Lesions hyper- to isointense to surrounding liver in the hepatobiliary phase of gadoxetic acid-enhanced MRI.

OBJECTIVES: Hyper- or isointensity in the hepatobiliary phase (HBP) of gadoxetic acid-enhanced MRI has high specificity for focal nodular hyperplasia (FNH) but may be present in hepatocellular adenoma and carcinoma (HCA/HCC). This study aimed to identify imaging characteristics differentiating FNH and HCA/HCC. MATERIALS AND METHODS: This multicenter retrospective cohort study included patients with pathology-proven FNH or HCA/HCC, hyper-/isointense in the HBP of gadoxetic acid-enhanced MRI between 2010 and 2020. Diagnostic performance of imaging characteristics for the differentiation between FNH and HCA/HCC were reported. Univariable analyses, multivariable logistic regression analyses, and classification and regression tree (CART) analyses were conducted. Sensitivity analyses evaluated imaging characteristics of B-catenin-activated HCA. RESULTS: In total, 124 patients (mean age 40 years, standard deviation 10 years, 108 female) with 128 hyper-/isointense lesions were included. Pathology diagnoses were FNH and HCA/HCC in 64 lesions (50%) and HCA/HCC in 64 lesions (50%). Imaging characteristics observed exclusively in HCA/HCC were raster and atoll fingerprint patterns in the HBP, sinusoidal dilatation on T2-w, hemosiderin, T1-w in-phase hyperintensity, venous washout, and nodule-in-nodule partification in the HBP and T2-w. Multivariable logistic regression and CART additionally found a T2-w scar indicating FNH, less than 50% fat, and a spherical contour indicating HCA/HCC. In our selected cohort, 14/48 (29%) of HCA were B-catenin activated, most (13/14) showed extensive hyper-/isointensity, and some had a T2-w scar (4/14, 29%). CONCLUSION: If the aforementioned characteristics typical for HCA/HCC are encountered in lesions extensively hyper- to isointense, further investigation may be warranted to exclude B-catenin-activated HCA. CLINICAL RELEVANCE: Hyper- or isointensity in the HBP of gadoxetic acid-enhanced MRI is specific for FNH, but HCA/HCC can also exhibit this feature. Therefore, we described imaging patterns to differentiate these entities. KEY POINTS: FNH and HCA/HCC have similar HBP intensities but have different malignant potentials. Six imaging patterns exclusive to HCA/HCC were identified in this lesion population. These features in liver lesions hyper- to isointense in the HBP warrant further evaluation.

Machine learning-based radiomic analysis and growth visualization for ablation site recurrence diagnosis in follow-up CT.

OBJECTIVES: Detecting ablation site recurrence (ASR) after thermal ablation remains a challenge for radiologists due to the similarity between tumor recurrence and post-ablative changes. Radiomic analysis and machine learning methods may show additional value in addressing this challenge. The present study primarily sought to determine the efficacy of radiomic analysis in detecting ASR on follow-up computed tomography (CT) scans. The second aim was to develop a visualization tool capable of emphasizing regions of ASR between follow-up scans in individual patients. MATERIALS AND METHODS: Lasso regression and Extreme Gradient Boosting (XGBoost) classifiers were employed for modeling radiomic features extracted from regions of interest delineated by two radiologists. A leave-one-out test (LOOT) was utilized for performance evaluation. A visualization method, creating difference heatmaps (diff-maps) between two follow-up scans, was developed to emphasize regions of growth and thereby highlighting potential ASR. RESULTS: A total of 55 patients, including 20 with and 35 without ASR, were included in the radiomic analysis. The best performing model was achieved by Lasso regression tested with the LOOT approach, reaching an area under the curve (AUC) of 0.97 and an accuracy of 92.73%. The XGBoost classifier demonstrated better performance when trained with all extracted radiomic features than without feature selection, achieving an AUC of 0.93 and an accuracy of 89.09%. The diff-maps correctly highlighted post-ablative liver tumor recurrence in all patients. CONCLUSIONS: Machine learning-based radiomic analysis and growth visualization proved effective in detecting ablation site recurrence on follow-up CT scans.

Sonic hedgehog hepatocellular adenoma: magnetic resonance imaging features and correlation with histology.

