Current use of percutaneous image-guided tumor ablation for the therapy of liver tumors: lessons learned from the registry of the German Society for Interventional Radiology and Minimally Invasive Therapy (DeGIR) 2018-2022.

OBJECTIVES: Percutaneous image-guided tumor ablation of liver malignancies has become an indispensable therapeutic procedure. The aim of this evaluation of the prospectively managed multinational registry of the voluntary German Society for Interventional Radiology and Minimally Invasive Therapy (DeGIR) was to analyze its use, technical success, and complications in clinical practice. MATERIALS AND METHODS: All liver tumor ablations from 2018 to 2022 were included. Technical success was defined as complete ablation of the tumor with an ablative margin. RESULTS: A total of 7228 liver tumor ablations from 136 centers in Germany and Austria were analyzed. In total, 31.4% (2268/7228) of patients were female. Median age was 67 years (IQR 58-74 years). Microwave ablation (MWA) was performed in 65.1% (4703/7228), and radiofrequency ablation (RFA) in 32.7% (2361/7228). Of 5229 cases with reported tumor etiology, 60.3% (3152/5229) of ablations were performed for liver metastases and 37.3% (1950/5229) for hepatocellular carcinoma. The median lesion diameter was 19 mm (IQR 12-27 mm). In total, 91.8% (6636/7228) of ablations were technically successful. The rate of technically successful ablations was significantly higher in MWA (93.9%, 4417/4703) than in RFA (87.3%, 2061/2361) (p < 0.0001). The total complication rate was 3.0% (214/7228) and was significantly higher in MWA (4.0%, 189/4703) than in RFA (0.9%, 21/2361, p < 0.0001). Additional needle track ablation did not increase the rate of major complications significantly (24.8% (33/133) vs. 28.4% (23/81), p = 0.56)). CONCLUSION: MWA is the most frequent ablation method. Percutaneous image-guided liver tumor ablations have a high technical success rate, which is higher for MWA than RFA. The complication rate is generally low but is higher for MWA than RFA. CLINICAL RELEVANCE STATEMENT: Percutaneous image-guided liver ablation using microwave ablation and radiofrequency ablation are effective therapeutic procedures with low complication rates for the treatment of primary and secondary liver malignancies. KEY POINTS: • Percutaneous image-guided liver tumor ablations have a high technical success rate, which is higher for microwave ablation than radiofrequency ablation. • Microwave ablation is the most frequent ablation method ahead of radiofrequency ablation. • The complication rate is generally low but is higher for microwave ablation than radiofrequency ablation.

Radiation dose aspects and establishment of diagnostic reference levels for90Y radioembolisation during angiographic procedure.

90Y radioembolisation (RE) is an angiographic procedure used in patients with both primary and secondary hepatic malignancies. Local tumour control can be achieved by short range tumour irradiation by the regional intra-arterial administration of glass or resin microspheres loaded with 90yttrium that accumulate in the tumorous tissue. The aim of this study was to investigate the radiation exposure of RE and to establish a local diagnostic reference level (DRL). In this retrospective study, dose data from 397 procedures in 306 patients (mean age 67.4 ± 10.6 years, 82 female) who underwent RE between 06/2017 and 01/2022 using one of two different angiography systems were analysed. DRL was set as the 75th percentile of the dose distribution. In the overall population, dose area product (DAP) (median (interquartile range, IQR)) was 26 Gy cm2(IQR 12-50) with a median fluoroscopy time (FT) of 4.5 min (IQR 2.9-8.0). FT and DAP increased significantly with the number of infusion positions (median, IQR): one position 23 Gy cm2(12-46), two positions 33 Gy cm2(14-60), three positions 50 Gy cm2(24-82) (p< 0.0001). Local DRL is 47 Gy cm2for RE and 111 Gy cm2for RE with additional embolisation. Radiation exposure and FT are significantly higher with increasing number of infusion positions as well as additional embolisation. Our established DRLs for RE may serve as a benchmark for dose optimisation.

Radiation exposure, organ and effective dose of CT-guided liver biopsy as a function of lesion depth and size.

