[Imaging of pancreatic neuroendocrine tumors]. / Bildgebung von neuroendokrinen Tumoren des Pankreas.

BACKGROUND: Neuroendocrine tumors of the pancreas have a broad biological spectrum. The treatment decision is based on an optimal diagnosis with regard to the local findings and possible locoregional and distant metastases. In addition to purely morphologic imaging procedures, functional parameters are playing an increasingly important role in imaging. OBJECTIVES: Prerequisites for optimal imaging of the pancreas, technical principles are provided, and the advantages and disadvantages of common cross-sectional imaging techniques as well as clinical indications for these special imaging methods are discussed. MATERIALS AND METHODS: Guidelines, basic and review papers will be analyzed. RESULTS: Neuroendocrine tumors of the pancreas have a broad imaging spectrum. Therefore, there is a need for multimodality imaging in which morphologic and functional techniques support each other. While positron emission tomography/computed tomography (PET/CT) can determine the presence of one or more lesions and its/their functional status of the tumor, magnetic resonance imaging (MRI) efficiently identifies the location, relationship to the main duct and the presence of liver metastases. CT allows a better vascular evaluation, even in the presence of anatomical variants as well as sensitive detection of lung metastases. CONCLUSIONS: Knowledge of the optimal combination of imaging modalities including clinical and histopathologic results and dedicated imaging techniques is essential to achieve an accurate diagnosis to optimize treatment decision-making and to assess therapy response.

[68Ga]Ga-FAPI-46 PET/CT for penile cancer - a feasibility study.

PURPOSE: Penile cancer is a rare entity and has a good prognosis in localized stage. Delayed surgical treatment of lymphatic disease is associated with poor overall survival but conventional imaging cannot detect occult lymph node metastasis sufficiently. Imaging cancer related fibroblasts has shown promising results as non-invasive staging tool in various tumor entities but has not yet been evaluated in penile cancer. METHODS: In this single-center pilot study, patients planned for surgical treatment for penile cancer underwent preoperatively [68Ga]Ga-FAPI-46 PET/CT. Post-operative histopathology was compared to [68Ga]Ga-FAPI-46 PET/CT results. RESULTS: From January 2022 to June 2022, a total number 11 patients with histopathologically proven penile cancer underwent surgery and received [68Ga]Ga-FAPI-46 PET/CT prior therapy. 8 primary tumor sites and 4 lymph node regions were analyzed. FAPI uptake was increased on primary tumor site (SUVmax 16.2 (9.1 - 25.8)). Histopathological proven lymph node regions showed highly increased FAPI uptakes (SUVmax 17.9 (16.4 - 23.5) on [68Ga]Ga-FAPI-46 PET/CT. CONCLUSION: In this first pilot cohort, there were no false-positive FAPI uptake which might allow the detection of occult lymph node metastasis by [68Ga]Ga-FAPI-46 PET/CT and might consequently lead to omitting lymph node regions during surgery that had no increased FAPI uptake pre-operatively.

Functional maturation and longitudinal imaging of intraportal neonatal porcine islet grafts in genetically diabetic pigs.

Allogeneic intraportal islet transplantation (ITx) has become an established treatment for patients with poorly controlled type 1 diabetes. However, the loss of viable beta-cell mass after transplantation remains a major challenge. Therefore, noninvasive imaging methods for long-term monitoring of the transplant fate are required. In this study, [68Ga]Ga-DOTA-exendin-4 positron emission tomography/computed tomography (PET/CT) was used for repeated monitoring of allogeneic neonatal porcine islets (NPI) after intraportal transplantation into immunosuppressed genetically diabetic pigs. NPI transplantation (3320-15,000 islet equivalents per kg body weight) led to a reduced need for exogenous insulin therapy and finally normalization of blood glucose levels in 3 out of 4 animals after 5 to 10 weeks. Longitudinal PET/CT measurements revealed a significant increase in standard uptake values in graft-bearing livers. Histologic analysis confirmed the presence of well-engrafted, mature islet clusters in the transplanted livers. Our study presents a novel large animal model for allogeneic intraportal ITx. A relatively small dose of NPIs was sufficient to normalize blood glucose levels in a clinically relevant diabetic pig model. [68Ga]Ga-DOTA-exendin-4 PET/CT proved to be efficacious for longitudinal monitoring of islet transplants. Thus, it could play a crucial role in optimizing ITx as a curative therapy for type 1 diabetes.

