[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.

[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.

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.

Total Tumor Volume on 18F-PSMA-1007 PET as Additional Imaging Biomarker in mCRPC Patients Undergoing PSMA-Targeted Alpha Therapy with 225Ac-PSMA-I&T.

Background: PSMA-based alpha therapy using 225Ac-PSMA-I&T provides treatment for metastatic castration-resistant prostate cancer (mCRPC), even after the failure of 177Lu-PSMA radioligand therapy (RLT). In clinical routine, the total tumor volume (TTV) on PSMA PET impacts therapy outcomes and plays an increasing role in mCRPC patients. Hence, we aimed to assess TTV and its changes during 225Ac-PSMA-I&T RLT. Methods: mCRPC patients undergoing RLT with 225Ac-PSMA-I&T with available 18F-PSMA-1007 PET/CT prior to therapy initiation were included. TTV was assessed in all patients using established cut-off values. Image derived, clinical and biochemistry parameters (PSA, LDH, AP, pain score) were analyzed prior to and after two cycles of 225Ac-PSMA. Changes in TTV and further parameters were directly compared and then correlated with established response criteria, such as RECIST 1.1 or mPERCIST. Results: 13 mCRPC patients were included. The median overall survival (OS) was 10 months. Prior to 225Ac-PSMA RLT, there was no significant correlation between TTV with other clinical parameters (p > 0.05 each). Between short-term survivors (STS, <10 months OS) and long-term survivors (LTS, ≥10 months OS), TTV and PSA were comparable (p = 0.592 & p = 0.286, respectively), whereas AP was significantly lower in the LTS (p = 0.029). A total of 7/13 patients completed two cycles and underwent a follow-up 18F-PSMA-1007 PET/CT. Among these patients, there was a significant decrease in TTV (median 835 vs. 201 mL, p = 0.028) and PSA (median 687 ng/dL vs. 178 ng/dL, p = 0.018) after two cycles of 225Ac-PSMA RLT. Here, percentage changes of TTV after two cycles showed no direct correlation to all other clinical parameters (p > 0.05 each). In two patients, new PET-avid lesions were detected on 18F-PSMA-1007 PET/CT. However, TTV and PSA were decreasing or stable. Conclusion: PET-derived assessment of TTV is an easily applicable imaging biomarker independent of other established parameters prior to 225Ac-PSMA RLT in these preliminary follow-up data. Even after the failure of 177Lu-PSMA, patients with extensive TTV seem to profit from RLT. All but one patient who was eligible for ≥2 cycles of 225Ac-PSMA-RLT demonstrated drastic TTV decreases without direct correlation to other biomarkers, such as serum PSA changes. Changes in TTV might hence improve the response assessment compared to standard classifiers by reflecting the current tumor load independent of the occurrence of new lesions.

Complicated Carotid Artery Plaques and Risk of Recurrent Ischemic Stroke or TIA.

BACKGROUND: Complicated nonstenosing carotid artery plaques (CAPs) are an under-recognized cause of stroke. OBJECTIVES: The purpose of this study was to determine whether complicated CAP ipsilateral to acute ischemic anterior circulation stroke (icCAP) are associated with recurrent ischemic stroke or transient ischemic attack (TIA). METHODS: The CAPIAS (Carotid Plaque Imaging in Acute Stroke) multicenter study prospectively recruited patients with ischemic stroke restricted to the territory of a single carotid artery. Complicated (AHA-lesion type VI) CAP were defined by multisequence, contrast-enhanced carotid magnetic resonance imaging obtained within 10 days from stroke onset. Recurrent events were assessed after 3, 12, 24, and 36 months. The primary outcome was recurrent ischemic stroke or TIA. RESULTS: Among 196 patients enrolled, 104 patients had cryptogenic stroke and nonstenosing CAP. During a mean follow-up of 30 months, recurrent ischemic stroke or TIA occurred in 21 patients. Recurrent events were significantly more frequent in patients with icCAP than in patients without icCAP, both in the overall cohort (incidence rate [3-year interval]: 9.50 vs 3.61 per 100 patient-years; P = 0.025, log-rank test) and in patients with cryptogenic stroke (10.92 vs 1.82 per 100 patient-years; P = 0.003). The results were driven by ipsilateral events. A ruptured fibrous cap (HR: 4.91; 95% CI: 1.31-18.45; P = 0.018) and intraplaque hemorrhage (HR: 4.37; 95% CI: 1.20-15.97; P = 0.026) were associated with a significantly increased risk of recurrent events in patients with cryptogenic stroke. CONCLUSIONS: Complicated CAP ipsilateral to acute ischemic anterior circulation stroke are associated with an increased risk of recurrent ischemic stroke or TIA. Carotid plaque imaging identifies high-risk patients who might be suited for inclusion into future secondary prevention trials. (Carotid Plaque Imaging in Acute Stroke [CAPIAS]; NCT01284933).