Computed tomography (CT)-guided percutaneous biopsies play an important role in the diagnostic workup of liver lesions. Because radiation dose accumulates rapidly due to repeated image acquisition in a relatively small scan area, analysing radiation exposure is critical for improving radiation protection of CT-guided interventions. The aim of this study was to assess the radiation dose of CT-guided liver biopsies and the influence of lesion parameters, and to establish a local diagnostic reference level (DRL). In this observational retrospective cohort study, dose data of 60 CT-guided liver biopsies between September 2016 and July 2017 were analysed. Radiation exposure was reported for volume-weighted CT dose index (CTDIvol), size-specific dose estimate (SSDE), dose-length product (DLP) and effective dose (ED). Radiation dose of CT-guided liver biopsy was (median (interquartile range)): CTDIvol9.91 mGy (8.33-11.45 mGy), SSDE 10.42 mGy (9.39-11.70 mGy), DLP 542 mGy cm (410-733 mGy cm), ED 8.52 mSv (7.17-13.25 mSv). Radiation exposure was significantly higher in biopsies of deep liver lesions compared to superficial lesions (DLP 679 ± 285 mGy cm vs. 497 ± 167 mGy cm,p= 0.0046). No significant dose differences were observed for differences in lesion or needle size. With helical CT spirals additional to the biopsy-guiding axial CT scans, radiation exposure was significantly increased: 797 ± 287 mGy cm vs. 495 ± 162 mGy cm,p< 0.0001. The local DRL is CTDIvol9.91 mGy, DLP 542 mGy cm. Radiation dose is significantly increased in biopsies of deeper liver lesions compared with superficial lesions. Interventions with additional biopsy-guiding CT spirals lead to higher radiation doses. This study provides a detailed analysis of local radiation doses for CT-guided liver biopsies and provides a benchmark for optimising radiation protection in interventional radiology.

What about the others: differential diagnosis of COVID-19 in a German emergency department.

BACKGROUND: The ongoing COVID-19 pandemic remains a major challenge for worldwide health care systems and in particular emergency medicine. An early and safe triage in the emergency department (ED) is especially crucial for proper therapy. Clinical symptoms of COVID-19 comprise those of many common diseases; thus, differential diagnosis remains challenging. METHOD: We performed a retrospective study of 314 ED patients presenting with conceivable COVID-19 symptoms during the first wave in Germany. All were tested for COVID-19 with SARS-Cov-2-nasopharyngeal swabs. Forty-seven patients were positive. We analyzed the 267 COVID-19 negative patients for their main diagnosis and compared COVID-19 patients with COVID-19 negative respiratory infections for differences in laboratory parameters, symptoms, and vital signs. RESULTS: Among the 267 COVID-19 negative patients, 42.7% had respiratory, 14.2% had other infectious, and 11.2% had cardiovascular diseases. Further, 9.0% and 6.7% had oncological and gastroenterological diagnoses, respectively. Compared to COVID-19 negative airway infections, COVID-19 patients showed less dyspnea (OR 0.440; p = 0.024) but more dysgeusia (OR 7.631; p = 0.005). Their hospital stay was significantly longer (9.0 vs. 5.6 days; p = 0.014), and their mortality significantly higher (OR 3.979; p = 0.014). CONCLUSION: For many common ED diagnoses, COVID-19 should be considered a differential diagnosis. COVID-19 cannot be distinguished from COVID-19 negative respiratory infections by clinical signs, symptoms, or laboratory results. When hospitalization is necessary, the clinical course of COVID-19 airway infections seems to be more severe compared to other respiratory infections. TRIAL REGISTRATION: German Clinical Trial Registry DRKS, DRKS-ID of the study: DRKS00021675 date of registration: May 8th, 2020, retrospectively registered.

Can integrated 18F-FDG PET/MR replace sentinel lymph node resection in malignant melanoma?

PURPOSE: To compare the sensitivity and specificity of 18F-fluordesoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT), 18F-FDG PET/magnetic resonance (18F-FDG PET/MR) and 18F-FDG PET/MR including diffusion weighted imaging (DWI) in the detection of sentinel lymph node metastases in patients suffering from malignant melanoma. MATERIAL & METHODS: Fifty-two patients with malignant melanoma (female: n = 30, male: n = 22, mean age 50.5 ± 16.0 years, mean tumor thickness 2.28 ± 1.97 mm) who underwent 18F-FDG PET/CT and subsequent PET/MR & DWI for distant metastasis staging were included in this retrospective study. After hybrid imaging, lymphoscintigraphy including single photon emission computed tomography/CT (SPECT/CT) was performed to identify the sentinel lymph node prior to sentinel lymph node biopsy (SLNB). In a total of 87 sentinel lymph nodes in 64 lymph node basins visible on SPECT/CT, 17 lymph node metastases were detected by histopathology. In separate sessions PET/CT, PET/MR, and PET/MR & DWI were assessed for sentinel lymph node metastases by two independent readers. Discrepant results were resolved in a consensus reading. Sensitivities, specificities, positive predictive values and negative predictive values were calculated with histopathology following SPECT/CT guided SLNB as a reference standard. RESULTS: Compared with histopathology, lymph nodes were true positive in three cases, true negative in 65 cases, false positive in three cases and false negative in 14 cases in PET/CT. PET/MR was true positive in four cases, true negative in 63 cases, false positive in two cases and false negative in 13 cases. Hence, we observed a sensitivity, specificity, positive predictive value and negative predictive value of 17.7, 95.6, 50.0 and 82.3% for PET/CT and 23.5, 96.9, 66.7 and 82.3% for PET/MR. In DWI, 56 sentinel lymph node basins could be analyzed. Here, the additional analysis of DWI led to two additional false positive findings, while the number of true positive findings could not be increased. CONCLUSION: In conclusion, integrated 18F-FDG PET/MR does not reliably differentiate N-positive from N-negative melanoma patients. Additional DWI does not increase the sensitivity of 18F-FDG PET/MR. Hence, sentinel lymph node biopsy cannot be replaced by 18F-FDG-PE/MR or 18F-FDG-PET/CT.