[68 Ga]Ga-FAPI-46 PET/CT for locoregional lymph node staging in urothelial carcinoma of the bladder prior to cystectomy: initial experiences from a pilot analysis.

INTRODUCTION: [68 Ga]Ga-FAPI-46 PET/CT is a novel hybrid imaging method that previously showed additional diagnostic value in the assessment of distant urothelial carcinoma lesions. We hypothesized that patients with bladder cancer benefit from [68 Ga]Ga-FAPI-46 PET/CT prior to radical cystectomy for locoregional lymph node staging. MATERIALS AND METHODS: Eighteen patients underwent [68 Ga]Ga-FAPI-46 PET/CT for evaluation of lymph node (LN) status in predefined LN regions. Two hundred twenty-nine intraoperatively removed LN served as histopathological reference standard. RESULTS: Urothelial carcinoma (UC) spread was found in ten LN in seven different regions (14.3%). Hereby, [68 Ga]Ga-FAPI-46 PET/CT was positive in four out of seven regions (57.1%) and showed significantly increased FAPI uptake compared to non-pathological regions. In the remaining three out of seven (42.9%) regions, [68 Ga]Ga-FAPI-46 PET/CT was rated negative since no pathological increased FAPI uptake was detected or the proximity of the urinary tract prevented a differentiation from physiological uptake. CT was inconspicuous in these three regions. In total, two FAP-positive LN regions were found without histopathological counterpart. Overall, sensitivity, specificity, positive predictive value, and negative predictive value were 57.1%, 95.2%, 66.7%, and 93.0% for PET imaging. CONCLUSION: In summary, this innovative [68 Ga]Ga-FAPI-46 PET/CT method showed high specificity and negative predictive value in patients with bladder UC with a future potential to optimize therapy planning.

Identification of impactful imaging biomarker: Clinical applications for breast and prostate carcinoma. / Ermittlung aussagekräftiger Bildgebungsbiomarker: Klinische Anwendungen bei Mamma- und Prostatakarzinomen.

BACKGROUND: Imaging biomarkers are quantitative parameters from imaging modalities, which are collected noninvasively, allow conclusions about physiological and pathophysiological processes, and may consist of single (monoparametric) or multiple parameters (bi- or multiparametric). METHOD: This review aims to present the state of the art for the quantification of multimodal and multiparametric imaging biomarkers. Here, the use of biomarkers using artificial intelligence will be addressed and the clinical application of imaging biomarkers in breast and prostate cancers will be explained. For the preparation of the review article, an extensive literature search was performed based on Pubmed, Web of Science and Google Scholar. The results were evaluated and discussed for consistency and generality. RESULTS AND CONCLUSION: Different imaging biomarkers (multiparametric) are quantified based on the use of complementary imaging modalities (multimodal) from radiology, nuclear medicine, or hybrid imaging. From these techniques, parameters are determined at the morphological (e. g., size), functional (e. g., vascularization or diffusion), metabolic (e. g., glucose metabolism), or molecular (e. g., expression of prostate specific membrane antigen, PSMA) level. The integration and weighting of imaging biomarkers are increasingly being performed with artificial intelligence, using machine learning algorithms. In this way, the clinical application of imaging biomarkers is increasing, as illustrated by the diagnosis of breast and prostate cancers. KEY POINTS: · Imaging biomarkers are quantitative parameters to detect physiological and pathophysiological processes.. · Imaging biomarkers from multimodality and multiparametric imaging are integrated using artificial intelligence algorithms.. · Quantitative imaging parameters are a fundamental component of diagnostics for all tumor entities, such as for mammary and prostate carcinomas.. CITATION FORMAT: · Bäuerle T, Dietzel M, Pinker K et al. Identification of impactful imaging biomarker: Clinical applications for breast and prostate carcinoma. Fortschr Röntgenstr 2024; 196: 354 - 362.

Implementing Artificial Intelligence for Emergency Radiology Impacts Physicians' Knowledge and Perception: A Prospective Pre- and Post-Analysis.

