Portal vein embolization following arterial portography for the management of an active portal bleeding after blunt liver trauma in a cirrhotic patient.

BACKGROUND: The management of blunt liver trauma in cirrhotic patients is challenging, because while bleeding is most often of arterial origin, the increased pressure in the portal system associated with cirrhosis can increase the risk of portal bleeding, which is sometimes difficult to confirm on contrast-enhanced abdominal computed tomography. CASE PRESENTATION: We managed a 54-year-old cirrhotic patient who presented with blunt liver trauma. Computed Tomography showed active intraperitoneal bleeding presumed to be of hepatic origin. Given the patient's hemodynamic stability, the decision was made to manage the patient non-surgically. The patient underwent hepatic arteriography to rule out an arterial origin to the bleeding. A superior mesenteric arterial portography confirmed the portal venous origin of the bleeding. To stop the bleeding, a distal portal vein embolization using coils and glue was performed by approaching a large paraumbilical vein. CONCLUSIONS: Our case study shows the value of arterial portography in the management of these patients, when they are clinically stable enough to benefit from non-surgical management; This allows arterial bleeding to be excluded on hepatic arteriography, portal bleeding to be confirmed on portography following arteriography in the superior mesenteric artery, and guidance of portal vein embolization.

Polycystic liver: automatic segmentation using deep learning on CT is faster and as accurate compared to manual segmentation.

OBJECTIVE: This study aimed to develop and investigate the performance of a deep learning model based on a convolutional neural network (CNN) for the automatic segmentation of polycystic livers at CT imaging. METHOD: This retrospective study used CT images of polycystic livers. To develop the CNN, supervised training and validation phases were performed using 190 CT series. To assess performance, the test phase was performed using 41 CT series. Manual segmentation by an expert radiologist (Rad1a) served as reference for all comparisons. Intra-observer variability was determined by the same reader after 12 weeks (Rad1b), and inter-observer variability by a second reader (Rad2). The Dice similarity coefficient (DSC) evaluated overlap between segmentations. CNN performance was assessed using the concordance correlation coefficient (CCC) and the two-by-two difference between the CCCs; their confidence interval was estimated with bootstrap and Bland-Altman analyses. Liver segmentation time was automatically recorded for each method. RESULTS: A total of 231 series from 129 CT examinations on 88 consecutive patients were collected. For the CNN, the DSC was 0.95 ± 0.03 and volume analyses yielded a CCC of 0.995 compared with reference. No statistical difference was observed in the CCC between CNN automatic segmentation and manual segmentations performed to evaluate inter-observer and intra-observer variability. While manual segmentation required 22.4 ± 10.4 min, central and graphics processing units took an average of 5.0 ± 2.1 s and 2.0 ± 1.4 s, respectively. CONCLUSION: Compared with manual segmentation, automated segmentation of polycystic livers using a deep learning method achieved much faster segmentation with similar performance. KEY POINTS: • Automatic volumetry of polycystic livers using artificial intelligence method allows much faster segmentation than expert manual segmentation with similar performance. • No statistical difference was observed between automatic segmentation, inter-observer variability, or intra-observer variability.

Partial major hepatectomy with cyst fenestration for polycystic liver disease: Indications, short and long-term outcomes.

BACKGROUND AND OBJECTIVE: Symptomatic polycystic liver disease (PLD) with massive hepatomegaly represents a challenging surgical issue. In this work, we focused on early and long term outcomes after partial hepatectomy with cyst fenestration (PHCF) in selected patients. METHODS: All patients who had PHCF for treatment of PLD between January 2003 and December 2019 in our center were included in this study. PHCF was undertaken if at least one hepatic section was relatively spared from PLD, afferent and efferent hepatic vasculature was patent, and liver function was maintained. RESULTS: Twenty nine patients (25 women) with a mean age of 54.6 ±â€¯9 years underwent PHCF. Major hepatectomy was performed in all cases with 4.3 ±â€¯0.8 resected segments. Overall perioperative morbidity (Clavien ≥ II) and mortality rates were 41.4.6% and 13.8% respectively. Significant postoperative liver volume reduction was 52.8% within the first year and 55.5% thereafter. From preoperative evaluation, performance status (PS) normalized or improved in 84% of patients. After a mean follow-up time of 70.8 ±â€¯65 months, overall patient survival was 82.7%. In univariate analysis, PS, initial liver volume, operative time and transfusion were associated with post-operative complications and PS, preoperative cyst infection, portal hypertension, transfusion, postoperative sepsis and persistent ascites were associated with mortality. CONCLUSIONS: Our study confirms that in spite of significant morbidity rate, PHCF allows a massive reduction of liver volume in selected patients with symptomatic PLD and is highly and durably effective for the reduction of liver volume and improvement of quality of life.