Morphological imaging and CT histogram analysis to differentiate pancreatic neuroendocrine tumor grade 3 from neuroendocrine carcinoma

PurposeTo compare morphological imaging features and CT texture histogram parameters between grade 3 pancreatic neuroendocrine tumors (G3-NET) and neuroendocrine carcinomas (NEC).Materials and methodsPatients with pathologically proven G3-NET and NEC, according to the 2017 World Health Organization classification who had CT and MRI examinations between 2006-2017 were retrospectively included. CT and MRI examinations were reviewed by two radiologists in consensus and analyzed with respect to tumor size, enhancement patterns, hemorrhagic content, liver metastases and lymphadenopathies. Texture histogram analysis of tumors was performed on arterial and portal phase CT images. images. Morphological imaging features and CT texture histogram parameters of G3-NETs and NECs were compared.ResultsThirty-seven patients (21 men, 16 women; mean age, 56 ± 13 [SD] years [range: 28-82 years]) with 37 tumors (mean diameter, 60 ± 46 [SD] mm) were included (CT available for all, MRI for 16/37, 43%). Twenty-three patients (23/37; 62%) had NEC and 14 patients (14/37; 38%) had G3-NET. NECs were larger than G3-NETs (mean, 70 ± 51 [SD] mm [range: 18 - 196 mm] vs. 42 ± 24 [SD] mm [range: 8 - 94 mm], respectively; P = 0.039), with more tumor necrosis (75% vs. 33%, respectively; P = 0.030) and lower attenuation on precontrast (30 ± 4 [SD] HU [range: 25-39 HU] vs. 37 ± 6 [SD] [range: 25-45 HU], respectively; P = 0.002) and on portal venous phase CT images (75 ± 18 [SD] HU [range: 43 - 108 HU] vs. 92 ± 19 [SD] HU [range: 46 - 117 HU], respectively; P = 0.014). Hemorrhagic content on MRI was only observed in NEC (P = 0.007). The mean ADC value was lower in NEC ([1.1 ± 0.1 (SD)] × 10⁻³ mm²/s [range: (0.91 - 1.3) × 10⁻³ mm²/s] vs. [1.4 ± 0.2 (SD)] × 10⁻³ mm²/s [range: (1.1 - 1.6) × 10⁻³ mm²/s]; P = 0.005). CT histogram analysis showed that NEC were more heterogeneous on portal venous phase images (Entropy-0: 4.7 ± 0.2 [SD] [range: 4.2-5.1] vs. 4.5 ± 0.4 [SD] [range: 3.7-4.9]; P = 0.023).ConclusionPancreatic NECs are larger, more frequently hypoattenuating and more heterogeneous with hemorrhagic content than G3-NET on CT and MRI.     

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%.     

Pediatric cardiac computed tomography angiography: Expert consensus from the Filiale de Cardiologie Pédiatrique et Congénitale (FCPC) and the Société Française d’Imagerie Cardiaque et Vasculaire diagnostique et interventionnelle (SFICV)

This article was designed to provide a pediatric cardiac computed tomography angiography (CCTA) expert panel consensus based on opinions of experts of the Société Française d’Imagerie Cardiaque et Vasculaire diagnostique et interventionnelle (SFICV) and of the Filiale de Cardiologie Pédiatrique Congénitale (FCPC). This expert panel consensus includes recommendations for indications, patient preparation, CTA radiation dose reduction techniques, and post-processing techniques. The consensus was based on data from available literature (original papers, reviews and guidelines) and on opinions of a group of specialists with extensive experience in the use of CT imaging in congenital heart disease. In order to reach high potential and avoid pitfalls, CCTA in children with congenital heart disease requires training and experience. Moreover, pediatric cardiac CCTA protocols should be standardized to acquire optimal images in this population with the lowest radiation dose possible to prevent unnecessary radiation exposure. We also provided a suggested structured report and a list of acquisition protocols and technical parameters in relation to specific vendors.     

Neural mechanisms regulating different forms of risk-related decision-making: Insights from animal models

Over the past 20 years there has been a growing interest in the neural underpinnings of cost/benefit decision-making. Recent studies with animal models have made considerable advances in our understanding of how different prefrontal, striatal, limbic and monoaminergic circuits interact to promote efficient risk/reward decision-making, and how dysfunction in these circuits underlies aberrant decision-making observed in numerous psychiatric disorders. This review will highlight recent findings from studies exploring these questions using a variety of behavioral assays, as well as molecular, pharmacological, neurophysiological, and translational approaches. We begin with a discussion of how neural systems related to decision subcomponents may interact to generate more complex decisions involving risk and uncertainty. This is followed by an overview of interactions between prefrontal-amygdala-dopamine and habenular circuits in regulating choice between certain and uncertain rewards and how different modes of dopamine transmission may contribute to these processes. These data will be compared with results from other studies investigating the contribution of some of these systems to guiding decision-making related to rewards vs. punishment. Lastly, we provide a brief summary of impairments in risk-related decision-making associated with psychiatric disorders, highlighting recent translational studies in laboratory animals.     

Psychometric properties of the Repetitive Behavior Scale-Revised for individuals with autism spectrum disorder in Japan

Restricted and repetitive behaviors (RRBs) constitute a core symptom of autism spectrum disorder (ASD). The Repetitive Behavior Scale-Revised (RBS-R) is a widely used questionnaire administered by parents or caregivers to assess RRBs in individuals with ASD. This study evaluated the psychometric properties of the RBS-R Japanese Version (RBS-R-J). The ASD and non-ASD groups comprised 274 and 36 participants, respectively. We examined corrected item-total correlation, Cronbach's alpha, and RBS-R-J scores of different diagnostic groups, as well as correlations between RBS-R-J scores and intelligence quotient (IQ), autistic symptoms, adaptive/maladaptive functioning, aberrant behaviors, and sensory processing. All items showed moderate corrected item-total correlations. Cronbach's alpha coefficient was .93. We found significant differences in the mean RBS-R-J scores of the low-functioning ASD group and the intellectual disabilities group, and of low-functioning and high-functioning ASD groups. RBS-R-J scores negatively correlated with IQ and scores on the Sensory Profile (Japanese version) and Adaptive Behavior Composite of the Maladaptive Behavior Index of the Vineland Adaptive Behavior Scales-Second Edition (VABS-II; Japanese version), but positively correlated with scores on the peak and current symptoms subscales of the Pervasive Developmental Disorders Autism Society Japan Rating Scale, the VABS-II, and the Aberrant Behavior Checklist-Community (Japanese version). From these results, we conclude that RBS-R-J showed good reliability, diagnostic validity, and convergent validity, indicating that it is a reliable, valid instrument for use among ASD individuals in clinical and research settings.     

Racial matching and adolescent self-disclosure of substance use and mental health symptoms

Obtaining accurate assessment data from adolescents in treatment aids clinical decision making and facilitates more accurate outcome evaluations. However, findings could be biased due to underreported substance use and mental health symptoms. This article compares self-reports of youth in non-White matched client–assessor dyads and those in nonmatched dyads. There were no differences on self-reported substance use, but matched youth reported significantly fewer attention deficit/hyperactivity disorder symptoms versus the comparison group. One possible reason for these findings is the effect of in-group stereotype threat. Future studies should examine the potential effect that in-group stereotyping and perceived racism have on the therapeutic relationship.