OBJECTIVES: Sonic hedgehog hepatocellular adenoma (shHCA) is a new hepatocellular adenoma (HCA) subgroup characterized by high risk of hemorrhage. ShHCA account for below 10% of all HCA cases and are often associated with female gender, obesity, and non-alcoholic steatohepatitis. No specific MRI characteristics have been described to date. The objective of this study was to assess the value of using MRI to identify shHCA, and correlate MRI findings with histology. METHODS: We retrospectively collected MRI scans of 29 patients with shHCA from our center and from different liver referral centers to include 35 lesions. Diagnosis of shHCA was assessed by immunohistochemical overexpression of argininosuccinate synthase 1 or prostaglandin D2 synthase, then confirmed by molecular analysis of sonic hedgehog pathway activation and/or by proteomic analysis. RESULTS: In 46% (n = 16/35) of shHCA cases, we detected intralesional fluid-filled cavities defined on MR images as fluid-like foci markedly hyperintense on T2-weighted sequences, and hypointense on T1-weighted sequences, with or without delayed enhancement. Pathologically, these cavities were observed in 54% of cases as vacuoles filled with blood at different stages of degradation. Hemorrhage and/or necrosis were detected among 71% of cases by MRI analysis (n = 25/35) versus 82% pathologically. Seventeen percent of shHCA cases (n = 6/35) were completely homogeneous via MRI and pathological analysis. No MRI criteria was found in favor of focal nodular hyperplasia, HNF1A-mutated HCA, or typical inflammatory HCA. CONCLUSION: We reveal the presence of intralesional fluid-filled cavities among 46% of our shHCA cases that represent a new MRI finding possibly helpful for shHCA diagnosis. CLINICAL RELEVANCE STATEMENT: This multicenter study is the first clinical study about the radiological aspect of this new hepatocellular adenoma subgroup. This highlights a strong correlation between MRI and histological analysis, with a specific pattern emerging for diagnosis. KEY POINTS: • Sonic hedgehog hepatocellular adenoma is a new hepatocellular adenoma subgroup associated with high risk of hemorrhage, but imaging features of this subgroup remain unknown. • Analysis of MR images and correlation with pathology revealed intralesional fluid-filled cavities and necrotic-hemorrhagic changes. • Intralesional fluid-filled cavities have not yet been described in other adenoma subtypes and represent a new MRI finding for sonic hedgehog hepatocellular adenoma.

pH-Responsive Elastin-Like Polypeptide Designer Condensates.

Biomolecular condensates are macromolecular complexes formed by liquid-liquid phase separation. They regulate key biological functions by reversibly compartmentalizing molecules in cells, in a stimulus-dependent manner. Designing stimuli-responsive synthetic condensates is crucial for engineering compartmentalized synthetic cells that are able to mimic spatiotemporal control over the biochemical reactions. Here, we design and test a family of condensate-forming, pH-responsive elastin-like polypeptides (ELPs) that form condensates above critical pH values ranging between 4 and 7, for temperatures between 20 and at 37 °C. We show that the condensation occurs rapidly, in sharp pH intervals (ΔpH < 0.3). For eventual applications in engineering synthetic cell compartments, we demonstrate that multiple types of pH-responsive ELPs can form mixed condensates inside micron-sized vesicles. When genetically fused with enzymes, receptors, and signaling molecules, these pH-responsive ELPs could be potentially used as pH-switchable functional condensates for spatially controlling biochemistry in engineered synthetic cells.

A dual-tracer approach using [11C]CH and [18F]FDG in HCC clinical decision making.

BACKGROUND: Early detection of recurrent or progressive HCC remains the strongest prognostic factor for survival. Dual tracer PET/CT imaging with [11C]CH and [18F]FDG can further increase detection rates as both tracers entail different metabolic pathways involved in HCC development. We investigated dual-tracer PET/CT in clinical decision making in patients suspected of recurrent or progressive HCC. All HCC patients who underwent both [11C]CH and [18F]FDG PET/CT in our institute from February 2018 to December 2021 were included. Both tracer PET/CT were within 4 weeks of each other with at least 6-month follow-up. Patients underwent dual tracer PET/CT because of unexplained and suspicious CT/MRI or sudden rise of serum tumour markers. A detected lesion was considered critical when the finding had prognostic consequences leading to treatment changes. RESULTS: Nineteen patients who underwent [11C]CH and [18F]FDG PET/CT were included of which all but six patients were previously treated for HCC. Dual-tracer critical finding detection rate was 95%, with [18F]FDG 68%, and [11C]CH 84%. Intrahepatic HCC recurrence finding rate was 65% for both tracers. [18F]FDG found more ablation site recurrences (4/5) compared to [11C]CH (2/5). Only [11C]CH found two needle tract metastases. Both tracers found 75% of the positive lymph nodes. Two new primary tumours were found, one by [18F]FDG and both by [11C]CH. CONCLUSIONS: Our study favours a dual-tracer approach in HCC staging in high-risk patients or when conventional imaging is non-conclusive.