Heparin-bonded stent graft treatment for major visceral arterial injury after upper abdominal surgery.

PURPOSE: To analyse technical success, complications, and short- and intermediate-term outcomes after heparin-bonded stent graft implantation for the treatment of major abdominal vessel injury after upper abdominal surgery. METHODS: This retrospective, IRB-approved analysis included 29 consecutive patients (female: n = 6, male: n = 23, mean age 65.9 ± 11.2 years). All patients underwent angiography and attempted heparin-bonded stent-graft implantation because of a major visceral arterial injury after upper abdominal surgery. Electronic clinical records, angiographic reports and imaging datasets were reviewed to assess technical success and complications. Telephone interviews were performed to obtain follow-up information and to estimate short- (> 30 days) and intermediate-term (> 90 days) outcomes. RESULTS: Successful stent graft placement was achieved in 82.8% (24/29). Peri-interventional complications were observed in 20.7% (6/29) and delayed, angiography-associated complications were observed in 34.5% (10/29) of the patients. Symptomatic re-bleeding occurred in 24.1% (7/29). Short-term survival (> 30 days) was 72.4% (21/29). Intermediate survival (> 90 days) was 37.9% (11/29). CONCLUSION: Treatment of major vascular injuries with heparin-bonded stent grafts is feasible with a high technical success rate. However, survival depends on the underlying surgical condition, making interdisciplinary patient management mandatory. KEY POINTS: • Stent graft implantation is challenging, but has a high technical success rate. • Complications are frequent but surgical conversion is rarely necessary. • Survival depends on the underlying surgical condition causing the vascular injury. • Interdisciplinary management is crucial for the survival of these patients.

Locoregional tumour evaluation of squamous cell carcinoma in the head and neck area: a comparison between MRI, PET/CT and integrated PET/MRI.

PURPOSE: To evaluate the accuracy of integrated (18)F-FDG PET/MR imaging for locoregional tumour evaluation compared to (18)F-FDG PET/CT and MR imaging in initial tumour and recurrence diagnosis in histopathologically confirmed head and neck squamous cell carcinoma (HNSCC). METHODS: (18)F-FDG PET/CT and integrated (18)F-FDG PET/MR imaging were performed for initial tumour staging or recurrence diagnosis in 25 patients with HNSCC. MR, fused (18)F-FDG PET/CT and fused (18)F-FDG PET/MR images were analysed by two independent readers in separate sessions in random order. In initial tumour staging, T and N staging was performed while individual lesions were analysed in patients with suspected cancer recurrence. In T and N staging, histopathological results after tumour resection served as the reference standard while histopathological sampling as well as cross-sectional and clinical follow-up were accepted in cancer recurrence diagnosis. The diagnostic accuracy of each modality was calculated separately for T and N staging as well as for tumour recurrence, and compared using McNemar's test. Values of p <0.017 were considered statistically significant after Bonferroni correction. RESULTS: In 12 patients undergoing (18)F-FDG PET/CT and (18)F-FDG PET/MR for initial tumour staging, T staging was accurate in 50 % with MRI, in 59 % with PET/CT and in 75 % with PET/MR while N staging was accurate in 75 % with MRI, in 77 % with PET/CT and in 71 % with PET/MR in relation to the reference standard. No significant differences were observed in T and N staging among the three modalities (p > 0.017). In 13 patients undergoing hybrid imaging for cancer recurrence diagnosis, diagnostic accuracy was 57 % with MRI and in 72 % with (18)F-FDG PET/CT and (18)F-FDG PET/MR, respectively. Again, no significant differences were found among the three modalities (p > 0.017). CONCLUSION: In this initial study, no significant differences were found among (18)F-FDG PET/MR, (18)F-FDG PET/CT and MRI in local tumour staging and cancer recurrence diagnosis.

Integrated PET/MRI for whole-body staging of patients with primary cervical cancer: preliminary results.

