Mass-Forming Portal Biliopathy Presenting as Extreme Wall-Thickening of the Common Bile Duct

Portal biliopathy refers to biliary tree abnormalities in patients with peribiliary collateral vessels and non-neoplastic extrahepatic portal vein occlusion. These biliary abnormalities are caused by vascular compression and ischemic damage of the biliary tree, which can result in bile duct compression, stenosis, fibrotic strictures, bile duct dilation, and thickening of the bile duct wall. Portal biliopathy is difficult to distinguish from cholangiocarcinoma, IgG4-related disease, and sclerosing cholangitis. Although most patients are asymptomatic, portal biliopathy can lead to serious complications, such as recurrent cholangitis. This case illustrates the importance of including portal biliopathy in the differential diagnosis at an early stage, especially in patients with portal hypertension. With early recognition, the need for additional invasive diagnostic procedures such as biopsies is minimized. Pathogenesis, clinical presentation, diagnostics, and treatment options of portal biliopathy are described in the article

A possible physiological mechanism of rectocele formation in women

BACKGROUND: We aimed to determine the anorectal physiological factors associated with rectocele formation.METHODS: Female patients (N = 32) with severe constipation, fecal incontinence, or suspicion of rectocele, who had undergone magnetic resonance defecography and anorectal function tests between 2015 and 2021, were retrospectively included for analysis. The anorectal function tests were used to measure pressure in the anorectum during defecation. Rectocele characteristics and pelvic floor anatomy were determined with magnetic resonance defecography. Constipation severity was determined with the Agachan score. Information regarding constipation-related symptoms was collected.RESULTS: Mean rectocele size during defecation was 2.14 ± 0.88 cm. During defecation, the mean anal sphincter pressure just before defecation was 123.70 ± 67.37 mm Hg and was associated with rectocele size (P = 0.041). The Agachan constipation score was moderately correlated with anal sphincter pressure just before defecation (r = 0.465, P = 0.022), but not with rectocele size (r = 0.276, P = 0.191). During defecation, increased anal sphincter pressure just before defecation correlated moderately and positively with straining maneuvers (r = 0.539, P = 0.007) and defecation blockage (r = 0.532, P = 0.007). Rectocele size correlated moderately and positively with the distance between the pubococcygeal line and perineum (r = 0.446, P = 0.011).CONCLUSION: Increased anal sphincter pressure just before defecation is correlated with the rectocele size. Based on these results, it seems important to first treat the increased anal canal pressure before considering surgical rectocele repair to enhance patient outcomes.</p

Scoping review of clinical practice guidelines on the management of benign liver tumours

OBJECTIVE: Benign liver tumours (BLT) are increasingly diagnosed as incidentalomas. Clinical implications and management vary across and within the different types of BLT. High-quality clinical practice guidelines are needed, because of the many nuances in tumour types, diagnostic modalities, and conservative and invasive management strategies. Yet, available observational evidence is subject to interpretation which may lead to practice variation. Therefore, we aimed to systematically search for available clinical practice guidelines on BLT, to critically appraise them, and to compare management recommendations. DESIGN: A scoping review was performed within MEDLINE, EMBASE, and Web of Science. All BLT guidelines published in peer-reviewed, and English language journals were eligible for inclusion. Clinical practice guidelines on BLT were analysed, compared, and critically appraised using the Appraisal of Guidelines, Research and Evaluation (AGREE II) checklist regarding hepatic haemangioma, focal nodular hyperplasia (FNH), and hepatocellular adenoma (HCA). Preferred Reporting Items for Systematic Reviews and Meta-Analyses recommendations (PRISMA) for scoping reviews were adhered to. RESULTS: The literature search yielded unique 367 papers, 348 were excluded after screening of title/abstract, and 16 after full-text screening. Three guidelines were included: the American College of Gastroenterology (ACG; 2014), Brazilian Society of Hepatology (SBH; 2015), and European Association for the Study of the Liver (EASL; 2016). There was no uniformity in the assessment methods for grading and gravity of recommendations between guidelines. Among observed differences were: (1) indications for biopsy in all three tumours; (2) advices on contraceptive pills and follow-up in FNH and HCA; (3) use of an individualised approach to HCA; (4) absence of recommendations for treatment of HCA in men; and (5) approaches to HCA subtype identification on magnetic resonance imaging. CONCLUSION: Recognising differences in recommendations can assist in harmonisation of practice standards and identify unmet needs in research. This may ultimately contribute to improved global patient care

Doppler Ultrasound of Vascular Complications After Pediatric Liver Transplantation:Incidence, Time of Detection, and Positive Predictive Value