Prediction of metastatic pheochromocytoma and paraganglioma: a machine learning modelling study using data from a cross-sectional cohort.

BACKGROUND: Pheochromocytomas and paragangliomas have up to a 20% rate of metastatic disease that cannot be reliably predicted. This study prospectively assessed whether the dopamine metabolite, methoxytyramine, might predict metastatic disease, whether predictions might be improved using machine learning models that incorporate other features, and how machine learning-based predictions compare with predictions made by specialists in the field. METHODS: In this machine learning modelling study, we used cross-sectional cohort data from the PMT trial, based in Germany, Poland, and the Netherlands, to prospectively examine the utility of methoxytyramine to predict metastatic disease in 267 patients with pheochromocytoma or paraganglioma and positive biochemical test results at initial screening. Another retrospective dataset of 493 patients with these tumors enrolled under clinical protocols at National Institutes of Health (00-CH-0093) and the Netherlands (PRESCRIPT trial) was used to train and validate machine learning models according to selections of additional features. The best performing machine learning models were then externally validated using data for all patients in the PMT trial. For comparison, 12 specialists provided predictions of metastatic disease using data from the training and external validation datasets. FINDINGS: Prospective predictions indicated that plasma methoxytyramine could identify metastatic disease at sensitivities of 52% and specificities of 85%. The best performing machine learning model was based on an ensemble tree classifier algorithm that used nine features: plasma methoxytyramine, metanephrine, normetanephrine, age, sex, previous history of pheochromocytoma or paraganglioma, location and size of primary tumours, and presence of multifocal disease. This model had an area under the receiver operating characteristic curve of 0·942 (95% CI 0·894-0·969) that was larger (p<0·0001) than that of the best performing specialist before (0·815, 0·778-0·853) and after (0·812, 0·781-0·854) provision of SDHB variant data. Sensitivity for prediction of metastatic disease in the external validation cohort reached 83% at a specificity of 92%. INTERPRETATION: Although methoxytyramine has some utility for prediction of metastatic pheochromocytomas and paragangliomas, sensitivity is limited. Predictive value is considerably enhanced with machine learning models that incorporate our nine recommended features. Our final model provides a preoperative approach to predict metastases in patients with pheochromocytomas and paragangliomas, and thereby guide individualised patient management and follow-up. FUNDING: Deutsche Forschungsgemeinschaft.

Evaluation of National Surgical Practice for Lateral Lymph Nodes in Rectal Cancer in an Untrained Setting.

BACKGROUND: Involved lateral lymph nodes (LLNs) have been associated with increased local recurrence (LR) and ipsi-lateral LR (LLR) rates. However, consensus regarding the indication and type of surgical treatment for suspicious LLNs is lacking. This study evaluated the surgical treatment of LLNs in an untrained setting at a national level. METHODS: Patients who underwent additional LLN surgery were selected from a national cross-sectional cohort study regarding patients undergoing rectal cancer surgery in 69 Dutch hospitals in 2016. LLN surgery consisted of either 'node-picking' (the removal of an individual LLN) or 'partial regional node dissection' (PRND; an incomplete resection of the LLN area). For all patients with primarily enlarged (≥7 mm) LLNs, those undergoing rectal surgery with an additional LLN procedure were compared to those  undergoing only rectal resection. RESULTS: Out of 3057 patients, 64 underwent additional LLN surgery, with 4-year LR and LLR rates of 26% and 15%, respectively. Forty-eight patients (75%) had enlarged LLNs, with corresponding recurrence rates of 26% and 19%, respectively. Node-picking (n = 40) resulted in a 20% 4-year LLR, and a 14% LLR after PRND (n = 8; p = 0.677). Multivariable analysis of 158 patients with enlarged LLNs undergoing additional LLN surgery (n = 48) or rectal resection alone (n = 110) showed no significant association of LLN surgery with 4-year LR or LLR, but suggested higher recurrence risks after LLN surgery (LR: hazard ratio [HR] 1.5, 95% confidence interval [CI] 0.7-3.2, p = 0.264; LLR: HR 1.9, 95% CI 0.2-2.5, p = 0.874). CONCLUSION: Evaluation of Dutch practice in 2016 revealed that approximately one-third of patients with primarily enlarged LLNs underwent surgical treatment, mostly consisting of node-picking. Recurrence rates were not significantly affected by LLN surgery, but did suggest worse outcomes. Outcomes of LLN surgery after adequate training requires further research.