PURPOSE: The aim of this study was to evaluate the impact of implementing an artificial intelligence (AI) solution for emergency radiology into clinical routine on physicians' perception and knowledge. MATERIALS AND METHODS: A prospective interventional survey was performed pre-implementation and 3 months post-implementation of an AI algorithm for fracture detection on radiographs in late 2022. Radiologists and traumatologists were asked about their knowledge and perception of AI on a 7-point Likert scale (-3, "strongly disagree"; +3, "strongly agree"). Self-generated identification codes allowed matching the same individuals pre-intervention and post-intervention, and using Wilcoxon signed rank test for paired data. RESULTS: A total of 47/71 matched participants completed both surveys (66% follow-up rate) and were eligible for analysis (34 radiologists [72%], 13 traumatologists [28%], 15 women [32%]; mean age, 34.8 ± 7.8 years). Postintervention, there was an increase that AI "reduced missed findings" (1.28 [pre] vs 1.94 [post], P = 0.003) and made readers "safer" (1.21 vs 1.64, P = 0.048), but not "faster" (0.98 vs 1.21, P = 0.261). There was a rising disagreement that AI could "replace the radiological report" (-2.04 vs -2.34, P = 0.038), as well as an increase in self-reported knowledge about "clinical AI," its "chances," and its "risks" (0.40 vs 1.00, 1.21 vs 1.70, and 0.96 vs 1.34; all P 's ≤ 0.028). Radiologists used AI results more frequently than traumatologists ( P < 0.001) and rated benefits higher (all P 's ≤ 0.038), whereas senior physicians were less likely to use AI or endorse its benefits (negative correlation with age, -0.35 to 0.30; all P 's ≤ 0.046). CONCLUSIONS: Implementing AI for emergency radiology into clinical routine has an educative aspect and underlines the concept of AI as a "second reader," to support and not replace physicians.

Reliability and practicability of PSMA-RADS 1.0 for structured reporting of PSMA-PET/CT scans in prostate cancer patients.

OBJECTIVES: As structured reporting is increasingly used in the evaluation of prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA-PET/CT) for prostate cancer, there is a need to assess the reliability of these frameworks. This study aimed to evaluate the intra- and interreader agreement among readers with varying levels of experience using PSMA-RADS 1.0 for interpreting PSMA-PET/CT scans, even when blinded to clinical data, and therefore to determine the feasibility of implementing this reporting system in clinical practice. METHODS: PSMA-PET/CT scans of 103 patients were independently evaluated by 4 readers with different levels of experience according to the reporting and data system (RADS) for PSMA-PET/CT imaging PSMA-RADS 1.0 at 2 time points within 6 weeks. For each scan, a maximum of five target lesions were freely chosen and stratified according to PSMA-RADS 1.0. Overall scan score and compartment-based scores were assessed. Intra- and interreader agreement was determined using the intraclass correlation coefficient (ICC). RESULTS: PSMA-RADS 1.0 demonstrated excellent interreader agreement for both overall scan scores (ICC ≥ 0.91) and compartment-based scores (ICC ≥ 0.93) across all four readers. The framework showed excellent intrareader agreement for overall scan scores (ICC ≥ 0.86) and compartment-based scores (ICC ≥ 0.95), even among readers with varying levels of experience. CONCLUSIONS: PSMA-RADS 1.0 is a reliable method for assessing PSMA-PET/CT with strong consistency and agreement among readers. It shows great potential for establishing a standard approach to diagnosing and planning treatment for prostate cancer patients, and can be used confidently even by readers with less experience. CLINICAL RELEVANCE STATEMENT: This study underlines that PSMA-RADS 1.0 is a valuable and highly reliable scoring system for PSMA-PET/CT scans of prostate cancer patients and can be used confidently by radiologists with different levels of experience in routine clinical practice. KEY POINTS: PSMA-RADS version 1.0 is a scoring system for PSMA-PET/CT scans. Its reproducibility needs to be analyzed in order to make it applicable to clinical practice. Excellent interreader and intrareader agreement for overall scan scores and compartment-based scores using PSMA-RADS 1.0 were seen in readers with varying levels of experience. PSMA-RADS 1.0 is a reliable tool for accurately diagnosing and planning treatment for prostate cancer patients, and can be used confidently in clinical routine.

Artificial Intelligence in Oncological Hybrid Imaging.

