayner, Ilse Patterson, Marika Reinius, Martin J Graves, Surrin Deen, Gabriel Funingana, Leonardo Rundo, Andrew Priest, Luigi Aloj, Roido Manavaki, Iosif A Mendichovszky, Fraser Robb, Rolf F Schulte, Dominique-Laurent Couturier, Clive S D'Santos, Valar Franklin, Kamal Kishore, Iris Allajbeu, Carolin Sauer, Ferdia A Gallagher, Kevin M Brindle, James D Brenton, Evis Sala","doi":"10.1186/s13550-025-01219-5","DOIUrl":"https://doi.org/10.1186/s13550-025-01219-5","url":null,"abstract":"<p><strong>Background: </strong>To evaluate the capability of hyperpolarized [1-¹³C] pyruvate MRI to predict pathologic response to neoadjuvant treatment in multi-site abdominopelvic disease of high-grade serous ovarian cancer (HGSOC) patients and to compare ¹³C MRI and [¹⁸F]-FDG PET/CT measurements for detecting early treatment response. We recruited eight patients with HGSOC in this prospective study who underwent ¹³C MRI and [¹⁸F]-FDG PET/CT before and after the first cycle of neoadjuvant chemotherapy treatment (NACT). Imaging parameters were compared with clinical and histophatologic parameters.</p><p><strong>Results: </strong>We demonstrate here that ¹³C MRI of hyperpolarized [1-¹³C]pyruvate metabolism in multiple abdominal metastases resulted in rapid labeling of the endogenous tumor lactate pool. The rate of labeling was similar between the different anatomical disease sites and independent of tumor volume. The apparent rate constant describing exchange of ¹³C label between pyruvate and lactate (k_PL) was positively correlated with PET standard uptake values (SUV_max) for [¹⁸F]-FDG in metastatic tumor deposits in the ovary/pelvis (R = 0.471, P = 0.02). Decreased lactate labeling could be detected after the first cycle of neoadjuvant chemotherapy and was associated with pathological response. There was no overall decrease in lactate labeling in a single patient who lacked a complete histopathologic response. k_PL was associated with cancer tissue LDHA concentration (rho = 0.641; P = 0.02).</p><p><strong>Conclusion: </strong>This exploratory study demonstrates the potential of ¹³C MRI measurements for assessing early response to neoadjuvant chemotherapy in patients with HGSOC.</p>","PeriodicalId":11611,"journal":{"name":"EJNMMI Research","volume":"15 1","pages":"40"},"PeriodicalIF":3.1,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12006644/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143970118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The prognostic value of CXCR4 PET/CT imaging in unilateral primary aldosteronism patients after adrenalectomy.","authors":"Shuai Shao, Haozhe Xu, Zhuo Xing, Yulong Hong, Xuan Yin, Jianguang Luo, Kai Ai, Xin Su, Xiaowei Ma, Yuan Li","doi":"10.1186/s13550-025-01242-6","DOIUrl":"https://doi.org/10.1186/s13550-025-01242-6","url":null,"abstract":"<p><strong>Background: </strong>CXCR4 PET/CT imaging has emerged as a tool for diagnosis and subtyping of primary aldosteronism (PA). But its prognostic value for postoperative blood pressure recovery has not been fully discussed.</p><p><strong>Results: </strong>The lesional SUVmax to the contralateral adrenal tissue SUVmean ratio (LCR) was identified as an independent predictor of clinical success at both the 3-month and 6-month assessments. The AUC for LCR was 0.894 at the 3-month and 0.832 at the 6-month. Patients were divided into high and low LCR groups according to the optimal cut-off of 3.240. The high LCR group exhibited elevated CXCR4 and CYP11B2 expression, higher PAC level, a greater probability of achieving complete clinical success compared to the low LCR group. Moreover, LCR was correlated with lateralization index and contralateral suppression index.</p><p><strong>Conclusions: </strong>LCR is a reliable independent predictor of postoperative blood pressure recovery in PA. Patients with LCR over 3.240 may benefit more from adrenalectomy. We recommend increased utilization of CXCR4 PET/CT for patients with PA.</p><p><strong>Registration: </strong>ChiCTR2200062844. Registered 20 August 2022.