Preoperative Prediction of Lymph Node Metastases in Nonfunctional Pancreatic Neuroendocrine Tumors Using a Combined CT Radiomics-Clinical Model.

BACKGROUND: PanNETs are a rare group of pancreatic tumors that display heterogeneous histopathological and clinical behavior. Nodal disease has been established as one of the strongest predictors of patient outcomes in PanNETs. Lack of accurate preoperative assessment of nodal disease is a major limitation in the management of these patients, in particular those with small (< 2 cm) low-grade tumors. The aim of the study was to evaluate the ability of radiomic features (RF) to preoperatively predict the presence of nodal disease in pancreatic neuroendocrine tumors (PanNETs). PATIENTS AND METHODS: An institutional database was used to identify patients with nonfunctional PanNETs undergoing resection. Pancreas protocol computed tomography was obtained, manually segmented, and RF were extracted. These were analyzed using the minimum redundancy maximum relevance analysis for hierarchical feature selection. Youden index was used to identify the optimal cutoff for predicting nodal disease. A random forest prediction model was trained using RF and clinicopathological characteristics and validated internally. RESULTS: Of the 320 patients included in the study, 92 (28.8%) had nodal disease based on histopathological assessment of the surgical specimen. A radiomic signature based on ten selected RF was developed. Clinicopathological characteristics predictive of nodal disease included tumor grade and size. Upon internal validation the combined radiomics and clinical feature model demonstrated adequate performance (AUC 0.80) in identifying nodal disease. The model accurately identified nodal disease in 85% of patients with small tumors (< 2 cm). CONCLUSIONS: Non-invasive preoperative assessment of nodal disease using RF and clinicopathological characteristics is feasible.

MR imaging for preoperative characterization of pelvic adhesions: role in diagnosis and surgical planning.

Pelvic adhesions are nonanatomic connections between organs and normal peritoneal surfaces that develop secondary to a maladaptive inflammatory response to tissue insults. Comprised of fibrous tissue, adhesions can result in the distortion of operative dissection planes, which can complicate the establishment of abdominal access in patients undergoing surgery, prolong the length of surgery, and increase the risk of injury to bowel and other structures if involved by extensive adhesive disease. This can adversely impact patient outcomes by increasing the risk of surgical complications including bleeding, infection, and prolonging postoperative length of stay. Literature on the characterization of adhesions with imaging is limited and a systematic framework for evaluating adhesive disease on cross-sectional imaging of the pelvis does not currently exist. In this review, we discuss the MR imaging features of pelvic adhesions, highlighting unique teaching cases in which surgical exploration was significantly complicated by the presence of adhesive disease. We will also review the correlation between MR imaging and intraoperative findings in these cases. A proposed standardized framework for the detection and characterization of adhesions on pelvic MRI will be reviewed with multiple imaging examples. Identification and characterization of pelvic adhesive disease on preoperative imaging provides radiologists with an opportunity to inform the referring clinician of their presence, potentially improving outcomes and the quality of patient care.

Cinematic rendering of primary adrenal lymphoma.

Primary adrenal lymphoma (PAL) is a particularly rare subset of malignant adrenal neoplasms, accounting for ∼1% of all non-Hodgkin's lymphomas. Reported outcomes of PAL, though limited, are dismal, with a 12-month survival rate of ∼20%. PAL is treated with polychemotherapy and early tissue diagnosis to allow initiation of chemotherapy is associated with improved outcomes. Early and accurate radiological diagnosis of PAL is therefore essential in improving outcomes through informing decisions to biopsy and thereby facilitating timely initiation of chemotherapy. To date, however, imaging features of PAL have not been conclusively defined, and a range of divergent imaging appearances have been reported. Cinematic rendering (CR) is a 3D post-processing technique that simulates the propagation and interaction of photons as they pass through the imaged volume. This results in the generation of more photorealistic images that may allow for more comprehensive visualization, description and interpretation of anatomical structures. This manuscript presents the first characterization of the various CR appearances of PAL in the reported literature and provides commentary on the clinical opportunities afforded by CR in the workup of these heterogenous tumors.

Early detection of pancreatic cancer in the era of precision medicine.

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related mortality and it is often diagnosed at advanced stages due to non-specific clinical presentation. Disease detection at localized disease stage followed by surgical resection remains the only potentially curative treatment. In this era of precision medicine, a multifaceted approach to early detection of PDAC includes targeted screening in high-risk populations, serum biomarkers and "liquid biopsies", and artificial intelligence augmented tumor detection from radiologic examinations. In this review, we will review these emerging techniques in the early detection of PDAC.

Hidden in plain sight: commonly missed early signs of pancreatic cancer on CT.