PURPOSE: To assess the diagnostic value of integrated PET/MRI for whole-body staging of cervical cancer patients, as well as to investigate a potential association between PET/MRI derived functional parameters and prognostic factors of cervical cancer. METHODS: The present study was approved by the local institutional review board. Twenty-seven patients with histopathologically confirmed cervical cancer were prospectively enrolled in our study. All patients underwent a whole-body PET/MRI examination after written informed consent was obtained. Two radiologists separately evaluated the PET/MRI data sets regarding the determination of local tumor extent of primary cervical cancer lesions, as well as detection of nodal and distant metastases. Furthermore, SUV and ADC values of primary tumor lesions were analyzed and correlated with dedicated prognostic factors of cervical cancer. Results based on histopathology and cross-sectional imaging follow-up served as the reference standard. RESULTS: PET/MRI enabled the detection of all 27 primary tumor lesions of the uterine cervix and allowed for the correct determination of the T-stage in 23 (85 %) out of the 27 patients. Furthermore, the calculated sensitivity, specificity and diagnostic accuracy for the detection of nodal positive patients (n = 11) were 91 %, 94 % and 93 %, respectively. PET/MRI correctly identified regional metastatic disease (N1-stage) in 8/10 (80 %) patients and non-regional lymph node metastases in 5/5 (100 %) patients. In addition, quantitative analysis of PET and MRI derived functional parameters (SUV; ADC values) revealed a significant correlation with pathological grade and tumor size (p < 0.05). CONCLUSIONS: The present study demonstrates the high potential of integrated PET/MRI for the assessment of primary tumor and the detection of lymph node metastases in patients with cervical cancer. Providing additional prognostic information, PET/MRI may serve as a valuable diagnostic tool for cervical cancer patients in a pretreatment setting.

The importance of educational tools and a new software solution for visualizing and quantifying report correction in radiology training.

A novel software, DiffTool, was developed in-house to keep track of changes made by board-certified radiologists to preliminary reports created by residents and evaluate its impact on radiological hands-on training. Before (t0) and after (t2-4) the deployment of the software, 18 residents (median age: 29 years; 33% female) completed a standardized questionnaire on professional training. At t2-4 the participants were also requested to respond to three additional questions to evaluate the software. Responses were recorded via a six-point Likert scale ranging from 1 ("strongly agree") to 6 ("strongly disagree"). Prior to the release of the software, 39% (7/18) of the residents strongly agreed with the statement that they manually tracked changes made by board-certified radiologists to each of their radiological reports while 61% were less inclined to agree with that statement. At t2-4, 61% (11/18) stated that they used DiffTool to track differences. Furthermore, we observed an increase from 33% (6/18) to 44% (8/18) of residents who agreed to the statement "I profit from every corrected report". The DiffTool was well accepted among residents with a regular user base of 72% (13/18), while 78% (14/18) considered it a relevant improvement to their training. The results of this study demonstrate the importance of providing a time-efficient way to analyze changes made to preliminary reports as an additive for professional training.

AI-Assisted X-ray Fracture Detection in Residency Training: Evaluation in Pediatric and Adult Trauma Patients.

Background: This study aimed to evaluate the impact of an AI-assisted fracture detection program on radiology residents' performance in pediatric and adult trauma patients and assess its implications for residency training. Methods: This study, conducted retrospectively, included 200 radiographs from participants aged 1 to 95 years (mean age: 40.7 ± 24.5 years), encompassing various body regions. Among these, 50% (100/200) displayed at least one fracture, totaling one hundred thirty-five fractures, assessed by four radiology residents with different experience levels. A machine learning algorithm was employed for fracture detection, and the ground truth was established by consensus among two experienced senior radiologists. Fracture detection accuracy, reporting time, and confidence were evaluated with and without AI support. Results: Radiology residents' sensitivity for fracture detection improved significantly with AI support (58% without AI vs. 77% with AI, p < 0.001), while specificity showed minor improvements (77% without AI vs. 79% with AI, p = 0.0653). AI stand-alone performance achieved a sensitivity of 93% with a specificity of 77%. AI support for fracture detection significantly reduced interpretation time for radiology residents by an average of approximately 2.6 s (p = 0.0156) and increased resident confidence in the findings (p = 0.0013). Conclusion: AI support significantly enhanced fracture detection sensitivity among radiology residents, particularly benefiting less experienced radiologists. It does not compromise specificity and reduces interpretation time, contributing to improved efficiency. This study underscores AI's potential in radiology, emphasizing its role in training and interpretation improvement.

Automated 3D-Body Composition Analysis as a Predictor of Survival in Patients With Idiopathic Pulmonary Fibrosis.