A prospective multicentre trial on survival after Microwave Ablation VErsus Resection for Resectable Colorectal liver metastases (MAVERRIC).

AIM: This multi-centre prospective cohort study aimed to investigate non-inferiority in patients' overall survival when treating potentially resectable colorectal cancer liver metastasis (CRLM) with stereotactic microwave ablation (SMWA) as opposed to hepatic resection (HR). METHODS: Patients with no more than 5 CRLM no larger than 30 mm, deemed eligible for both SMWA and hepatic resection at the local multidisciplinary team meetings, were deliberately treated with SMWA (study group). The contemporary control group consisted of patients with no more than 5 CRLM, none larger than 30 mm, treated with HR, extracted from a prospectively maintained nationwide Swedish database. After propensity-score matching, 3-year overall survival (OS) was compared as the primary outcome using Kaplan-Meier and Cox regression analyses. RESULTS: All patients in the study group (n = 98) were matched to 158 patients from the control group (mean standardised difference in baseline covariates = 0.077). OS rates at 3 years were 78% (Confidence interval [CI] 68-85%) after SMWA versus 76% (CI 69-82%) after HR (stratified Log-rank test p = 0.861). Estimated 5-year OS rates were 56% (CI 45-66%) versus 58% (CI 50-66%). The adjusted hazard ratio for treatment type was 1.020 (CI 0.689-1.510). Overall and major complications were lower after SMWA (percentage decrease 67% and 80%, p < 0.01). Hepatic retreatments were more frequent after SMWA (percentage increase 78%, p < 0.01). CONCLUSION: SMWA is a valid curative-intent treatment alternative to surgical resection for small resectable CRLM. It represents an attractive option in terms of treatment-related morbidity with potentially wider options regarding hepatic retreatments over the future course of disease.

The Value of Deep Learning in Gallbladder Lesion Characterization.

BACKGROUND: The similarity of gallbladder cancer and benign gallbladder lesions brings challenges to diagnosing gallbladder cancer (GBC). This study investigated whether a convolutional neural network (CNN) could adequately differentiate GBC from benign gallbladder diseases, and whether information from adjacent liver parenchyma could improve its performance. METHODS: Consecutive patients referred to our hospital with suspicious gallbladder lesions with histopathological diagnosis confirmation and available contrast-enhanced portal venous phase CT scans were retrospectively selected. A CT-based CNN was trained once on gallbladder only and once on gallbladder including a 2 cm adjacent liver parenchyma. The best-performing classifier was combined with the diagnostic results based on radiological visual analysis. RESULTS: A total of 127 patients were included in the study: 83 patients with benign gallbladder lesions and 44 with gallbladder cancer. The CNN trained on the gallbladder including adjacent liver parenchyma achieved the best performance with an AUC of 0.81 (95% CI 0.71-0.92), being >10% better than the CNN trained on only the gallbladder (p = 0.09). Combining the CNN with radiological visual interpretation did not improve the differentiation between GBC and benign gallbladder diseases. CONCLUSIONS: The CT-based CNN shows promising ability to differentiate gallbladder cancer from benign gallbladder lesions. In addition, the liver parenchyma adjacent to the gallbladder seems to provide additional information, thereby improving the CNN's performance for gallbladder lesion characterization. However, these findings should be confirmed in larger multicenter studies.

Variation in the management of benign liver tumors: A European survey and case vignette study.

