Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.     

Immune Checkpoint Inhibitor Toxicities

Immune checkpoint inhibitors are molecules that increase the endogenous immune response against tumors. They have revolutionized the field of oncology. Since their initial approval for the treatment of advanced melanoma, their use has expanded to the treatment of several other advanced cancers. Unfortunately, immune checkpoint inhibitors have also been associated with the emergence of a new subset of autoimmune-like toxicities, known as immune-related adverse events. These toxicities differ depending on the agent, malignancy, and individual susceptibilities. Although the skin and colon are most commonly involved, any organ may be affected, including the liver, lungs, kidneys, and heart. Most of these toxicities are diagnosed by excluding other secondary infectious or inflammatory causes. Corticosteroids are commonly used for treatment of moderate and severe immune-related adverse events, although additional immunosuppressive therapy may occasionally be required. The occurrence of immune-related toxicities may require discontinuation of immunotherapy, depending on the specific toxicity and its severity. In this article, we provide a focused review to familiarize practicing clinicians with this important topic given that the use of immune checkpoint inhibitors continues to increase.     

Investigation of the mechanisms of Genkwa Flos hepatotoxicity by a cell metabolomics strategy combined with serum pharmacology in HL-7702 liver cells

1. To investigate Genkwa Flos hepatotoxicity, a cell metabolomics strategy combined with serum pharmacology was performed on human HL-7702 liver cells in this study.

2. Firstly, cell viability and biochemical indicators were determined and the cell morphology was observed to confirm the cell injury and develop a cell hepatotoxicity model. Then, with the help of cell metabolomics based on UPLC-MS, the Genkwa Flos group samples were completely separated from the blank group samples in the score plots and seven upregulated as well as two down-regulated putative biomarkers in the loading plot were identified and confirmed. Besides, two signal molecules and four enzymes involved in biosynthesis pathway of lysophosphatidylcholine and the sphingosine kinase/sphingosine-1-phosphate pathway were determined to investigate the relationship between Genkwa Flos hepatotoxicity and these two classic pathways. Finally, the metabolic pathways related to specific biomarkers and two classic metabolic pathways were analyzed to explain the possible mechanism of Genkwa Flos hepatotoxicity.

3. Based on the results, lipid peroxidation and oxidative stress, phospholipase A₂/lysophosphatidylcholine pathway, the disturbance of sphingosine-1-phosphate metabolic profile centered on sphingosine kinase/sphingosine-1-phosphate pathway and fatty acid metabolism might be critical participators in the progression of liver injury induced by Genkwa Flos.     

Combining CAPRA-S With Tumor IDC/C Features Improves the Prognostication of Biochemical Recurrence in Prostate Cancer Patients

Background: Intraductal carcinoma and cribriform (IDC/C) tumor features are well-established prognosticators of biochemical recurrence (BCR), metastasis, and prostate cancer (PCa)-specific mortality. However, approximately 70% of PCa patients undergoing a radical prostatectomy are IDC/C negative, yet up-to 20% of these patients progress and experience BCR. Thus, tumor histopathologic characteristics such as IDC/C alone are limited in their ability to predict disease progression. Conversely, several nomograms such as Cancer of the Prostate Risk Assessment-Surgery (CAPRA-S) have been developed to aid in the prognostication of BCR, but not yet widely applied in clinical settings. Materials and methods: In this study, we assessed the combined prognostic utility of IDC/C, and CAPRA-S for BCR in 3 PCa patient cohorts. Results: CAPRA-S+IDC/C improved the predictive accuracy of BCR in all 3 cohorts (P < .001). Specifically, among IDC/C negative cases, CAPRA-S improved the prognostication of BCR in low-risk (Cohort 1; P < .001, Cohort 2; P < .001, Cohort 3; P = .003), intermediate (Cohort 1; P < .001, Cohort 2; P = .006, Cohort 3; P = .03) and high-risk (Cohort 1-3; P < .001) patients. Conversely, IDC/C improved the prognostication of BCR among CAPRA-S low-risk (Cohorts 1; P < .001 and Cohort 3; P = .003) patients. Conclusion: Our results suggest the investigation of histopathological IDC/C features in CAPRA-S low-risk patients and conversely, nomogram CAPRA-S among IDC/C negative patients improves the identification of patients likely to experience BCR, which would otherwise be missed through current assessment regimens. These patients can be offered more intensive monitoring and adjuvant therapies upfront to circumvent the development of recurrent cancer or overtreatment at the time of surgery.     

Evaluation of vilazodone for the treatment of depressive and anxiety disorders

Introduction: Major Depressive Disorder (MDD) and General Anxiety Disorder (GAD) significantly contribute to the global burden of disease. Vilazodone, a combined serotonin reuptake inhibitor and 5-HT1A partial agonist, is an approved therapy for the treatment of MDD and which has been further investigated for GAD.

Areas covered: This article covers the pharmacokinetics and pharmacodynamics of vilazodone and provides an evaluation of the clinical usefulness of vilazodone for the treatment of MDD and anxiety disorders. A literature search was performed using PubMed/MEDLINE, Web of Science and the Cochrane Library.

Expert opinion: Studies have shown that vilazodone is significantly superior to placebo. However, vilazodone cannot as yet be recommended as a first-line treatment option for MDD as it is unclear whether the drug’s dual mechanism of action provides greater efficacy than prevailing treatment options. Moreover, more phase IV studies are needed to establish its efficacy and long-term safety in larger and more diverse populations. Although vilazodone may have an additional advantage for the treatment of anxiety symptoms in MDD, here also additional studies are required to confirm its efficacy over and above SSRI alternatives and other antidepressant treatments. Therefore, presently, vilazodone should be considered as a second- or third-line treatment option for MDD and GAD.