PURPOSE: Idiopathic pulmonary fibrosis (IPF) is the most common interstitial lung disease, with a median survival time of 2 to 5 years. The focus of this study is to establish a novel imaging biomarker. MATERIALS AND METHODS: In this study, 79 patients (19% female) with a median age of 70 years were studied retrospectively. Fully automated body composition analysis (BCA) features (bone, muscle, total adipose tissue, intermuscular, and intramuscular adipose tissue) were combined into Sarcopenia, Fat, and Myosteatosis indices and compared between patients with a survival of more or less than 2 years. In addition, we divided the cohort at the median (high=≥ median, low=

AI-derived body composition parameters as prognostic factors in patients with HCC undergoing TACE in a multicenter study.

Background & Aims: Body composition assessment (BCA) parameters have recently been identified as relevant prognostic factors for patients with hepatocellular carcinoma (HCC). Herein, we aimed to investigate the role of BCA parameters for prognosis prediction in patients with HCC undergoing transarterial chemoembolization (TACE). Methods: This retrospective multicenter study included a total of 754 treatment-naïve patients with HCC who underwent TACE at six tertiary care centers between 2010-2020. Fully automated artificial intelligence-based quantitative 3D volumetry of abdominal cavity tissue composition was performed to assess skeletal muscle volume (SM), total adipose tissue (TAT), intra- and intermuscular adipose tissue, visceral adipose tissue, and subcutaneous adipose tissue (SAT) on pre-intervention computed tomography scans. BCA parameters were normalized to the slice number of the abdominal cavity. We assessed the influence of BCA parameters on median overall survival and performed multivariate analysis including established estimates of survival. Results: Univariate survival analysis revealed that impaired median overall survival was predicted by low SM (p <0.001), high TAT volume (p = 0.013), and high SAT volume (p = 0.006). In multivariate survival analysis, SM remained an independent prognostic factor (p = 0.039), while TAT and SAT volumes no longer showed predictive ability. This predictive role of SM was confirmed in a subgroup analysis of patients with BCLC stage B. Conclusions: SM is an independent prognostic factor for survival prediction. Thus, the integration of SM into novel scoring systems could potentially improve survival prediction and clinical decision-making. Fully automated approaches are needed to foster the implementation of this imaging biomarker into daily routine. Impact and implications: Body composition assessment parameters, especially skeletal muscle volume, have been identified as relevant prognostic factors for many diseases and treatments. In this study, skeletal muscle volume has been identified as an independent prognostic factor for patients with hepatocellular carcinoma undergoing transarterial chemoembolization. Therefore, skeletal muscle volume as a metaparameter could play a role as an opportunistic biomarker in holistic patient assessment and be integrated into decision support systems. Workflow integration with artificial intelligence is essential for automated, quantitative body composition assessment, enabling broad availability in multidisciplinary case discussions.

BOA: A CT-Based Body and Organ Analysis for Radiologists at the Point of Care.

PURPOSE: The study aimed to develop the open-source body and organ analysis (BOA), a comprehensive computed tomography (CT) image segmentation algorithm with a focus on workflow integration. METHODS: The BOA combines 2 segmentation algorithms: body composition analysis (BCA) and TotalSegmentator. The BCA was trained with the nnU-Net framework using a dataset including 300 CT examinations. The CTs were manually annotated with 11 semantic body regions: subcutaneous tissue, muscle, bone, abdominal cavity, thoracic cavity, glands, mediastinum, pericardium, breast implant, brain, and spinal cord. The models were trained using 5-fold cross-validation, and at inference time, an ensemble was used. Afterward, the segmentation efficiency was evaluated on a separate test set comprising 60 CT scans. In a postprocessing step, a tissue segmentation (muscle, subcutaneous adipose tissue, visceral adipose tissue, intermuscular adipose tissue, epicardial adipose tissue, and paracardial adipose tissue) is created by subclassifying the body regions. The BOA combines this algorithm and the open-source segmentation software TotalSegmentator to have an all-in-one comprehensive selection of segmentations. In addition, it integrates into clinical workflows as a DICOM node-triggered service using the open-source Orthanc research PACS (Picture Archiving and Communication System) server to make the automated segmentation algorithms available to clinicians. The BCA model's performance was evaluated using the Sørensen-Dice score. Finally, the segmentations from the 3 different tools (BCA, TotalSegmentator, and BOA) were compared by assessing the overall percentage of the segmented human body on a separate cohort of 150 whole-body CT scans. RESULTS: The results showed that the BCA outperformed the previous publication, achieving a higher Sørensen-Dice score for the previously existing classes, including subcutaneous tissue (0.971 vs 0.962), muscle (0.959 vs 0.933), abdominal cavity (0.983 vs 0.973), thoracic cavity (0.982 vs 0.965), bone (0.961 vs 0.942), and an overall good segmentation efficiency for newly introduced classes: brain (0.985), breast implant (0.943), glands (0.766), mediastinum (0.880), pericardium (0.964), and spinal cord (0.896). All in all, it achieved a 0.935 average Sørensen-Dice score, which is comparable to the one of the TotalSegmentator (0.94). The TotalSegmentator had a mean voxel body coverage of 31% ± 6%, whereas BCA had a coverage of 75% ± 6% and BOA achieved 93% ± 2%. CONCLUSIONS: The open-source BOA merges different segmentation algorithms with a focus on workflow integration through DICOM node integration, offering a comprehensive body segmentation in CT images with a high coverage of the body volume.