BACKGROUND: Management of focal nodular hyperplasia (FNH) and hepatocellular adenoma (HCA), is multidisciplinary and subject to practice variation. We aimed to evaluate variation in clinical management of FNH and HCA in Europe. METHODS: We distributed an online survey (November 2021-March 2022) among 294 European experts. The survey included questions on local practice and included eight clinical vignettes. The clinical vignettes focused on FNH or HCA management in the setting of sex, lifestyle modification, and pregnancy. RESULTS: The response rate was 32% and respondents included surgeons (38%), gastroenterologists/hepatologists (25%), radiologists (32%), and pathologists (1.6%) from ten European countries. We observed practice variation with regard to lifestyle modification and imaging follow-up in patients with FNH, and with regard to the management of HCA >5 cm before and during pregnancy. Finally, the management of HCA >5 cm after lifestyle modification deviated from EASL guideline recommendations. CONCLUSION: Our survey illustrates variability in FNH and HCA management in Europe. Several areas were identified for future research and guideline recommendations, including FNH follow-up and the management of HCA >5 cm. We propose the organization of Delphi consensus meetings to prioritize areas of research and update current guidelines to optimize management for all patients with benign liver tumors.

Hyperammonemic Encephalopathy in a Patient with Pancreatic Neuroendocrine Tumor and Portosystemic Shunt.

Hyperammonemia can lead to encephalopathy and may be accompanied by a diagnostic dilemma. Imaging as well as biochemical analyses are the cornerstone for identifying possible underlying causes such as severe liver disease or urea cycle defect. We report a case of a patient that presented with neurological deficits based on hyperammonemia in the presence of a large pancreatic neuroendocrine tumor (PNET) and portosystemic shunts in the liver. Prior cases are rather scarce, and the exact mechanism is not fully understood. The case illustrates the added value of a multimodality imaging approach in patients presenting with hyperammonemia-induced encephalopathy.

A nationwide assessment of hepatocellular adenoma resection: Indications and pathological discordance.

Hepatocellular adenomas (HCAs) are benign liver tumors associated with bleeding or malignant transformation. Data on the indication for surgery are scarce. We analyzed indications and outcome of patients operated for HCAs < 50 mm compared to HCAs ≥ 50 mm. Changes in final postoperative diagnosis were assessed. We performed a retrospective study that included patients who underwent resection for (suspected) HCAs in the Netherlands from 2014 to 2019. Indication for resection was analyzed and stratified for small (<50 mm) and large (≥50 mm) tumors. Logistic regression analysis was performed on factors influencing change in tumor diagnosis. Out of 222 patients who underwent surgery, 44 (20%) patients had a tumor <50 mm. Median age was 46 (interquartile range [IQR], 33-56) years in patients with small tumors and 37 (IQR, 31-46) years in patients with large tumors ( p  = 0.016). Patients with small tumors were more frequently men (21% vs. 5%, p  = 0.002). Main indications for resection in patients with small tumors were suspicion of (pre)malignancy (55%), (previous) bleeding (14%), and male sex (11%). Patients with large tumors received operations because of tumor size >50 mm (52%), suspicion of (pre)malignancy (28%), and (previous) bleeding (5.1%). No difference was observed in HCA-subtype distribution between small and large tumors. Ninety-six (43%) patients had a postoperative change in diagnosis. Independent risk factors for change in diagnosis were tumor size <50 mm (adjusted odds ratio [aOR], 3.4; p  < 0.01), male sex (aOR, 3.7; p  = 0.03), and lack of hepatobiliary contrast-enhanced magnetic resonance imaging (CE-MRI) (aOR, 1.8; p  = 0.04). Resection for small (suspected) HCAs was mainly indicated by suspicion of (pre)malignancy, whereas for large (suspected) HCAs, tumor size was the most prevalent indication. Male sex, tumor size <50 mm, and lack of hepatobiliary CE-MRI were independent risk factors for postoperative change in tumor diagnosis.

Multidisciplinary management of chronic refractory pain in autosomal dominant polycystic kidney disease.

BACKGROUND: Chronic pain is often difficult to manage in autosomal dominant polycystic kidney disease (ADPKD) patients and sometimes even leads to nephrectomy. We analyzed the long-term efficacy of our innovative multidisciplinary protocol to treat chronic refractory pain that aims to preserve kidney function by applying among other sequential nerve blocks. METHODS: Patients were eligible if pain was present ≥3 months with a score of ≥50 on a visual analog scale (VAS) of 100, was negatively affecting quality of life and if there had been insufficient response to previous therapies, including opioid treatment. Treatment options were, in order, analgesics, cyst aspiration and fenestration, nerve blocks and nephrectomy. RESULTS: A total of 101 patients were assessed in our clinic (mean age 50 ± 11 years, 65.3% females). Eight patients were treated with medication, 6 by cyst aspiration or fenestration, 63 by nerve blocks and 6 received surgery as the first treatment option. Overall, 76.9% experienced a positive effect on pain complaints shortly after treatment. The VAS score was reduced from 60/100 to 20/100 (P < 0.001) and patients decreased their number of nonopioid and opioid analgesics significantly (P < 0.001, P = 0.01, respectively). A substantial number of the patients (n = 51) needed additional treatment. At the end of follow-up in only 13 patients (12.9%) was surgical intervention necessary: 11 nephrectomies (of which 10 were in patients already on kidney function replacement treatment), 1 liver transplantation and 1 partial hepatectomy. After a median follow-up of 4.5 years (interquartile range 2.5-5.3), 69.0% of the patients still had fewer pain complaints. CONCLUSIONS: These data indicate that our multidisciplinary treatment protocol appears effective in reducing pain in the majority of patients with chronic refractory pain, while postponing or even avoiding in most patients surgical interventions such as nephrectomy in most patients.