BACKGROUND: Artificial intelligence (AI) applications have become increasingly relevant across a broad spectrum of settings in medical imaging. Due to the large amount of imaging data that is generated in oncological hybrid imaging, AI applications are desirable for lesion detection and characterization in primary staging, therapy monitoring, and recurrence detection. Given the rapid developments in machine learning (ML) and deep learning (DL) methods, the role of AI will have significant impact on the imaging workflow and will eventually improve clinical decision making and outcomes. METHODS AND RESULTS: The first part of this narrative review discusses current research with an introduction to artificial intelligence in oncological hybrid imaging and key concepts in data science. The second part reviews relevant examples with a focus on applications in oncology as well as discussion of challenges and current limitations. CONCLUSION: AI applications have the potential to leverage the diagnostic data stream with high efficiency and depth to facilitate automated lesion detection, characterization, and therapy monitoring to ultimately improve quality and efficiency throughout the medical imaging workflow. The goal is to generate reproducible, structured, quantitative diagnostic data for evidence-based therapy guidance in oncology. However, significant challenges remain regarding application development, benchmarking, and clinical implementation. KEY POINTS: · Hybrid imaging generates a large amount of multimodality medical imaging data with high complexity and depth.. · Advanced tools are required to enable fast and cost-efficient processing along the whole radiology value chain.. · AI applications promise to facilitate the assessment of oncological disease in hybrid imaging with high quality and efficiency for lesion detection, characterization, and response assessment. The goal is to generate reproducible, structured, quantitative diagnostic data for evidence-based oncological therapy guidance.. · Selected applications in three oncological entities (lung, prostate, and neuroendocrine tumors) demonstrate how AI algorithms may impact imaging-based tasks in hybrid imaging and potentially guide clinical decision making..

Next-generation PET/CT imaging in meningioma-first clinical experiences using the novel SSTR-targeting peptide [18F]SiTATE.

BACKGROUND: Somatostatin-receptor (SSTR)-targeted PET/CT provides important clinical information in addition to standard imaging in meningioma patients. [18F]SiTATE is a novel, 18F-labeled SSTR-targeting peptide with superior imaging properties according to preliminary data. We provide the first [18F]SiTATE PET/CT data of a large cohort of meningioma patients. METHODS: Patients with known or suspected meningioma undergoing [18F]SiTATE PET/CT were included. Uptake intensity (SUV) of meningiomas, non-meningioma lesions, and healthy organs were assessed using a 50% isocontour volume of interest (VOI) or a spherical VOI, respectively. Also, trans-osseous extension on PET/CT was assessed. RESULTS: A total of 107 patients with 117 [18F]SiTATE PET/CT scans were included. Overall, 231 meningioma lesions and 61 non-meningioma lesions (e.g., post-therapeutic changes) were analyzed. Physiological uptake was lowest in healthy brain tissue, followed by bone marrow, parotid, and pituitary (SUVmean 0.06 ± 0.04 vs. 1.4 ± 0.9 vs. 1.6 ± 1.0 vs. 9.8 ± 4.6; p < 0.001). Meningiomas showed significantly higher uptake than non-meningioma lesions (SUVmax 11.6 ± 10.6 vs. 4.0 ± 3.3, p < 0.001). Meningiomas showed significantly higher uptake than non-meningioma lesions (SUVmax 11.6±10.6 vs. 4.0±3.3, p<0.001). 93/231 (40.3%) meningiomas showed partial trans-osseous extension and 34/231 (14.7%) predominant intra-osseous extension. 59/231 (25.6%) meningioma lesions found on PET/CT had not been reported on previous standard imaging. CONCLUSION: This is the first PET/CT study using an 18F-labeled SSTR-ligand in meningioma patients: [18F]SiTATE provides extraordinary contrast in meningioma compared to healthy tissue and non-meningioma lesions, which leads to a high detection rate of so far unknown meningioma sites and osseous involvement. Having in mind the advantageous logistic features of 18F-labeled compared to 68Ga-labeled compounds (e.g., longer half-life and large-badge production), [18F]SiTATE has the potential to foster a widespread use of SSTR-targeted imaging in neuro-oncology.

Diagnostic performance of PET/CT in the detection of liver metastases in well-differentiated NETs.