Contrast Agent Dose Reduction in MRI Utilizing a Generative Adversarial Network in an Exploratory Animal Study.

OBJECTIVES: The aim of this study is to use virtual contrast enhancement to reduce the amount of hepatobiliary gadolinium-based contrast agent in magnetic resonance imaging with generative adversarial networks (GANs) in a large animal model. METHODS: With 20 healthy Göttingen minipigs, a total of 120 magnetic resonance imaging examinations were performed on 6 different occasions, 50% with reduced (low-dose; 0.005 mmol/kg, gadoxetate) and 50% standard dose (normal-dose; 0.025 mmol/kg). These included arterial, portal venous, venous, and hepatobiliary contrast phases (20 minutes, 30 minutes). Because of incomplete examinations, one animal had to be excluded. Randomly, 3 of 19 animals were selected and withheld for validation (18 examinations). Subsequently, a GAN was trained for image-to-image conversion from low-dose to normal-dose (virtual normal-dose) with the remaining 16 animals (96 examinations). For validation, vascular and parenchymal contrast-to-noise ratio (CNR) was calculated using region of interest measurements of the abdominal aorta, inferior vena cava, portal vein, hepatic parenchyma, and autochthonous back muscles. In parallel, a visual Turing test was performed by presenting the normal-dose and virtual normal-dose data to 3 consultant radiologists, blinded for the type of examination. They had to decide whether they would consider both data sets as consistent in findings and which images were from the normal-dose study. RESULTS: The pooled dynamic phase vascular and parenchymal CNR increased significantly from low-dose to virtual normal-dose (pooled vascular: P < 0.0001, pooled parenchymal: P = 0.0002) and was found to be not significantly different between virtual normal-dose and normal-dose examinations (vascular CNR [mean ± SD]: low-dose 17.6 ± 6.0, virtual normal-dose 41.8 ± 9.7, and normal-dose 48.4 ± 12.2; parenchymal CNR [mean ± SD]: low-dose 20.2 ± 5.9, virtual normal-dose 28.3 ± 6.9, and normal-dose 29.5 ± 7.2). The pooled parenchymal CNR of the hepatobiliary contrast phases revealed a significant increase from the low-dose (22.8 ± 6.2) to the virtual normal-dose (33.2 ± 6.1; P < 0.0001) and normal-dose sequence (37.0 ± 9.1; P < 0.0001). In addition, there was no significant difference between the virtual normal-dose and normal-dose sequence. In the visual Turing test, on the median, the consultant radiologist reported that the sequences of the normal-dose and virtual normal-dose are consistent in findings in 100% of the examinations. Moreover, the consultants were able to identify the normal-dose series as such in a median 54.5% of the cases. CONCLUSIONS: In this feasibility study in healthy Göttingen minipigs, it could be shown that GAN-based virtual contrast enhancement can be used to recreate the image impression of normal-dose imaging in terms of CNR and subjective image similarity in both dynamic and hepatobiliary contrast phases from low-dose data with an 80% reduction in gadolinium-based contrast agent dose. Before clinical implementation, further studies with pathologies are needed to validate whether pathologies are correctly represented by the network.

PSMA-Directed Imaging and Therapy of Salivary Gland Tumors: A Single-Center Retrospective Study.