Optimal radiological gallbladder lesion characterization by combining visual assessment with CT-based radiomics.

OBJECTIVES: Differentiating benign gallbladder diseases from gallbladder cancer (GBC) remains a radiological challenge because they can appear very similar on imaging. This study aimed at investigating whether CT-based radiomic features of suspicious gallbladder lesions analyzed by machine learning algorithms could adequately discriminate benign gallbladder disease from GBC. In addition, the added value of machine learning models to radiological visual CT-scan interpretation was assessed. METHODS: Patients were retrospectively selected based on confirmed histopathological diagnosis and available contrast-enhanced portal venous phase CT-scan. The radiomic features were extracted from the entire gallbladder, then further analyzed by machine learning classifiers based on Lasso regression, Ridge regression, and XG Boosting. The results of the best-performing classifier were combined with radiological visual CT diagnosis and then compared with radiological visual CT assessment alone. RESULTS: In total, 127 patients were included: 83 patients with benign gallbladder lesions and 44 patients with GBC. Among all machine learning classifiers, XG boosting achieved the best AUC of 0.81 (95% CI 0.72-0.91) and the highest accuracy rate of 73% (95% CI 65-80%). When combining radiological visual interpretation and predictions of the XG boosting classifier, the highest diagnostic performance was achieved with an AUC of 0.98 (95% CI 0.96-1.00), a sensitivity of 91% (95% CI 86-100%), a specificity of 93% (95% CI 90-100%), and an accuracy of 92% (95% CI 90-100%). CONCLUSIONS: Machine learning analysis of CT-based radiomic features shows promising results in discriminating benign from malignant gallbladder disease. Combining CT-based radiomic analysis and radiological visual interpretation provided the most optimal strategy for GBC and benign gallbladder disease differentiation. KEY POINTS: Radiomic-based machine learning algorithms are able to differentiate benign gallbladder disease from gallbladder cancer. Combining machine learning algorithms with a radiological visual interpretation of gallbladder lesions at CT increases the specificity, compared to visual interpretation alone, from 73 to 93% and the accuracy from 85 to 92%. Combined use of machine learning algorithms and radiological visual assessment seems the most optimal strategy for GBC and benign gallbladder disease differentiation.

Comparison of Two 2.45 GHz Microwave Ablation Devices with Respect to Ablation Zone Volume in Relation to Applied Energy in Patients with Malignant Liver Tumours.

Purpose: (i) to compare two 2.45 GHz MWA devices with respect to AZV in relation to the applied energy after MWA in patients with hepatocellular carcinoma (HCC) or colorectal liver metastasis (CRLM) and (ii) to identify potential confounders for this relationship. Methods: In total, 102 tumours, 65 CRLM and 37 HCC were included in this retrospective analysis. Tumours were treated with Emprint (n = 71) or Neuwave (n = 31) MWA devices. Ablation treatment setting were recorded and applied energy was calculated. AZV and tumour volumes were segmented on the contrast-enhanced CT scans obtained 1 week after treatment. The AZV to applied energy R(AZV:E) ratios were calculated for each tumour treatment and compared between both MWA devices and tumour types. Results: R(AZV:E)EMPRINT was 0.41 and R(AZV:E)NEUWAVE was 0.81, p < 0.001. Moderate correlation between AZV and applied energy was found for Emprint (r = 0.57, R2 = 0.32, p < 0.001) and strong correlation was found for Neuwave (r = 0.78, R2 = 0.61, p < 0.001). R(AZV:E)CRLM was 0.45 and R(AZV:E)HCC was 0.52, p = 0.270. Conclusion: This study confirms the unpredictability of AZVs based on the applied output energy for HCC and CRLM. No significant differences in R(AZV:E) were observed between CRLM and HCC. Significantly lower R(AZV:E) was found for Emprint devices compared to Neuwave; however, reflected energy due to cable and antenna design remains unclear and might contribute to these differences.