BACKGROUND: The aim of this retrospective study was to compare the diagnostic accuracy of somatostatin receptor (SSR)-PET/CT to liver MRI as reference standard in the evaluation of hepatic involvement in neuroendocrine tumors (NET). METHODS: An institutional database was screened for "SSR" imaging studies between 2006 and 2021. 1000 NET Patients (grade 1/2) with 2383 SSR-PET/CT studies and matching liver MRI in an interval of +3 months were identified. Medical reports of SSR-PET/CT and MRI were retrospectively evaluated regarding hepatic involvement and either confirmed by both or observed in MRI but not in SSR-PET/CT (false-negative) or in SSR-PET but not in MRI (false-positive). RESULTS: Metastatic hepatic involvement was reported in 1650 (69.2%) of the total 2383 SSR-PET/CT imaging studies, whereas MRI detected hepatic involvement in 1685 (70.7%) cases. There were 51 (2.1%) false-negative and 16 (0.7%) false-positive cases. In case of discrepant reports, MRI and PET/CT were reviewed side by side for consensus reading. SSR-PET/CT demonstrated a sensitivity of 97.0% (95%CI: 96.0%, 97.7%), a specificity of 97.7% (95%CI: 96.3%, 98.7%), a PPV of 99.0% (95%CI: 98.4%, 99.4%) and NPV of 93.0% (95%CI: 91.0, 94.8%) in identifying hepatic involvement. The most frequent reason for false-negative results was the small size of lesions with the majority < 0.6 cm. CONCLUSION: This study confirms the high diagnostic accuracy of SSR-PET/CT in the detection of hepatic involvement in NET patients based on a patient-based analysis of metastatic hepatic involvement with a high sensitivity and specificity using liver MRI imaging as reference standard. However, one should be aware of possible pitfalls when a single imaging method is used in evaluating neuroendocrine liver metastases in patients.

Validation of the SSTR-RADS 1.0 for the structured interpretation of SSTR-PET/CT and treatment planning in neuroendocrine tumor (NET) patients.

OBJECTIVES: The recently proposed standardized reporting and data system for somatostatin receptor (SSTR)-targeted PET/CT SSTR-RADS 1.0 showed promising first results in the assessment of diagnosis and treatment planning with peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumors (NET). This study aimed to determine the intra- and interreader agreement of SSTR-RADS 1.0. METHODS: SSTR-PET/CT scans of 100 patients were independently evaluated by 4 readers with different levels of expertise according to the SSTR-RADS 1.0 criteria at 2 time points within 6 weeks. For each scan, a maximum of five target lesions were freely chosen by each reader (not more than three lesions per organ) and stratified according to the SSTR-RADS 1.0 criteria. Overall scan score and binary decision on PRRT were assessed. Intra- and interreader agreement was determined using the intraclass correlation coefficient (ICC). RESULTS: Interreader agreement using SSTR-RADS 1.0 for identical target lesions (ICC ≥ 0.91) and overall scan score (ICC ≥ 0.93) was excellent. The decision to state "functional imaging fulfills requirements for PRRT and qualifies patient as potential candidate for PRRT" also demonstrated excellent agreement among all readers (ICC ≥ 0.86). Intrareader agreement was excellent even among different experience levels when comparing target lesion-based scores (ICC ≥ 0.98), overall scan score (ICC ≥ 0.93), and decision for PRRT (ICC ≥ 0.88). CONCLUSION: SSTR-RADS 1.0 represents a highly reproducible and accurate system for stratifying SSTR-targeted PET/CT scans with high intra- and interreader agreement. The system is a promising approach to standardize the diagnosis and treatment planning in NET patients. KEY POINTS: • SSTR-RADS 1.0 offers high reproducibility and accuracy. • SSTR-RADS 1.0 is a promising method to standardize diagnosis and treatment planning for patients with NET.

Comparison of somatostatin receptor expression in patients with neuroendocrine tumours with and without somatostatin analogue treatment imaged with [18F]SiTATE.