Purpose Doppler ultrasound (DUS) is widely used to detect vascular complications after pediatric liver transplantation (LT). This study aimed to assess the moment of first detection of vascular complications with DUS, and to determine the positive predictive value (PPV) of DUS. Materials and Methods Patients aged 0–18 years who underwent LT between 2015 and 2019 were retrospectively included. 92 LTs in 83 patients were included (median age: 3.9 years, interquartile range: 0.7–10.5). Patients underwent perioperative (intra-operative and immediately postoperative) and daily DUS surveillance during the first postoperative week, and at 1, 3, and 12 months. Vascular complications were categorized for the hepatic artery, portal vein, and hepatic veins. DUS findings were compared to surgical or radiological findings during the 1-year follow-up. Results 52 vascular complications were diagnosed by DUS in 35/92 LTs (38%). 15 out of 52 (28.8%) were diagnosed perioperatively, 29/52 (55.8%) were diagnosed on postoperative days 1–7, and 8/52 (15.4%) after day 7. The PPV for all vascular complications diagnosed with DUS was 92.3%. During the 1-year follow-up, 18/19 (94.7%) hepatic artery complications, 19/26 (73.1%) portal vein complications, and 7/7 (100%) hepatic vein complications were diagnosed perioperatively or during the first week. Conclusion The majority of vascular complications during the first year after pediatric LT were diagnosed by DUS perioperatively or during the first week, with a high PPV. Our findings provide important information regarding when to expect different types of vascular complications on DUS, which might improve DUS post-LT surveillance protocols

Diagnostic performance of preoperative CT in differentiating between benign and malignant origin of suspicious gallbladder lesions

Purpose: To determine diagnostic performance of preoperative CT in differentiating between benign and malignant suspicious gallbladder lesions and to develop a preoperative risk score. Method: All patients referred between January 2007 and September 2018 for suspicion of gallbladder cancer (GBC) or incidentally found GBC were retrospectively analyzed. Patients were excluded when preoperative CT or histopathologic examination was lacking. Two radiologists, blinded to histopathology results, independently reviewed CT images to differentiate benign disease from GBC. Multivariable analysis and internal validation were used to develop a risk score for GBC. Model discrimination, calibration, and diagnostic performance were assessed. Results: In total, 118 patients with 39 malignant (33 %) and 79 benign (67 %) lesions were included. Sensitivity of CT for diagnosing GBC was 90 % (95 % confidence interval [CI]: 76?97). Specificity rates were 61 % (95 % CI: 49?72) and 59 % (95 % CI: 48?70). Three predictors of GBC (irregular lesion aspect, absence of fat stranding, and locoregional lymphadenopathy) were included in the risk score ranging from -1 to 4. Adequate performance was found (AUC: 0.79, calibration slope: 0.89). In patients allocated >0 points, the model showed higher performance in excluding GBC than the radiologists (sensitivity 92 % [95 % CI: 79?98]). Moreover, when allocated >3 points, the risk score was superior in diagnosing GBC (specificity 99 % [95 % CI: 93?100]). Conclusions: Sensitivity rates of CT for differentiation between benign and malignant gallbladder lesions are high, however specificity rates are relatively low. The proposed risk score may facilitate differentiation between benign and malignant suspicious gallbladder lesions

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

BACKGROUND: Post-therapy [(90)Y] PET/CT-based dosimetry is currently recommended to validate treatment planning as [(99m)Tc] MAA SPECT/CT is often a poor predictor of subsequent actual [(90)Y] 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 [(90)Y] 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 [(90)Y] SIRT could play a role in evaluative dosimetry

Combining Hepatic and Splenic CT Radiomic Features Improves Radiomic Analysis Performance for Liver Fibrosis Staging

Background: The exact focus of computed tomography (CT)-based artificial intelligence techniques when staging liver fibrosis is still not exactly known. This study aimed to determine both the added value of splenic information to hepatic information, and the correlation between important radiomic features and information exploited by deep learning models for liver fibrosis staging by CT-based radiomics. Methods: The study design is retrospective. Radiomic features were extracted from both liver and spleen on portal venous phase CT images of 252 consecutive patients with histologically proven liver fibrosis stages between 2006 and 2018. The radiomics analyses for liver fibrosis staging were done by hepatic and hepatic–splenic features, respectively. The most predictive radiomic features were automatically selected by machine learning models. Results: When using splenic–hepatic features in the CT-based radiomics analysis, the average accuracy rates for significant fibrosis, advanced fibrosis, and cirrhosis were 88%, 82%, and 86%, and area under the receiver operating characteristic curves (AUCs) were 0.92, 0.81, and 0.85. The AUC of hepatic–splenic-based radiomics analysis with the ensemble classifier was 7% larger than that of hepatic-based analysis (p < 0.05). The most important features selected by machine learning models included both hepatic and splenic features, and they were consistent with the location maps indicating the focus of deep learning when predicting liver fibrosis stage. Conclusions: Adding CT-based splenic radiomic features to hepatic radiomic features increases radiomics analysis performance for liver fibrosis staging. The most important features of the radiomics analysis were consistent with the information exploited by deep learning

Liver fibrosis staging by deep learning:a visual-based explanation of diagnostic decisions of the model