</p>","PeriodicalId":11611,"journal":{"name":"EJNMMI Research","volume":"15 1","pages":"41"},"PeriodicalIF":3.1,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12006604/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143978413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI may help to predict thyroid nodule malignancy based on radiomics features from [¹⁸F]FDG PET/CT.","authors":"Krystian Ślusarz, Mikolaj Buchwald, Adrian Szczeszek, Szymon Kupinski, Anna Gramek-Jedwabna, Wojciech Andrzejewski, Juliusz Pukacki, Robert Pękal, Marek Ruchała, Rafał Czepczyński, Cezary Mazurek","doi":"10.1186/s13550-025-01228-4","DOIUrl":"https://doi.org/10.1186/s13550-025-01228-4","url":null,"abstract":"<p><strong>Background: </strong>The number of thyroid cancer diagnoses has been increasing for several decades, with a significant part of cases being detected incidentally (thyroid incidentaloma, TI) by imaging studies performed for reasons other than thyroid disease, including PET/CT with [¹⁸F]FDG. The chacteristics of the detected TI cannot be determined solely on the basis of conventional parameters used in everyday clinical practice, such as SUV_max. In recent years, there has been a growing interest in radiomics, which is a quantitative method of analyzing radiological images based on the analysis of image texture. Textural analysis may be helpful, as it allows to characterize features invisible to the physician with the naked eye.</p><p><strong>Results: </strong>Of the 54 patients who presented focal [¹⁸F]FDG-avid TI and had subsequent fine needle aspiration biopsy, 4 patients were excluded from the analysis due to the unavailability of the final diagnostic information. Hence, in the final analysis, data from 50 patients were used (39 females and 11 males) with a mean age of 58.5 ± 11.26. Of these 50 patients, 11 (22.0%) [¹⁸F]FDG-avid nodules were diagnosed as malignant. The performance of the XGBoost model in assessing [¹⁸F]FDG-avid TI was similar (0.846 [confidence interval, CI, 95% 0.737-0.956]) to SUV_max (0.797 [CI 95%: 0.622-0.973]; p = 0.60).</p><p><strong>Conclusions: </strong>With an AI-based algorithm using radiomics features it is possible to detect the malignancy of thyroid nodule. However, no statistically significant differences were observed between the AI and radiomics approach, and when using a conventional measure, i.e., SUV_max.</p>","PeriodicalId":11611,"journal":{"name":"EJNMMI Research","volume":"15 1","pages":"39"},"PeriodicalIF":3.1,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11992293/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143987101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prostate-specific membrane antigen (PSMA) expression in primary and metastatic renal cell cancer (UroCCR-65 study).","authors":"Salma Binzaqr, David Kryza, Anne-Laure Giraudet, Jean Christophe Bernhard, Marine Gross-Goupil, Mokrane Yacoub, Gaelle Margue, Elif Hindié, Clément Morgat","doi":"10.1186/s13550-025-01232-8","DOIUrl":"https://doi.org/10.1186/s13550-025-01232-8","url":null,"abstract":"<p><strong>Background: </strong>Prostate-specific membrane antigen (PSMA) has been shown to be overexpressed in the neo-vasculature of renal cancers. However, studies investigating the pattern of PSMA expression in primary RCC and RCC metastases according to metastatic sites are rare. 44 frozen samples of RCC, 19 primaries (9 clear cell (cc) RCC, 7 papillary (pap) RCC, and 3 chromophobe (ch) RCC) and 25 (24 samples have ccRCC histology and one is unclassified) unpaired metastases (8 from adrenals, 8 from bones, 2 from lungs, 2 from liver and 5 others (1 lymph node, 1 pancreas, 1 brain, 1 gallbladder and 1 muscle)), were available from the UroCCR project (NCT03293563). PSMA expression was assessed by autoradiography using [¹⁷⁷Lu]Lu-PSMA-617 as binding agent and the specific binding (total binding-non-specific binding) was calculated and expressed as a percentage of total binding. A patient suffering from metastatic ccRCC was also administered [⁶⁸Ga]Ga-PSMA-11 to evaluate PSMA expression.</p><p><strong>Results: </strong>The mean specific binding was 28.9 ± 40.4% for primary renal cancer and 65.0 ± 38.9% for metastasis. Regarding histology, high PSMA expression was depicted in 33.3% of ccRCC, 33.3% of chRCC and 57.1% of papRCC. PSMA was more frequently expressed in primary samples of papRCC histology with renal capsule invasion (p = 0.0286). A higher PSMA-specific binding and a higher number of samples with high PSMA-expression were depicted in metastatic samples. Bone metastasis showed lower binding than other metastatic sites combined (p = 0.0005). The patient suffering from metastatic ccRCC showed high [⁶⁸Ga]Ga-PSMA-11 uptake on known distant metastases and additional site uncovered.</p><p><strong>Conclusion: </strong>PSMA showed high expression in metastases of ccRCC.</p><p><strong>Clinical trial registration: </strong>NCT, NCT03293563, prospectively registered September 20, 2017, http://www.</p><p><strong>Clinicaltrials: </strong>gov .</p>","PeriodicalId":11611,"journal":{"name":"EJNMMI Research","volume":"15 1","pages":"38"},"PeriodicalIF":3.1,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11981970/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143958947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}