Feasibility of [68Ga]Ga-FAPI-46 PET/CT for detection of nodal and hematogenous spread in high-grade urothelial carcinoma.

BACKGROUND: [68Ga]Ga-FAPI-46 is a novel positron emission tomography (PET) ligand that targets fibroblast activation protein (FAP) expression as FAP inhibitor (FAPI) and could already show promising results in several tumor entities. It could be demonstrated that an increased FAP expression correlates with tumor aggressivity in urothelial carcinoma (UC). Given the limited value of [18F]FDG in UC, [68Ga]Ga-FAPI-46 could add diagnostic information in staging and response assessment in UC. We present the first data of [68Ga]Ga-FAPI-46 PET imaging in a pilot cohort of UC patients evaluating uptake characteristics in metastases and primary tumors. METHODS: Fifteen patients with UC prior to or after local treatment underwent [68Ga]Ga-FAPI-46 PET/CT imaging for detection of metastatic spread. We compared the biodistribution in non-affected organs and tumor uptake of UC lesions by standard uptake value measurements (SUVmean and SUVmax). Additionally, metastatic sites on PET were compared to its morphological correlate on contrast-enhanced computed tomography (CT). RESULTS: Overall, 64 tumor sites were detected on PET and/or CT. The highest uptake intensity was noted at the primary site (SUVmax 20.8 (range, 8.1-27.8)) followed by lymph node metastases (SUVmax 10.6 (range, 4.7-29.1)). In 4/15 (26.7%) patients there were [68Ga]Ga-FAPI-46-positive lesions that were missed on standard routine CT imaging. On the other hand, 2/15 patients had suspicious prominent bipulmonary nodules as well as pelvic lymph nodes previously rated as suspicious for metastatic spread on CT, but without increased FAPI expression; here histopathology excluded malignancy. CONCLUSION: [68Ga]Ga-FAPI-46 PET shows distinctly elevated uptake in UC lesions. Therefore, the tracer has potential as a promising new biomarker in metastatic UC patients, as [68Ga]Ga-FAPI-46 PET might improve detection of metastatic sites compared to CT alone. These findings highly emphasize larger studies investigating FAPI imaging in UC patients.

Semi-Automatic MRI Feature Assessment in Small- and Medium-Volume Benign Prostatic Hyperplasia after Prostatic Artery Embolization.

(1) Background: To assess the treatment response of benign prostatic syndrome (BPS) following prostatic artery embolization (PAE) using a semi-automatic software analysis of magnetic resonance imaging (MRI) features and clinical indexes. (2) Methods: Prospective, monocenter study of MRI and clinical data of n = 27 patients with symptomatic BPS before and (1, 6, 12 months) after PAE. MRI analysis was performed using a dedicated semi-automatic software for segmentation of the central and the total gland (CG, TG), respectively; signal intensities (SIs) of T1-weighted (T1w), T2-weighted (T2w), and diffusion-weighted images (DWI), as well as intravesical prostatic protrusion (IPP) and prostatic volumes (CGV, TGV), were evaluated at each time point. The semi-automatic assessed TGV was compared to conventional TGV by an ellipse formula. International prostate symptom score (IPSS) and international consultation on incontinence questionnaire−urinary incontinence short form (ICIQ-UI SF) questionnaires were used as clinical indexes. Statistical testing in the form of ANOVA, pairwise comparisons using Bonferroni correction, and multiple linear correlations, were conducted using SPSS. (3) Results: TGV was significantly reduced one, six, and 12 months after PAE as assessed by the semi-automatic approach and conventional ellipse formula (p = 0.005; p = 0.025). CGV significantly decreased after one month (p = 0.038), but showed no significant differences six and 12 months after PAE (p = 0.191; p = 0.283). IPP at baseline was demonstrated by 25/27 patients (92.6%) with a significant decrease one, six, and 12 months after treatment (p = 0.028; p = 0.010; p = 0.008). Significant improvement in IPSS and ICIQ-UI SF (p = 0.002; p = 0.016) after one month correlated moderately with TGV reduction (p = 0.031; p = 0.05, correlation coefficients 0.52; 0.69). Apparent diffusion coefficient (ADC) values of CG significantly decreased one month after embolization (p < 0.001), while there were no significant differences in T1w and T2w SIs before and after treatment at each time point. (4) Conclusions: The semi-automatic approach is appropriate for the assessment of volumetric and morphological changes in prostate MRI following PAE, able to identify significantly different ADC values post-treatment without the need for manual identification of infarct areas. Semi-automatic measured TGV reduction is significant and comparable to the TGV calculated by the conventional ellipse formula, confirming the clinical response after PAE.