Purpose: Somatostatin analogues (SSA) are frequently used in the treatment of neuroendocrine tumours. Recently, [18F]SiTATE entered the field of somatostatin receptor (SSR) positron emission tomography (PET)/computed tomography (CT) imaging. The purpose of this study was to compare the SSR-expression of differentiated gastroentero-pancreatic neuroendocrine tumours (GEP-NET) measured by [18F]SiTATE-PET/CT in patients with and without previous treatment with long-acting SSAs to evaluate if SSA treatment needs to be paused prior to [18F]SiTATE-PET/CT. Methods: 77 patients were examined with standardised [18F]SiTATE-PET/CT within clinical routine: 40 patients with long-acting SSAs up to 28 days prior to PET/CT examination and 37 patients without pre-treatment with SSAs. Maximum and mean standardized uptake values (SUVmax and SUVmean) of tumours and metastases (liver, lymphnode, mesenteric/peritoneal and bones) as well as representative background tissues (liver, spleen, adrenal gland, blood pool, small intestine, lung, bone) were measured, SUV ratios (SUVR) were calculated between tumours/metastases and liver, likewise between tumours/metastases and corresponding specific background, and compared between the two groups. Results: SUVmean of liver (5.4 ± 1.5 vs. 6.8 ± 1.8) and spleen (17.5 ± 6.8 vs. 36.7 ± 10.3) were significantly lower (p < 0.001) and SUVmean of blood pool (1.7 ± 0.6 vs. 1.3 ± 0.3) was significantly higher (p < 0.001) in patients with SSA pre-treatment compared to patients without. No significant differences between tumour-to-liver and specific tumour-to-background SUVRs were observed between both groups (all p > 0.05). Conclusion: In patients previously treated with SSAs, a significantly lower SSR expression ([18F]SiTATE uptake) in normal liver and spleen tissue was observed, as previously reported for 68Ga-labelled SSAs, without significant reduction of tumour-to-background contrast. Therefore, there is no evidence that SSA treatment needs to be paused prior to [18F]SiTATE-PET/CT.

Artificial Intelligence in Oncological Hybrid Imaging.

BACKGROUND: Artificial intelligence (AI) applications have become increasingly relevant across a broad spectrum of settings in medical imaging. Due to the large amount of imaging data that is generated in oncological hybrid imaging, AI applications are desirable for lesion detection and characterization in primary staging, therapy monitoring, and recurrence detection. Given the rapid developments in machine learning (ML) and deep learning (DL) methods, the role of AI will have significant impact on the imaging workflow and will eventually improve clinical decision making and outcomes. METHODS AND RESULTS: The first part of this narrative review discusses current research with an introduction to artificial intelligence in oncological hybrid imaging and key concepts in data science. The second part reviews relevant examples with a focus on applications in oncology as well as discussion of challenges and current limitations. CONCLUSION: AI applications have the potential to leverage the diagnostic data stream with high efficiency and depth to facilitate automated lesion detection, characterization, and therapy monitoring to ultimately improve quality and efficiency throughout the medical imaging workflow. The goal is to generate reproducible, structured, quantitative diagnostic data for evidence-based therapy guidance in oncology. However, significant challenges remain regarding application development, benchmarking, and clinical implementation. KEY POINTS: · Hybrid imaging generates a large amount of multimodality medical imaging data with high complexity and depth.. · Advanced tools are required to enable fast and cost-efficient processing along the whole radiology value chain.. · AI applications promise to facilitate the assessment of oncological disease in hybrid imaging with high quality and efficiency for lesion detection, characterization, and response assessment. The goal is to generate reproducible, structured, quantitative diagnostic data for evidence-based oncological therapy guidance.. · Selected applications in three oncological entities (lung, prostate, and neuroendocrine tumors) demonstrate how AI algorithms may impact imaging-based tasks in hybrid imaging and potentially guide clinical decision making.. CITATION FORMAT: · Feuerecker B, Heimer M, Geyer T et al. Artificial Intelligence in Oncological Hybrid Imaging. Fortschr Röntgenstr 2023; 195: 105 - 114.

Attitudes and perceptions of radiologists towards online (virtual) oncologic multidisciplinary team meetings during the COVID-19 pandemic-a survey of the European Society of Oncologic Imaging (ESOI).