Pancreatic ductal adenocarcinoma (PDAC) has poor prognosis mostly due to the advanced stage at which disease is diagnosed. Early detection of disease at a resectable stage is, therefore, critical for improving outcomes of patients. Prior studies have demonstrated that pancreatic abnormalities may be detected on CT in up to 38% of CT studies 5 years before clinical diagnosis of PDAC. In this review, we highlight commonly missed signs of early PDAC on CT. Broadly, these commonly missed signs consist of small isoattenuating PDAC without contour deformity, isolated pancreatic duct dilatation and cutoff, focal pancreatic enhancement and focal parenchymal atrophy, pancreatitis with underlying PDAC, and vascular encasement. Through providing commentary on demonstrative examples of these signs, we demonstrate how to reduce the risk of missing or misinterpreting radiological features of early PDAC.

Cinematic Rendering of Pancreatic Neuroendocrine Tumours: Opportunities for Clinical Implementation: Part 1: Tumour Detection and Characterization.

Pancreatic neuroendocrine tumours (PNETs) are a rare subset of pancreatic tumours that have historically comprised up to 3% of all clinically detected pancreatic tumours. In recent decades, however, advancements in imaging have led to an increased incidental detection rate of PNETs and imaging has played an increasingly central role in the initial diagnostics and surgical planning of these tumours. Cinematic rendering (CR) is a 3D post-processing technique that generates highly photorealistic images through more realistically modelling the path of photons through the imaged volume. This allows for more comprehensive visualization, description, and interpretation of anatomical structures. In this 2-part review article, we present the first description of the various CR appearances of PNETs in the reported literature while providing commentary on the unique clinical opportunities afforded by the adjunctive utilization of CR in the workup of these rare tumours. The first of these 2 instalments highlights the utility of CR in optimizing PNET detection and characterization.

Cinematic Rendering of Pancreatic Neuroendocrine Tumours: Opportunities for Clinical Implementation: Part 2: Preoperative Planning and Evaluation of Metastatic Disease.

Pancreatic neuroendocrine tumours (PNETs) are a rare subset of pancreatic tumours that have historically comprised up to 3% of all clinically detected pancreatic tumours. In recent decades, however, advancements in imaging have led to an increased incidental detection rate of PNETs and imaging has played an increasingly central role in the initial diagnostics and surgical planning of these tumours. Cinematic rendering (CR) is a 3D post-processing technique that generates highly photorealistic images through more realistically modelling the path of photons through the imaged volume. This allows for more comprehensive visualization, description, and interpretation of anatomical structures. In this 2-part review article, we present the first description of the various CR appearances of PNETs in the reported literature while providing commentary on the unique clinical opportunities afforded by the adjunctive utilization of CR in the workup of these rare tumours. This second instalment focuses on the applications of CR in optimizing preoperative planning of PNETs.

Cinematic rendering of solid pseudopapillary tumors: Augmenting diagnostics of an increasingly encountered tumor.

Pancreatic solid pseudopapillary tumors (SPTs) are a rare subset of pancreatic neoplasms, accounting for under 2 % of exocrine pancreatic tumors. The incidence of SPTs has shown a significant increase in the past two decades, attributed to heightened cross-sectional imaging utilization. These tumors often present with nonspecific clinical symptoms, making imaging a crucial tool in their detection and diagnosis. Cinematic rendering (CR) is an advanced 3D post-processing technique that generates highly photorealistic realistic images by accurately modeling the interaction of light within the imaged volume. This allows improved visualization of anatomic structures which holds potential to improve diagnostics. In this manuscript we present the first description of CR appearances of SPTs in the reported literature. Through showcasing a range of cases, we highlight the potential of CR in illustrating the diverse imaging characteristics of these unique neoplasms.

Three-dimensional CT cinematic rendering of adrenal masses: Role in tumor analysis and management.

The adrenal gland is home to an array of complex physiological and neoplastic disease processes. While dedicated adrenal computed tomography (CT) is the gold standard imaging modality for adrenal lesions, there exists significant overlap among imaging features of adrenal pathology. This can often make radiological diagnosis and subsequent determination of the optimal surgical approach challenging. Cinematic rendering (CR) is a novel CT post-processing technique that utilizes advanced light modeling to generate highly photorealistic anatomic visualization. This generates unique prospects in the evaluation of adrenal masses. As one of the first large tertiary care centers to incorporate CR into routine diagnostic workup, our preliminary experience with using CR has been positive, and we have found CR to be a valuable adjunct during surgical planning. Herein, we highlight the unique utility of CR techniques in the workup of adrenal lesions and provide commentary on the opportunities and obstacles associated with the application of this novel display method in this setting.

CT angiography for characterization of advanced placenta accreta spectrum: indications, risks, and benefits.