We analyzed the diagnostic performance of prostate-specific membrane antigen (PSMA) PET/CT and the dosimetry, efficacy, and safety of 177Lu-PSMA-617 radioligand therapy (RLT) in salivary gland malignancies (SGMs). Methods: We identified 28 SGM patients with PSMA PET/CT from our database. CT and PSMA PET/CT images were evaluated separately by 3 masked readers in joint reading sessions. Pathologic findings were grouped into 6 TNM regions, and lesion-based disease extent was classified as no disease (n = 1, 4%), unifocal (n = 2, 7%), oligometastatic (n = 9, 32%), multifocal (n = 3, 11%), or disseminated (n = 13, 47%). For each region, the SUVmax of the lesion with the highest uptake was measured and the visual PSMA expression score was evaluated on a per-patient basis using PROMISE criteria. The association between PSMA expression and clinical and histopathologic markers was tested using the Student t test. Five patients underwent PSMA RLT with intratherapeutic dosimetry. Response was assessed using RECIST 1.1, and adverse events were graded according to version 5.0 of the Common Terminology Criteria for Adverse Events. Results: Compared with CT, PSMA PET/CT demonstrated additional metastatic lesions in 11 of 28 (39%) patients, leading to upstaging of TNM and lesion-based disease extent in 3 (11%) and 6 (21%) patients, respectively. PSMA PET/CT detected CT-occult local tumor, regional lymph nodes, nonregional lymph nodes, and bone metastases in 1 (4%), 4 (14%), 2 (7%), and 4 (14%) patients, respectively; no additional lesions were detected in the other predefined regions. PSMA expression level was higher than liver in 6 patients (25%). A significantly higher SUVmax was observed in male than female patients (15.8 vs. 8.5, P = 0.007) and in bone than lung lesions (14.2 vs. 6.4, P = 0.006). PSMA RLT was discontinued after 1 cycle in 3 of 5 patients because of insufficient tumor doses. No adverse events of grade 4 or higher occurred. Conclusion: In SGMs, PSMA PET/CT demonstrated a superior detection rate and led to upstaging in about one third of patients when compared with CT. The male sex and the presence of bone metastases were associated with significantly higher PSMA expression. PSMA RLT was well tolerated, but most patients did not have more than 1 cycle because of insufficient tumor doses.

Individualized scan protocols for CT angiography: an animal study for contrast media or radiation dose optimization.

BACKGROUND: We investigated about optimization of contrast media (CM) dose or radiation dose in thoracoabdominal computed tomography angiography (CTA) by automated tube voltage selection (ATVS) system configuration and CM protocol adaption. METHODS: In six minipigs, CTA-optimized protocols were evaluated regarding objective (contrast-to-noise ratio, CNR) and subjective (6 criteria assessed by Likert scale) image quality. Scan parameters were automatically adapted by the ATVS system operating at 90-kV semi-mode and configured for standard, CM saving, or radiation dose saving (image task, quality settings). Injection protocols (dose, flow rate) were adapted manually. This approach was tested for normal and simulated obese conditions. RESULTS: Radiation exposure (volume-weighted CT dose index) for normal (obese) conditions was 2.4 ± 0.7 (5.0 ± 0.7) mGy (standard), 4.3 ± 1.1 (9.0 ± 1.3) mGy (CM reduced), and 1.7 ± 0.5 (3.5 ± 0.5) mGy (radiation reduced). The respective CM doses for normal (obese) settings were 210 (240) mgI/kg, 155 (177) mgI/kg, and 252 (288) mgI/kg. No significant differences in CNR (normal; obese) were observed between standard (17.8 ± 3.0; 19.2 ± 4.0), CM-reduced (18.2 ± 3.3; 20.5 ± 4.9), and radiation-saving CTAs (16.0 ± 3.4; 18.4 ± 4.1). Subjective analysis showed similar values for optimized and standard CTAs. Only the parameter diagnostic acceptability was significantly lower for radiation-saving CTA compared to the standard CTA. CONCLUSIONS: The CM dose (-26%) or radiation dose (-30%) for thoracoabdominal CTA can be reduced while maintaining objective and subjective image quality, demonstrating the feasibility of the personalization of CTA scan protocols. KEY POINTS: • Computed tomography angiography protocols could be adapted to individual patient requirements using an automated tube voltage selection system combined with adjusted contrast media injection. • Using an adapted automated tube voltage selection system, a contrast media dose reduction (-26%) or radiation dose reduction (-30%) could be possible.

Adipopenia in body composition analysis: a promising imaging biomarker and potential predictive factor for patients undergoing transjugular intrahepatic portosystemic shunt placement.

