Pancreatic surgery is considered one of the most technically challenging surgical procedures, despite the evolution of modern techniques. Neoplasms remain the most common indication for pancreatic surgery, although inflammatory conditions may also prompt surgical evaluation. The choice of surgical procedure depends on the type and location of the pathologic finding because different parts of the pancreas have separate vascular supplies that may be shared by adjacent organs. The surgical approach could be conventional or minimally invasive (laparoscopic, endoscopic, or robotic assisted). Because of the anatomic complexity of the pancreatic bed, perioperative complications may be frequently encountered and commonly involve the pancreatic-biliary, vascular, lymphatic, or bowel systems, irrespective of the surgical technique used. Imaging plays an important role in the assessment of suspected postoperative complications, with CT considered the primary imaging modality, while MRI, digital subtraction angiography, and molecular imaging are considered ancillary diagnostic tools. Accurate diagnosis of postoperative complications requires a solid understanding of pancreatic anatomy, surgical indications, normal postoperative appearance, and expected postsurgical changes. The practicing radiologist should be familiar with the most common perioperative complications, such as anastomotic leak, abscess, and hemorrhage, and be able to differentiate these entities from normal anticipated postoperative changes such as seroma, edema and fat stranding at the surgical site, and perivascular soft-tissue thickening. In addition to evaluation of the primary operative fossa, imaging plays a fundamental role in assessment of the adjacent organ systems secondarily affected after pancreatic surgery, such as vascular, biliary, and enteric complications. Published under a CC BY 4.0 license. Test Your Knowledge questions are available in the supplemental material. See the invited commentary by Winslow in this issue.

PURPOSE: Variability in computed tomography images intrinsic to individual scanners limits the application of radiomics in clinical and research settings. The development of reproducible and generalizable radiomics-based models to assess lesions requires harmonization of data. The purpose of this study was to develop, test, and analyze the efficacy of a radiomics data harmonization model. MATERIALS AND METHODS: Radiomic features from biopsy-proven untreated hepatic metastasis (N = 380) acquired from 167 unique patients with pancreatic, colon, and breast cancers were analyzed. Radiomic features from volume-match 551 samples of normal liver tissue and 188 hepatic cysts were included as references. A novel linear mixed effect model was used to identify effects associated with lesion size, tissue type, and scanner model. Six separate machine learning models were then used to test the effectiveness of radiomic feature harmonization using multivariate analysis. RESULTS: Proposed model identifies and removes scanner-associated effects while preserving cancer-specific functional dependence of radiomic features on the tumor size. Data harmonization improves the performance of classification models by reducing the scanner-associated variability. For example, the multiclass logistic regression model, LogitBoost, demonstrated the improvement in sensitivity in the range from 15% to 40% for each type of liver metastasis, whereas the overall model accuracy and the kappa coefficient increased by 5% and 8% accordingly. CONCLUSION: The model removed scanner-associated effects while preserving cancer-specific functional dependence of radiomic features.

Elder abuse often goes unrecognized until it is too late, but radiologists can play an essential role in detecting and reporting elder abuse through recognition of injury patterns that are characte... Elder abuse may result in serious physical injuries and long-term psychological consequences and can be life threatening. Over the past decade, attention to elder abuse has increased owing to its h...

Patients often have symptoms due to the mass effect of a neoplasm on surrounding tissues or the development of distant metastases. However, some patients may present with clinical symptoms that are not attributable to direct tumor invasion. In particular, certain tumors may release substances such as hormones or cytokines or trigger an immune cross-reactivity between malignant and normal body cells, resulting in characteristic clinical features that are broadly referred to as paraneoplastic syndromes (PNSs). Recent advances in medicine have improved the understanding of the pathogenesis of PNSs and enhanced their diagnosis and treatment. It is estimated that 8% of patients with cancer develop a PNS. Diverse organ systems may be involved, most notably the neurologic, musculoskeletal, endocrinologic, dermatologic, gastrointestinal, and cardiovascular systems. Knowledge of various PNSs is necessary, as these syndromes may precede tumor development, complicate the patient's clinical presentation, indicate tumor prognosis, or be mistaken for metastatic spread. Radiologists should be familiar with the clinical presentations of common PNSs and the selection of appropriate imaging examinations. Many of these PNSs have imaging features that can assist with arriving at the correct diagnosis. Therefore, the key radiographic findings associated with these PNSs and the diagnostic pitfalls that can be encountered during imaging are important, as their detection can facilitate early identification of the underlying tumor, reveal early recurrence, and enable monitoring of the patient's response to therapy. ^© RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Objectives: Adrenal adenoma with myelolipomatous degeneration (AMD) is a rarely reported and often overlooked entity. The aim of this study is to improve understanding of these lesions by characterizing the imaging findings with pathologic and clinical correlation. Methods: In the largest series to date, we report 11 nodules in 11 patients confirmed with a pathologic diagnosis of AMD. The available cross-sectional imaging and histopathologic features were reviewed by two radiologists and two pathologists, respectively. Clinical and laboratory data for each patient were obtained from the electronic medical records, when available. Results: All 11 patients had a CT prior to resection or biopsy of the adrenal nodule, with five having received an adrenal mass protocol study. An MRI was available in three patients. The median size of the nodules on imaging was 4.5 cm (range 2.8–8.7) and all but one had macroscopic fat. The largest focus of macroscopic fat had a median size of 0.7 cm (range 0.2–1.6) and on average was 14.4% the size of the tumor, using greatest dimensions. Four (36.4%) patients had a diagnosis of Cushing syndrome prior to nodule resection. Conclusions: Not all adrenal nodules with macroscopic fat on imaging are pure myelolipomas. An AMD should be considered, especially if the foci of fat are small and other features of an adenoma are present. Some may also be associated with Cushing syndrome. Advances in knowledge: Myelolipomatous degeneration within an adrenal adenoma has only rarely been previously reported with very few reports emphasizing the imaging features. There may be an association with cortisol hypersecretion and improved recognition of this entity could lead to changes in clinical management.