OBJECTIVES: To explore radiologists' opinions regarding the shift from in-person oncologic multidisciplinary team meetings (MDTMs) to online MDTMs. To assess the perceived impact of online MDTMs, and to evaluate clinical and technical aspects of online meetings. METHODS: An online questionnaire including 24 questions was e-mailed to all European Society of Oncologic Imaging (ESOI) members. Questions targeted the structure and efficacy of online MDTMs, including benefits and limitations. RESULTS: A total of 204 radiologists responded to the survey. Responses were evaluated using descriptive statistical analysis. The majority (157/204; 77%) reported a shift to online MDTMs at the start of the pandemic. For the most part, this transition had a positive effect on maintaining and improving attendance. The majority of participants reported that online MDTMs provide the same clinical standard as in-person meetings, and that interdisciplinary discussion and review of imaging data were not hindered. Seventy three of 204 (35.8%) participants favour reverting to in-person MDTs, once safe to do so, while 7/204 (3.4%) prefer a continuation of online MDTMs. The majority (124/204, 60.8%) prefer a combination of physical and online MDTMs. CONCLUSIONS: Online MDTMs are a viable alternative to in-person meetings enabling continued timely high-quality provision of care with maintained coordination between specialties. They were accepted by the majority of surveyed radiologists who also favoured their continuation after the pandemic, preferably in combination with in-person meetings. An awareness of communication issues particular to online meetings is important. Training, improved software, and availability of support are essential to overcome technical and IT difficulties reported by participants. KEY POINTS: • Majority of surveyed radiologists reported shift from in-person to online oncologic MDT meetings during the COVID-19 pandemic. • The shift to online MDTMs was feasible and generally accepted by the radiologists surveyed with the majority reporting that online MDTMs provide the same clinical standard as in-person meetings. • Most would favour the return to in-person MDTMs but would also accept the continued use of online MDTMs following the end of the current pandemic.

A whole-body FDG-PET/CT Dataset with manually annotated Tumor Lesions.

We describe a publicly available dataset of annotated Positron Emission Tomography/Computed Tomography (PET/CT) studies. 1014 whole body Fluorodeoxyglucose (FDG)-PET/CT datasets (501 studies of patients with malignant lymphoma, melanoma and non small cell lung cancer (NSCLC) and 513 studies without PET-positive malignant lesions (negative controls)) acquired between 2014 and 2018 were included. All examinations were acquired on a single, state-of-the-art PET/CT scanner. The imaging protocol consisted of a whole-body FDG-PET acquisition and a corresponding diagnostic CT scan. All FDG-avid lesions identified as malignant based on the clinical PET/CT report were manually segmented on PET images in a slice-per-slice (3D) manner. We provide the anonymized original DICOM files of all studies as well as the corresponding DICOM segmentation masks. In addition, we provide scripts for image processing and conversion to different file formats (NIfTI, mha, hdf5). Primary diagnosis, age and sex are provided as non-imaging information. We demonstrate how this dataset can be used for deep learning-based automated analysis of PET/CT data and provide the trained deep learning model.

Preoperative Imaging with [18F]-Fluorocholine PET/CT in Primary Hyperparathyroidism.

Primary hyperparathyroidism (pHPT) is a common endocrine disorder due to hyperfunctioning parathyroid glands. To date, the only curing therapy is surgical removal of the dysfunctional gland, making correct detection and localization crucial in order to perform a minimally invasive parathyroidectomy. 18F-Fluorocholine positron emission tomography/computed tomography (18F-FCH PET/CT) has shown promising results for the detection of pHPT, suggesting superiority over conventional imaging with ultrasounds or scintigraphy. A total of 33 patients with pHPT who had negative or equivocal findings in conventional imaging received 18F-FCH PET/CT preoperatively and were retrospectively included. A pathological hyperfunctional parathyroid gland was diagnosed in 24 cases (positive PET, 72.7%), 4 cases showed equivocal choline uptake (equivocal PET, 12.1%), and in 5 cases, no enhanced choline uptake was evident (negative PET, 15.2%). Twelve of the twenty-four detected adenoma patients underwent surgery, and in all cases, a pathological parathyroid adenoma was resected at the site detected by PET/CT. Two of the six patients without pathological choline uptake who received a parathyroidectomy revealed no evidence of parathyroid adenoma tissue in the histopathological evaluation. This retrospective study analyzes 18F-FCH PET/CT in a challenging patient cohort with pHPT and negative or equivocal conventional imaging results and supports the use of 18F-FCH for the diagnosis of hyperfunctional parathyroid tissue, especially in this patient setting, with a 100% true positive and true negative detection rate. Our study further demonstrates the importance of 18F-FCH PET/CT for successful surgical guidance.