OBJECTIVE: Body tissue composition plays a crucial role in the multisystemic processes of advanced liver disease and has been shown to be influenced by transjugular intrahepatic portosystemic shunt (TIPS). A differentiated analysis of the various tissue compartments has not been performed until now. The purpose of this study was to evaluate the value of imaging biomarkers derived from automated body composition analysis (BCA) to predict clinical and functional outcome. METHODS: A retrospective analysis of 56 patients undergoing TIPS procedure between 2013 and 2021 was performed. BCA on the base of pre-interventional CT examination was used to determine quantitative data as well as ratios of bone, muscle and fat masses. Furthermore, a BCA-derived sarcopenia marker was investigated. Regarding potential correlations between BCA imaging biomarkers and the occurrence of hepatic encephalopathy (HE) as well as 1-year survival, an exploratory analysis was conducted. RESULTS: No BCA imaging biomarker was associated with the occurrence of HE after TIPS placement. However, there were significant differences in alive and deceased patients regarding the BCA-derived sarcopenia marker (alive: 1.60, deceased: 1.83, p = 0.046), ratios of intra- and intermuscular fat/skeletal volume (alive: 0.53, deceased: 0.31, p = 0.015) and intra- and intermuscular fat/muscle volume (alive: 0.21, deceased: 0.14, p = 0.031). CONCLUSION: A lower amount of intra- and intermuscular adipose tissue might have protective effects regarding liver derived complications and survival. ADVANCES IN KNOWLEDGE: Precise characterization of body tissue components with automated BCA might provide prognostic information in patients with advanced liver disease undergoing TIPS procedure.

Contrast Media Reduction in Computed Tomography With Deep Learning Using a Generative Adversarial Network in an Experimental Animal Study.

OBJECTIVE: This feasibility study aimed to use optimized virtual contrast enhancement through generative adversarial networks (GAN) to reduce the dose of iodine-based contrast medium (CM) during abdominal computed tomography (CT) in a large animal model. METHODS: Multiphasic abdominal low-kilovolt CTs (90 kV) with low (low CM, 105 mgl/kg) and normal contrast media doses (normal CM, 350 mgl/kg) were performed with 20 healthy Göttingen minipigs on 3 separate occasions for a total of 120 examinations. These included an early arterial, late arterial, portal venous, and venous contrast phase. One animal had to be excluded because of incomplete examinations. Three of the 19 animals were randomly selected and withheld for validation (18 studies). Subsequently, the GAN was trained for image-to-image conversion from low CM to normal CM (virtual CM) with the remaining 16 animals (96 examinations). For validation, region of interest measurements were performed in the abdominal aorta, inferior vena cava, portal vein, liver parenchyma, and autochthonous back muscles, and the contrast-to-noise ratio (CNR) was calculated. In addition, the normal CM and virtual CM data were presented in a visual Turing test to 3 radiology consultants. On the one hand, they had to decide which images were derived from the normal CM examination. On the other hand, they had to evaluate whether both images are pathological consistent. RESULTS: Average vascular CNR (low CM 6.9 ± 7.0 vs virtual CM 28.7 ± 23.8, P < 0.0001) and parenchymal (low CM 1.5 ± 0.7 vs virtual CM 3.8 ± 2.0, P < 0.0001) CNR increased significantly by GAN-based contrast enhancement in all contrast phases and was not significantly different from normal CM examinations (vascular: virtual CM 28.7 ± 23.8 vs normal CM 34.2 ± 28.8; parenchymal: virtual CM 3.8 ± 2.0 vs normal CM 3.7 ± 2.6). During the visual Turing testing, the radiology consultants reported that images from normal CM and virtual CM were pathologically consistent in median in 96.5% of the examinations. Furthermore, it was possible for the examiners to identify the normal CM data as such in median in 91% of the cases. CONCLUSIONS: In this feasibility study, it could be demonstrated in an experimental setting with healthy Göttingen minipigs that the amount of CM for abdominal CT can be reduced by approximately 70% by GAN-based contrast enhancement with satisfactory image quality.

Generating Virtual Short Tau Inversion Recovery (STIR) Images from T1- and T2-Weighted Images Using a Conditional Generative Adversarial Network in Spine Imaging.

Short tau inversion recovery (STIR) sequences are frequently used in magnetic resonance imaging (MRI) of the spine. However, STIR sequences require a significant amount of scanning time. The purpose of the present study was to generate virtual STIR (vSTIR) images from non-contrast, non-fat-suppressed T1- and T2-weighted images using a conditional generative adversarial network (cGAN). The training dataset comprised 612 studies from 514 patients, and the validation dataset comprised 141 studies from 133 patients. For validation, 100 original STIR and respective vSTIR series were presented to six senior radiologists (blinded for the STIR type) in independent A/B-testing sessions. Additionally, for 141 real or vSTIR sequences, the testers were required to produce a structured report of 15 different findings. In the A/B-test, most testers could not reliably identify the real STIR (mean error of tester 1-6: 41%; 44%; 58%; 48%; 39%; 45%). In the evaluation of the structured reports, vSTIR was equivalent to real STIR in 13 of 15 categories. In the category of the number of STIR hyperintense vertebral bodies (p = 0.08) and in the diagnosis of bone metastases (p = 0.055), the vSTIR was only slightly insignificantly equivalent. By virtually generating STIR images of diagnostic quality from T1- and T2-weighted images using a cGAN, one can shorten examination times and increase throughput.