Pancreatic Serous Cystic Neoplasms and Mucinous Cystic Neoplasms: Differential Diagnosis by Combining Imaging Features and Enhanced CT Texture Analysis

ObjectiveTo establish a diagnostic model by combining imaging features with enhanced CT texture analysis to differentiate pancreatic serous cystadenomas (SCNs) from pancreatic mucinous cystadenomas (MCNs).Materials and MethodsFifty-seven and 43 patients with pathology-confirmed SCNs and MCNs, respectively, from one center were analyzed and divided into a training cohort (n = 72) and an internal validation cohort (n = 28). An external validation cohort (n = 28) from another center was allocated. Demographic and radiological information were collected. The least absolute shrinkage and selection operator (LASSO) and recursive feature elimination linear support vector machine (RFE_LinearSVC) were implemented to select significant features. Multivariable logistic regression algorithms were conducted for model construction. Receiver operating characteristic (ROC) curves for the models were evaluated, and their prediction efficiency was quantified by the area under the curve (AUC), 95% confidence interval (95% CI), sensitivity and specificity.ResultsFollowing multivariable logistic regression analysis, the AUC was 0.932 and 0.887, the sensitivity was 87.5% and 90%, and the specificity was 82.4% and 84.6% with the training and validation cohorts, respectively, for the model combining radiological features and CT texture features. For the model based on radiological features alone, the AUC was 0.84 and 0.91, the sensitivity was 75% and 66.7%, and the specificity was 82.4% and 77% with the training and validation cohorts, respectively.ConclusionThis study showed that a logistic model combining radiological features and CT texture features is more effective in distinguishing SCNs from MCNs of the pancreas than a model based on radiological features alone.

Cyst Type Differentiates Rathke Cleft Cysts From Cystic Pituitary Adenomas

PurposeA classification system for cystic sellar lesions does not exist. We propose a novel classification scheme for these lesions based on the heterogeneity of the cyst wall/contents and the presence of a solid component on imaging.MethodsWe retrospectively reviewed 205 patients’ medical records (2008–2020) who underwent primary surgery for a cystic sellar lesion. Cysts were classified a priori into 1 of 4 cyst types based on the heterogeneity of the cyst wall/contents and the presence of a solid component imaging. There was high interrater reliability. Univariable and multivariable models were used to estimate the ability of cyst type to predict the two most common diagnoses: Rathke cleft cyst (RCC) and cystic pituitary adenoma.ResultsThe frequencies of RCC and cystic pituitary adenoma in our cohort were 45.4% and 36.4%, respectively. Non-neoplastic lesions (e.g., arachnoid cysts and RCC) were more likely to be Type 1 or 2, whereas cystic neoplasms (e.g., pituitary adenomas and craniopharyngiomas) were more likely to be Type 3 or 4 (p<0.0001). Higher cyst types, compared to Type 1, had higher odds of being cystic pituitary adenomas compared to RCCs (OR: 23.7, p=0.033, and 342.6, p <0.0001, for Types 2 and 4, respectively). Lesions with a fluid-fluid level on preoperative MRI also had higher odds of being pituitary adenomas (OR: 12.7; p=0.023). Cystic pituitary adenomas were more common in patients with obesity (OR: 5.0, p=0.003) or symptomatic hyperprolactinemia (OR: 11.5; p<0.001, respectively). The multivariable model had a positive predictive value of 82.2% and negative predictive value of 86.4%.ConclusionWhen applied to the diagnosis of RCC versus cystic pituitary adenoma, higher cystic lesion types (Type 2 & 4), presence of fluid-fluid level, symptomatic hyperprolactinemia, and obesity were predictors of cystic pituitary adenoma. Further validation is needed, but this classification scheme may prove to be a useful tool for the management of patients with common sellar pathology.

Tumor Microenvironment in Pancreatic Intraepithelial Neoplasia

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive tumors with a poor prognosis. A characteristic of PDAC is the formation of an immunosuppressive tumor microenvironment (TME) that facilitates bypassing of the immune surveillance. The TME consists of a desmoplastic stroma, largely composed of cancer-associated fibroblasts (CAFs), immunosuppressive immune cells, immunoregulatory soluble factors, neural network cells, and endothelial cells with complex interactions. PDAC develops from various precursor lesions such as pancreatic intraepithelial neoplasia (PanIN), intraductal papillary mucinous neoplasms (IPMN), mucinous cystic neoplasms (MCN), and possibly, atypical flat lesions (AFL). In this review, we focus on the composition of the TME in PanINs to reveal detailed insights into the complex restructuring of the TME at early time points in PDAC progression and to explore ways of modifying the TME to slow or even halt tumor progression.