Prediction of Non-Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer Patients with 18F-FDG PET Radiomics Based Machine Learning Classification.

BACKGROUND: Approximately 26% of esophageal cancer (EC) patients do not respond to neoadjuvant chemoradiotherapy (nCRT), emphasizing the need for pre-treatment selection. The aim of this study was to predict non-response using a radiomic model on baseline 18F-FDG PET. METHODS: Retrospectively, 143 18F-FDG PET radiomic features were extracted from 199 EC patients (T1N1-3M0/T2-4aN0-3M0) treated between 2009 and 2019. Non-response (n = 57; 29%) was defined as Mandard Tumor Regression Grade 4-5 (n = 44; 22%) or interval progression (n = 13; 7%). Randomly, 139 patients (70%) were allocated to explore all combinations of 24 feature selection strategies and 6 classification methods towards the cross-validated average precision (AP). The predictive value of the best-performing model, i.e AP and area under the ROC curve analysis (AUC), was evaluated on an independent test subset of 60 patients (30%). RESULTS: The best performing model had an AP (mean ± SD) of 0.47 ± 0.06 on the training subset, achieved by a support vector machine classifier trained on five principal components of relevant clinical and radiomic features. The model was externally validated with an AP of 0.66 and an AUC of 0.67. CONCLUSION: In the present study, the best-performing model on pre-treatment 18F-FDG PET radiomics and clinical features had a small clinical benefit to identify non-responders to nCRT in EC.

Algorithm-based care versus usual care for the early recognition and management of complications after pancreatic resection in the Netherlands: an open-label, nationwide, stepped-wedge cluster-randomised trial.

BACKGROUND: Early recognition and management of postoperative complications, before they become clinically relevant, can improve postoperative outcomes for patients, especially for high-risk procedures such as pancreatic resection. METHODS: We did an open-label, nationwide, stepped-wedge cluster-randomised trial that included all patients having pancreatic resection during a 22-month period in the Netherlands. In this trial design, all 17 centres that did pancreatic surgery were randomly allocated for the timing of the crossover from usual care (the control group) to treatment given in accordance with a multimodal, multidisciplinary algorithm for the early recognition and minimally invasive management of postoperative complications (the intervention group). Randomisation was done by an independent statistician using a computer-generated scheme, stratified to ensure that low-medium-volume centres alternated with high-volume centres. Patients and investigators were not masked to treatment. A smartphone app was designed that incorporated the algorithm and included the daily evaluation of clinical and biochemical markers. The algorithm determined when to do abdominal CT, radiological drainage, start antibiotic treatment, and remove abdominal drains. After crossover, clinicians were trained in how to use the algorithm during a 4-week wash-in period; analyses comparing outcomes between the control group and the intervention group included all patients other than those having pancreatic resection during this wash-in period. The primary outcome was a composite of bleeding that required invasive intervention, organ failure, and 90-day mortality, and was assessed by a masked adjudication committee. This trial was registered in the Netherlands Trial Register, NL6671. FINDINGS: From Jan 8, 2018, to Nov 9, 2019, all 1805 patients who had pancreatic resection in the Netherlands were eligible for and included in this study. 57 patients who underwent resection during the wash-in phase were excluded from the primary analysis. 1748 patients (885 receiving usual care and 863 receiving algorithm-centred care) were included. The primary outcome occurred in fewer patients in the algorithm-centred care group than in the usual care group (73 [8%] of 863 patients vs 124 [14%] of 885 patients; adjusted risk ratio [RR] 0·48, 95% CI 0·38-0·61; p<0·0001). Among patients treated according to the algorithm, compared with patients who received usual care there was a decrease in bleeding that required intervention (47 [5%] patients vs 51 [6%] patients; RR 0·65, 0·42-0·99; p=0·046), organ failure (39 [5%] patients vs 92 [10%] patients; 0·35, 0·20-0·60; p=0·0001), and 90-day mortality (23 [3%] patients vs 44 [5%] patients; 0·42, 0·19-0·92; p=0·029). INTERPRETATION: The algorithm for the early recognition and minimally invasive management of complications after pancreatic resection considerably improved clinical outcomes compared with usual care. This difference included an approximate 50% reduction in mortality at 90 days. FUNDING: The Dutch Cancer Society and UMC Utrecht.