Placenta accreta spectrum disorder (PASD) encompasses various types of abnormal placentation in which chorionic villi directly adhere to or invade the myometrium. The incidence of PASD has dramatically risen in the US over the past 3 decades owing to the increased rates of patients undergoing cesarean sections. While PASD remains a significant cause of maternal morbidity and mortality, accurate prenatal identification and characterization of PASD is associated with improved outcomes. Although ultrasound is the first-line imaging modality in the evaluation of PASD, with MRI serving as an adjunct, computed tomography angiography (CTA) may also offer unique diagnostic advantages in cases of advanced PASD by providing superior visualization of placental and abdominopelvic vasculature and enabling the creation of comprehensive vascular maps to roadmap complex surgical interventions. This paper represents the first evaluation of CTA as a diagnostic tool and operative planning aid in this context. Appropriate indications and diagnostic advantages of CTA in this setting are reviewed, and key multimodal imaging features of normal and abnormal placentation are highlighted.

CT of retroperitoneal solitary fibrous tumor.

Solitary fibrous tumors are rare tumors of pluripotent fibroblastic or myofibroblastic origin that generally arise among older individuals, with a mean age of onset ranging from 55 to 65 years. Though typically associated with pleural involvement, solitary fibrous tumors can emerge in virtually every anatomic location within the body. Although most solitary fibrous tumors are benign, approximately 20% may exhibit malignant features such as local invasion, recurrence, and metastases. In this article, we report the case of a 58-year-old male with a diagnosis of a retroperitoneal solitary fibrous tumor. We analyze computed tomography imaging findings and additionally correlate imaging features with the patient's unique pathological and genotypic findings to optimize diagnosis.

A primer on artificial intelligence in pancreatic imaging.

Artificial Intelligence (AI) is set to transform medical imaging by leveraging the vast data contained in medical images. Deep learning and radiomics are the two main AI methods currently being applied within radiology. Deep learning uses a layered set of self-correcting algorithms to develop a mathematical model that best fits the data. Radiomics converts imaging data into mineable features such as signal intensity, shape, texture, and higher-order features. Both methods have the potential to improve disease detection, characterization, and prognostication. This article reviews the current status of artificial intelligence in pancreatic imaging and critically appraises the quality of existing evidence using the radiomics quality score.

A Rare Presentation of a True Intra-articular Lipoma: A Case Report and Review of Imaging Findings.

This report describes the unique case of an intra-articular lipoma in a 34-year-old male. The patient presented with a history of chronic knee pain associated with an intermittent sensation of the knee giving way. Physical examination and initial radiographic imaging were unremarkable. Magnetic resonance imaging (MRI) revealed a 9.2 x 6.7 mm ovoid mass posterior to the posterior cruciate ligament (PCL) exhibiting hyperintense signals on T1-weighted images and intermediate-to-high intensity signals on T2. On subsequent proton density fat suppression sequences, the mass demonstrated homogenous signal suppression and was confirmed as being a lipoma. To the best of our knowledge, this is only the second reported case of an intra-articular lipoma arising posterior to the PCL. Intra-articular lipomas, albeit rare, should be considered in the differential diagnosis for chronic knee pain with associated joint motion abnormalities. MRI remains the gold standard in imaging intra-articular soft tissue pathology and should be the study of choice in differentiating intra-articular lipomas from similar conditions such as pigmented villonodular synovitis and lipoma arborescens.

Epidemiology, outcomes, and prognostic factors of orbital lymphoma in the United States.

PURPOSE: We performed an epidemiological study of orbital lymphoma in the United States to determine how histological subtypes confer differing prognosis, and understand other factors associated with survival. METHODS: All patients in the Surveillance, Epidemiology and End Results database diagnosed with a histologically confirmed orbital lymphoma between 1973 and 2014 were included. Exclusion criteria included diagnosis at autopsy and the presence of other malignancies. Measures included patient demographic information, histological subtype and treatment modalities. Outcomes included overall and disease specific survival. RESULTS: Of the 1504 cases identified, 702 were male (46.7%, mean age: 64.4 years, standard deviation [SD]: 15.3) and 802 were female (53.3%, mean age: 67.5 years, SD: 14.3). Mucosal associated lymphoid tissue (MALT) (49.5%) and diffuse large B cell lymphoma (DLBCL) (19.5%) were the two most common histologic subtypes. MALT lymphoma conferred the best prognosis (10-year cancer specific survival [CSS] 90.2%, 95% Confidence Interval [CI] 87.4% - 93.1%) and DLBCL conferred the worst prognosis (10-year CSS 68.6%, 95% CI 62.5% - 75.3%) (p < .001, log-rank test). Older age (Hazard Ratio [HR]: 3.71, 95% Confidence Interval [CI]: 2.94-4.66, p < .001), male sex (HR: 1.22, 95% CI: 1.039-1.441, p = .015), no radiation (HR: 1.72, 95% CI: 1.46-2.02, p < .001) and DLBCL histology were significant predictors of worse overall survival. CONCLUSIONS: DLBCL histology confers the worst outcomes whereas MALT lymphoma confers the best outcome in orbital lymphoma. Age, gender, and radiation treatment also influence survival. These epidemiological results can be used clinically to communicate outcomes on the basis of patient characteristics and disease histology.