Multi-Phase CT-Based Radiomics Nomogram for Discrimination Between Pancreatic Serous Cystic Neoplasm From Mucinous Cystic Neoplasm

PurposeThis study aimed to develop and verify a multi-phase (MP) computed tomography (CT)-based radiomics nomogram to differentiate pancreatic serous cystic neoplasms (SCNs) from mucinous cystic neoplasms (MCNs), and to compare the diagnostic efficacy of radiomics models for different phases of CT scans.Materials and MethodsA total of 170 patients who underwent surgical resection between January 2011 and December 2018, with pathologically confirmed pancreatic cystic neoplasms (SCN=115, MCN=55) were included in this single-center retrospective study. Radiomics features were extracted from plain scan (PS), arterial phase (AP), and venous phase (VP) CT scans. Algorithms were performed to identify the optimal features to build a radiomics signature (Radscore) for each phase. All features from these three phases were analyzed to develop the MP-Radscore. A combined model comprised the MP-Radscore and imaging features from which a nomogram was developed. The accuracy of the nomogram was evaluated using receiver operating characteristic (ROC) curves, calibration tests, and decision curve analysis.ResultsFor each scan phase, 1218 features were extracted, and the optimal ones were selected to construct the PS-Radscore (11 features), AP-Radscore (11 features), and VP-Radscore (12 features). The MP-Radscore (14 features) achieved better performance based on ROC curve analysis than any single phase did [area under the curve (AUC), training cohort: MP-Radscore 0.89, PS-Radscore 0.78, AP-Radscore 0.83, VP-Radscore 0.85; validation cohort: MP-Radscore 0.88, PS-Radscore 0.77, AP-Radscore 0.83, VP-Radscore 0.84]. The combination nomogram performance was excellent, surpassing those of all other nomograms in both the training cohort (AUC, 0.91) and validation cohort (AUC, 0.90). The nomogram also performed well in the calibration and decision curve analyses.ConclusionsRadiomics for arterial and venous single-phase models outperformed the plain scan model. The combination nomogram that incorporated the MP-Radscore, tumor location, and cystic number had the best discriminatory performance and showed excellent accuracy for differentiating SCN from MCN.

P-P50 Analysis of the efficiency of the hepatobiliary multidisciplinary team meeting to identify quality improvement strategies

Background The multidisciplinary team meeting is the mainstay of management of patients with hepatopancreatobiliary (HPB) cancer and is considered the gold standard of care. Disadvantages of these meetings include large numbers of patients to be discussed covering multiple super-specialities over a short time span. This can lead to decision fatigue amongst clinicians. Logistical factors such as information technology and presence of clinicians with relevant expertise may also hamper the progress of the meeting. The aim of this study was to analyse the efficiency of our HPB MDT with a view to identifying multi-factorial quality improvement interventions. Methods 13 weeks of prospectively generated multidisciplinary team meeting outcomes were analysed from our departments weekly 150-minute long MDT meeting between 01/06/21 and 24/08/21. Patient demographics and pathology were noted. The number of overall discussions in each meeting were recorded. Number of patients in each sub-category (1. Regional pancreatic cancer service, 2. Hepatocellular carcinoma or liver adenoma, 3. pancreatic cystic neoplasms, 4. Gallbladder cancer and cholangiocarcinoma, 5. Pancreatic neuroendocrine tumours and 6. Other) were recorded. The number of patients without a recorded outcome was collated and reasons for no outcome being generated were categorised. Results 174/ 869 patients (20 %) did not receive an outcome from the meeting and were carried forward to the next week. Of the patients carried forward to the next week; 33/177 (18.6%) had no available histopathology following biopsies. Of these 33 patients, 23 did not have post-operative histopathology yet available for discussion. 82/177 (46 %) patients did not have the relevant investigations performed or available to move the discussion forward. These investigations were wide ranging and included radiological and endoscopic interventions. Of these, 19 patients (2 % over-all) had not had images sent across from a peripheral centre. 3 patients required both histology and radiology for further discussion. 59/869 (6%) of patients were not discussed due to time constraints. This equated to an average of 4 patients per meeting. Conclusions This study demonstrates the breadth and depth of a general HPB MDT. Strategies are required to simplify the MDT process to allow for time for discussion of the most complex patients, in particular those requiring surgery. Multifactorial reasons for a lack of MDT outcome at any single meeting have been found in this study. This signifies that a more robust triage process involving multiple specialities needs to be considered. Logistical factors also need to be in place allowing for transfer of relevant images from peripheral units. Histopathology reporting takes time and appropriate expectations for the availability of these results needs to be in place. The next step in this study is to identify and implement effective quality improvement strategies to improve outcome rates and allow more time for complex case discussions.

HYDATIC CYST OF THE LIVER OR HEPATIC MUCINOUS CYSTADENOMA

Mucinous cystadenomas of the liver are rare cystic neoplasms, often mistaken for simple cysts or hydatid cysts of the liver. They are generally benign tumors, often discovered incidentally on imaging or during independent surgeries. Despite their tendency to grow slowly, mucinous cystadenomas of the liver can reach symptomatic dimensions. And given their potential for malignant transformation into mucinous cystadenocarcinomas, a misdiagnosis can have serious secondary consequences. We report the case of a 55-year-old woman with chronic right hypochondrium pain in whom a mucinous cystadenoma of the liver was accidentally discovered during surgery for hepatic hydatid cyst at the general surgery department at the ARRAZI Hospital - UHC Mohammed VI in Marrakech, Morocco.