Liver Imaging in Gastroenteropancreatic Neuroendocrine Neoplasms.

ABSTRACT: The incidence of neuroendocrine neoplasms (NENs) has gradually increased over the past few decades with the majority of patients presenting with metastases on initial presentation. The liver is the most common site of initial metastatic disease, and the presence of liver metastasis is an independent prognostic factor associated with a negative outcome. Because NENs are heterogenous neoplasms with variable differentiation, grading, and risk of grade transformation over time, accurate diagnosis and management of neuroendocrine liver lesions are both important and challenging. This is particularly so with the multiple liver-directed treatment options available. In this review article, we discuss the diagnosis, treatment, and response evaluation of NEN liver metastases.

Immune Checkpoint Inhibitor-Induced Pancreatic Injury: Clinical and Radiological Profile and Response to Steroids.

Background and Aims: Immune checkpoint inhibitor therapy causes numerous immune-related adverse events, including autoimmune pancreatic injury (AIPI), which results in rapid organ atrophy. We profiled the clinico-radiological features, short-term natural history, and response to steroids of AIPI. Methods: We retrospectively reviewed medical records of 229/11,165 (2.1%) adult patients with AIPI. One hundred and ten out of 229 (48%) had abdominal computerized tomography (CT) scan at lipase elevation; data of 110 without pancreatic metastases were analyzed. We analyzed serial CT-based pancreas volumetry data in 48 patients with AIPI (32 with normal CT and 16 with pancreatitis on CT at lipase elevation). We examined impact of steroids on pain and disease course. Results: In AIPI (n = 229), median lipase elevation was 4x upper limit of normal (range: 3-40x). The injury was more often asymptomatic than painful (143/229 (62%) vs 86/229 (38%), P < .000). Majority (83/110 (75%) had normal CT, often in painless vs painful disease: 51/57 (90%) vs 32/53 (60%), P < .001) 25% had interstitial pancreatitis. On serial pancreas volumetry, marked volume (cc) loss occurred 1 year after vs 3 months before lipase elevation in both normal CT (median 81.6 vs 61.3, P = .00) and pancreatitis on CT groups (91.8 vs 60.5, P = .00), ≥20% volume loss occurred in 47% vs 73%, respectively (P = .08). Steroids, when used did not mitigate pain, biochemical relapse, pancreas volume loss or 1-year diabetes incidence (7.2%). Conclusion: Autoimmune pancreatic injury (AIPI) is uniquely characterized by painless lipase elevation, normal pancreas on CT and rapid pancreatic volume loss on follow-up. Steroids do not appear to have a role in management.

Fully automated deep learning based auto-contouring of liver segments and spleen on contrast-enhanced CT images.

Manual delineation of liver segments on computed tomography (CT) images for primary/secondary liver cancer (LC) patients is time-intensive and prone to inter/intra-observer variability. Therefore, we developed a deep-learning-based model to auto-contour liver segments and spleen on contrast-enhanced CT (CECT) images. We trained two models using 3d patch-based attention U-Net ([Formula: see text] and 3d full resolution of nnU-Net ([Formula: see text] to determine the best architecture ([Formula: see text]. BA was used with vessels ([Formula: see text] and spleen ([Formula: see text] to assess the impact on segment contouring. Models were trained, validated, and tested on 160 ([Formula: see text]), 40 ([Formula: see text]), 33 ([Formula: see text]), 25 (CCH) and 20 (CPVE) CECT of LC patients. [Formula: see text] outperformed [Formula: see text] across all segments with median differences in Dice similarity coefficients (DSC) ranging 0.03-0.05 (p < 0.05). [Formula: see text], and [Formula: see text] were not statistically different (p > 0.05), however, both were slightly better than [Formula: see text] by DSC up to 0.02. The final model, [Formula: see text], showed a mean DSC of 0.89, 0.82, 0.88, 0.87, 0.96, and 0.95 for segments 1, 2, 3, 4, 5-8, and spleen, respectively on entire test sets. Qualitatively, more than 85% of cases showed a Likert score [Formula: see text] 3 on test sets. Our final model provides clinically acceptable contours of liver segments and spleen which are usable in treatment planning.