Deep learning in CT colonography: differentiating premalignant from benign colorectal polyps.

OBJECTIVES: To investigate the differentiation of premalignant from benign colorectal polyps detected by CT colonography using deep learning. METHODS: In this retrospective analysis of an average risk colorectal cancer screening sample, polyps of all size categories and morphologies were manually segmented on supine and prone CT colonography images and classified as premalignant (adenoma) or benign (hyperplastic polyp or regular mucosa) according to histopathology. Two deep learning models SEG and noSEG were trained on 3D CT colonography image subvolumes to predict polyp class, and model SEG was additionally trained with polyp segmentation masks. Diagnostic performance was validated in an independent external multicentre test sample. Predictions were analysed with the visualisation technique Grad-CAM++. RESULTS: The training set consisted of 107 colorectal polyps in 63 patients (mean age: 63 ± 8 years, 40 men) comprising 169 polyp segmentations. The external test set included 77 polyps in 59 patients comprising 118 polyp segmentations. Model SEG achieved a ROC-AUC of 0.83 and 80% sensitivity at 69% specificity for differentiating premalignant from benign polyps. Model noSEG yielded a ROC-AUC of 0.75, 80% sensitivity at 44% specificity, and an average Grad-CAM++ heatmap score of ≥ 0.25 in 90% of polyp tissue. CONCLUSIONS: In this proof-of-concept study, deep learning enabled the differentiation of premalignant from benign colorectal polyps detected with CT colonography and the visualisation of image regions important for predictions. The approach did not require polyp segmentation and thus has the potential to facilitate the identification of high-risk polyps as an automated second reader. KEY POINTS: • Non-invasive deep learning image analysis may differentiate premalignant from benign colorectal polyps found in CT colonography scans. • Deep learning autonomously learned to focus on polyp tissue for predictions without the need for prior polyp segmentation by experts. • Deep learning potentially improves the diagnostic accuracy of CT colonography in colorectal cancer screening by allowing for a more precise selection of patients who would benefit from endoscopic polypectomy, especially for patients with polyps of 6-9 mm size.

Cost-effectiveness of short-protocol emergency brain MRI after negative non-contrast CT for minor stroke detection.

OBJECTIVES: To investigate the cost-effectiveness of supplemental short-protocol brain MRI after negative non-contrast CT for the detection of minor strokes in emergency patients with mild and unspecific neurological symptoms. METHODS: The economic evaluation was centered around a prospective single-center diagnostic accuracy study validating the use of short-protocol brain MRI in the emergency setting. A decision-analytic Markov model distinguished the strategies "no additional imaging" and "additional short-protocol MRI" for evaluation. Minor stroke was assumed to be missed in the initial evaluation in 40% of patients without short-protocol MRI. Specialized post-stroke care with immediate secondary prophylaxis was assumed for patients with detected minor stroke. Utilities and quality-of-life measures were estimated as quality-adjusted life years (QALYs). Input parameters were obtained from the literature. The Markov model simulated a follow-up period of up to 30 years. Willingness to pay was set to $100,000 per QALY. Cost-effectiveness was calculated and deterministic and probabilistic sensitivity analysis was performed. RESULTS: Additional short-protocol MRI was the dominant strategy with overall costs of $26,304 (CT only: $27,109). Cumulative calculated effectiveness in the CT-only group was 14.25 QALYs (short-protocol MRI group: 14.31 QALYs). In the deterministic sensitivity analysis, additional short-protocol MRI remained the dominant strategy in all investigated ranges. Probabilistic sensitivity analysis results from the base case analysis were confirmed, and additional short-protocol MRI resulted in lower costs and higher effectiveness. CONCLUSION: Additional short-protocol MRI in emergency patients with mild and unspecific neurological symptoms enables timely secondary prophylaxis through detection of minor strokes, resulting in lower costs and higher cumulative QALYs. KEY POINTS: • Short-protocol brain MRI after negative head CT in selected emergency patients with mild and unspecific neurological symptoms allows for timely detection of minor strokes. • This strategy supports clinical decision-making with regard to immediate initiation of secondary prophylactic treatment, potentially preventing subsequent major strokes with associated high costs and reduced QALY. • According to the Markov model, additional short-protocol MRI remained the dominant strategy over wide variations of input parameters, even when assuming disproportionally high costs of the supplemental MRI scan.