Static and dynamic predictors of forensic mental health decision-making.

In Canada, individuals found not criminally responsible on account of mental disorder (NCR) fall under the supervision of a jurisdictional review board (RB) per the Criminal Code. Limited research has examined whether RB decisions balance the needs of public safety with social reintegration as intended by federal legislation. To fill this gap, the present study determined whether forensic decisional outcomes in one provincial RB system accounted for information relevant to violence risk. Study instruments included the Level of Service/Case Management Inventory (LS/CMI), Historical Clinical Risk Management-20 Version 3, and the Revised Violence Risk Appraisal Guide. A retrospective longitudinal design was employed to examine an NCR cohort (N = 109) that entered the RB system between 2005 and 2010 and their respective RB hearings (N = 327) until 2015. Results indicated that risk-relevant information was supplied to the RB by forensic professionals; however, key criminogenic risk and need factors as defined by the LS/CMI were absent in clinical reports. RB decisions were still strongly predicted by empirically supported risk factors linked to violent recidivism. Higher release likelihoods corresponded to a proportionally greater reliance on dynamic risk factors to enact dispositions. Forensic risk instruments are central aspects of correctional rehabilitation, and the results demonstrated their relevance to forensic tribunals. It is recommended that information from a forensic risk instrument be routinely delivered to RBs to support evidence-based decision-making. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Augmented deep learning model for improved quantitative accuracy of MR-based PET attenuation correction in PSMA PET-MRI prostate imaging.

PURPOSE: Estimation of accurate attenuation maps for whole-body positron emission tomography (PET) imaging in simultaneous PET-MRI systems is a challenging problem as it affects the quantitative nature of the modality. In this study, we aimed to improve the accuracy of estimated attenuation maps from MRI Dixon contrast images by training an augmented generative adversarial network (GANs) in a supervised manner. We augmented the GANs by perturbing the non-linear deformation field during image registration between MRI and the ground truth CT images. METHODS: We acquired the CT and the corresponding PET-MR images for a cohort of 28 prostate cancer patients. Data from 18 patients (2160 slices and later augmented to 270,000 slices) was used for training the GANs and others for validation. We calculated the error in bone and soft tissue regions for the AC µ-maps and the reconstructed PET images. RESULTS: For quantitative analysis, we use the average relative absolute errors and validate the proposed technique on 10 patients. The DL-based MR methods generated the pseudo-CT AC µ-maps with an accuracy of 4.5% more than standard MR-based techniques. Particularly, the proposed method demonstrates improved accuracy in the pelvic regions without affecting the uptake values. The lowest error of the AC µ-map in the pelvic region was 1.9% for µ-mapGAN + aug compared with 6.4% for µ-mapdixon, 5.9% for µ-mapdixon + bone, 2.1% for µ-mapU-Net and 2.0% for µ-mapU-Net + aug. For the reconstructed PET images, the lowest error was 2.2% for PETGAN + aug compared with 10.3% for PETdixon, 8.7% for PETdixon + bone, 2.6% for PETU-Net and 2.4% for PETU-Net + aug.. CONCLUSION: The proposed technique to augment the training datasets for training of the GAN results in improved accuracy of the estimated µ-map and consequently the PET quantification compared to the state of the art.

High-throughput multiplexed autoantibody detection to screen type 1 diabetes and multiple autoimmune diseases simultaneously.

BACKGROUND: Islet autoantibodies (IAbs) are the most reliable biomarkers to assess risk of progression to clinical type 1 diabetes (T1D). There are four major biochemically defined IAbs currently used in clinical trials that are equally important for disease prediction. The current screening methods use a radio-binding assay (RBA) for single IAb measurement, which are laborious and inefficient for large-scale screening. More importantly, up to 40% of patients with T1D have other autoimmune conditions that can be identified through relevant autoantibody testing. Thus, there is a need to screen for T1D and other autoimmune diseases simultaneously. METHODS: Based on our well-established electrochemiluminescence (ECL) assay platform, we developed a multiplexed ECL assay that combines 7 individual autoantibody assays together in one single well to simultaneously screen T1D, and three other autoimmune diseases including celiac disease, autoimmune thyroid disease and autoimmune poly-glandular syndrome-1 (APS-1). The 7-Plex ECL assay was extensively validated against single antibody measurements including a standard RBA and single ECL assay. FINDINGS: The 7-Plex ECL assay was well correlated to each single ECL autoantibody assay and each RBA. INTERPRETATION: The multiplexed ECL assay provides high sensitivity and disease specificity, along with high throughput and a low cost for large-scale screenings of T1D and other relevant autoimmune diseases in the general population. FUND: JDRF grants 2-SRA-2015-51-Q-R, 2-SRA-2018-533-S-B, NIH grants DK32083 and DK32493. NSFC grants 81770777.

Bridging Neuropsychology and Forensic Psychology: Executive Function Overlaps With the Central Eight Risk and Need Factors.

Recent research expanded theoretical frameworks of criminality to include biosocial perspectives. This article advances the biosocial integration into traditional criminological theories by focusing on the potential contribution of executive function (EF) to Andrews and Bonta's risk-need-responsivity (RNR) model. EF encompasses a collection of abilities critical to adaptive human functioning, many of which seem to underlie criminogenic risk and need factors. Although the assessment of EF can be elusive, research suggests that offenders with antisocial personality disorder (ASPD) experience EF deficits. Theoretical analysis on neuropsychological and forensic concepts suggests that unitary and discrete EF domains underlie the "Central Eight" criminogenic factors that are related to criminal behavior and, by extension, the RNR model of forensic assessment and treatment. Research and conceptual limitations of the current neuropsychological and forensic literature are discussed along with the limits of our theoretical analysis. A call for more theoretical and applied forensic neuropsychological research is presented.

Predictors of Historical Clinical Risk Management-20 Version 3 (HCR-20:V3) summary risk ratings.

How individual risk factors on structured professional judgement (SPJ) assessment tools translate into SPJ final risk formulations is unclear due to a lack of structured criteria. Understanding pathways to risk formulations is vital, as they serve as intervention targets for risk management. This study examined how Historical Clinical Risk Management-20 Version 3 (HCR-20:V3) raters weighed varied information sources to complete summary risk ratings (SRRs). Four independent raters retrospectively coded an archived sample of 32 inpatients at a Canadian forensic psychiatric hospital. HCR-20:V3 SPJ SRRs were regressed on the 20 individual items and sample covariates to identify unique predictors of risk formulations across each rater. Raters consistently used HCR-20:V3 items and composite subscales for SRRs. Despite strong inter-rater agreement on the SRRs, there were variations across raters regarding which items informed each SRR. Rater-unique biases were also shown to influence SRRs. Implications for forensic practice and risk management are discussed.