OBJECTIVES: Deep learning has been proven to be able to stage liver fibrosis based on contrast-enhanced CT images. However, until now, the algorithm is used as a black box and lacks transparency. This study aimed to provide a visual-based explanation of the diagnostic decisions made by deep learning. METHODS: The liver fibrosis staging network (LFS network) was developed at contrast-enhanced CT images in the portal venous phase in 252 patients with histologically proven liver fibrosis stage. To give a visual explanation of the diagnostic decisions made by the LFS network, Gradient-weighted Class Activation Mapping (Grad-cam) was used to produce location maps indicating where the LFS network focuses on when predicting liver fibrosis stage. RESULTS: The LFS network had areas under the receiver operating characteristic curve of 0.92, 0.89, and 0.88 for staging significant fibrosis (F2-F4), advanced fibrosis (F3-F4), and cirrhosis (F4), respectively, on the test set. The location maps indicated that the LFS network had more focus on the liver surface in patients without liver fibrosis (F0), while it focused more on the parenchyma of the liver and spleen in case of cirrhosis (F4). CONCLUSIONS: Deep learning methods are able to exploit CT-based information from the liver surface, liver parenchyma, and extrahepatic information to predict liver fibrosis stage. Therefore, we suggest using the entire upper abdomen on CT images when developing deep learning-based liver fibrosis staging algorithms. KEY POINTS: • Deep learning algorithms can stage liver fibrosis using contrast-enhanced CT images, but the algorithm is still used as a black box and lacks transparency. • Location maps produced by Gradient-weighted Class Activation Mapping can indicate the focus of the liver fibrosis staging network. • Deep learning methods use CT-based information from the liver surface, liver parenchyma, and extrahepatic information to predict liver fibrosis stage

Assessment of hepatic artery anatomy in pediatric liver transplant recipients:MR angiography versus CT angiography

During LT screening, children undergo CTA to determine hepatic artery anatomy. However, CTA imparts radiation, unlike MRA. The aim was to compare MRA to CTA in assessing hepatic artery anatomy in pediatric LT recipients. Twenty-one children (median age 8.9 years) who underwent both CTA and fl3D-ce MRA before LT were retrospectively included. Interreader variability between 2 radiologists, image quality, movement artifacts, and confidence scores, were used to compare MRA to CTA. Subgroup analyses for ages <6 years and ≥6 years were performed. Interreader variability for MRA and CTA in children <6 years was comparable (k = 0.839 and k = 0.757, respectively), while in children ≥6 years CTA was superior to MRA (k 1.000 and k 0.000, respectively). Overall image quality and confidence scores of CTA were significantly higher compared to MRA at all ages (2.8/3 vs. 2.3/3, p = .001; and 2.9/3 vs. 2.5/3, p = .003, respectively). Movement artifacts were significantly lower in CTA compared to MRA in children ≥6 years (1.0/3 vs. 1.7/3, p = .010, respectively). CTA is preferred over fl3D-ce MRA for the preoperative assessment of hepatic artery anatomy in children receiving LT, both at ages <6 years and ≥6 years

Doppler-ultrasound reference values after pediatric liver transplantation:a consecutive cohort study

OBJECTIVES: Doppler ultrasound (DUS) is the main imaging modality to evaluate vascular complications of pediatric liver transplants (LT). The current study aimed to determine reference values and their change over time.METHODS: A consecutive cohort of pediatric patients undergoing an LT were retrospectively included between 2015 and 2020. Timepoints for standardized DUS were intra-operative and postoperative (day 0), days 1-7, months 1 and 3, and years 1 and 2. DUS measurements of the hepatic artery (HA), portal vein (PV), and hepatic vein(s) (HV) were included if there were no complications during 2 years follow-up. Measurements consisted of: peak systolic velocity (PSV) and resistive index (RI) for the HA, PSV for the PV, and venous pulsatility index (VPI) for the HV. Generalized estimating equations were used to analyze change over time.RESULTS: One hundred twelve pediatric patients with 123 LTs were included (median age 3.3 years, interquartile range 0.7-10.1). Ninety-five HAs, 100 PVs, and 115 HVs without complications were included. Reference values for HA PSV and RI, PV PSV, and HV VPI were obtained for all timepoints (4043 included data points in total) and presented using 5th-95th percentiles and threshold values. All reference values changed significantly over time (p = 0.032 to p &lt; 0.001).CONCLUSIONS: DUS reference values of hepatic vessels in children after LT are presented, reference values change over time with specific vessel-dependent patterns. Timepoint-specific reference values improve the interpretation of DUS values and may help to better weigh their clinical significance.KEY POINTS: • Doppler ultrasound reference values of pediatric liver transplantations are not static but change over time. Applying the correct reference values for the specific timepoint may further improve the interpretation of the measurements. • The pattern of change over time of Doppler ultrasound measurements differs between the hepatic vessel and measurement; knowledge of these patterns may help radiologists to better understand normal postoperative hemodynamic changes.</p