Post-treatment three-dimensional voxel-based dosimetry after Yttrium-90 resin microsphere radioembolization in HCC.

BACKGROUND: Post-therapy [90Y] PET/CT-based dosimetry is currently recommended to validate treatment planning as [99mTc] MAA SPECT/CT is often a poor predictor of subsequent actual [90Y] absorbed dose. Treatment planning software became available allowing 3D voxel dosimetry offering tumour-absorbed dose distributions and dose-volume histograms (DVH). We aim to assess dose-response effects in post-therapy [90Y] PET/CT dosimetry in SIRT-treated HCC patients for predicting overall and progression-free survival (OS and PFS) and four-month follow-up tumour response (mRECIST). Tumour-absorbed dose and mean percentage of the tumour volume (V) receiving ≥ 100, 150, 200, or 250 Gy and mean minimum absorbed dose (D) delivered to 30%, 50%, 70%, and 90% of tumour volume were calculated from DVH's. Depending on the mean tumour -absorbed dose, treated lesions were assigned to a < 120 Gy or ≥ 120 Gy group. RESULTS: Thirty patients received 36 SIRT treatments, totalling 43 lesions. Median tumour-absorbed dose was significantly different between the ≥ 120 Gy (n = 28, 207 Gy, IQR 154-311 Gy) and < 120 Gy group (n = 15, 62 Gy, IQR 49-97 Gy, p <0 .01). Disease control (DC) was found more frequently in the ≥ 120 Gy group (79%) compared to < 120 Gy (53%). Mean tumour-absorbed dose optimal cut-off predicting DC was 131 Gy. Tumour control probability was 54% (95% CI 52-54%) for a mean tumour-absorbed dose of 120 Gy and 90% (95% CI 87-92%) for 284 Gy. Only D30 was significantly different between DC and progressive disease (p = 0.04). For the ≥ 120 Gy group, median OS and PFS were longer (median OS 33 months, [range 8-33 months] and median PFS 23 months [range 4-33 months]) than the < 120 Gy group (median OS 17 months, [range 5-33 months] and median PFS 13 months [range 1-33 months]) (p < 0.01 and p = 0.03, respectively). CONCLUSIONS: Higher 3D voxel-based tumour-absorbed dose in patients with HCC is associated with four-month DC and longer OS and PFS. DVHs in [90Y] SIRT could play a role in evaluative dosimetry.

Study protocol for a multicentre nationwide prospective cohort study to investigate the natural course and clinical outcome in benign liver tumours and cysts in the Netherlands: the BELIVER study.

INTRODUCTION: Benign liver tumours and cysts (BLTCs) comprise a heterogeneous group of cystic and solid lesions, including hepatic haemangioma, focal nodular hyperplasia and hepatocellular adenoma. Some BLTCs, for example, (large) hepatocellular adenoma, are at risk of complications. Incidence of malignant degeneration or haemorrhage is low in most other BLTCs. Nevertheless, the diagnosis BLTC may carry a substantial burden and patients may be symptomatic, necessitating treatment. The indications for interventions remain matter of debate. The primary study aim is to investigate patient-reported outcomes (PROs) of patients with BLTCs, with special regards to the influence of invasive treatment as compared with the natural course of the disease. METHODS AND ANALYSIS: A nationwide observational cohort study of patients with BLTC will be performed between October 2021 and October 2026, the minimal follow-up will be 2 years. During surveillance, a questionnaire regarding symptoms and their impact will be sent to participants on a biannual basis and more often in case of invasive intervention. The questionnaire was previously developed based on PROs considered relevant to patients with BLTCs and their caregivers. Most questionnaires will be administered by computerised adaptive testing through the Patient-Reported Outcomes Measurement Information System. Data, such as treatment outcomes, will be extracted from electronic patient files. Multivariable analysis will be performed to identify patient and tumour characteristics associated with significant improvement in PROs or a complicated postoperative course. ETHICS AND DISSEMINATION: The study was assessed by the Medical Ethics Committee of the University Medical Center Groningen and the Amsterdam UMC. Local consultants will provide information and informed consent will be asked of all patients. Results will be published in a peer-reviewed journal. STUDY REGISTRATION: NL8231-10 December 2019; Netherlands Trial Register.