Web-based tool for cancer family history collection: A prospective randomized controlled trial.

OBJECTIVES: Approximately 1% of individuals have a hereditary cancer predisposition syndrome, however, the majority are not aware. Collecting a cancer family history (CFH) can triage patients to receive genetic testing. To rigorously assess different methods of CFH collection, we compared a web-based tool (WBT) to usual care (clinician collects CFH) in a randomized controlled trial. METHODS: New gynecologic oncology patients (seen 9/2019-9/2021) were randomized to one of three arms in a 2:2:1 allocation ratio: 1) usual care clinician CFH collection, 2) WBT completed at home, or 3) WBT completed in office. The WBT generated a cancer-focused pedigree and scores on eight validated cancer risk models. The primary outcome was collection of an adequate CFH (based on established guidelines) with usual care versus the WBT. RESULTS: We enrolled 250 participants (usual care - 110; WBT home - 105; WBT office - 35 [closed early due to COVID-19]). Within WBT arms, 109 (78%) participants completed the tool, with higher completion for office versus home (33 [94%] vs. 76 [72%], P = 0.008). Among participants completing the WBT, 63 (58%) had an adequate CFH versus 5 (5%) for usual care (P < 0.001). Participants completing the WBT were significantly more likely to complete genetic counseling (34 [31%] vs. 15 [14%], P = 0.002) and genetic testing (20 [18%] vs. 9 [8%], P = 0.029). Participant and provider WBT experience was favorable. CONCLUSIONS: WBTs for CFH collection are a promising application of health information technology, resulting in more comprehensive CFH and a significantly greater percentage of participants completing genetic counseling and testing.

Barriers to completion of cascade genetic testing: how can we improve the uptake of testing for hereditary breast and ovarian cancer syndrome?

Cascade testing for familial cancer syndromes has historically been difficult to execute. As part of a facilitated cascade testing pathway, we evaluated barriers to completion of cascade testing. Our previously published study evaluated a facilitated cascade testing pathway whereby a genetics team facilitated at-risk relative (ARR) cascade testing through telephone genetic counseling and mailed saliva kit testing. This follow-up study evaluated barriers to completion of cascade genetic testing through six-month follow-up telephone interviews. Probands identified 114 ARRs, of whom 97 were successfully contacted by telephone. Among those contacted, 83 (86%) reported interest in genetic testing and 14 (14%) declined. Among those reporting interest in testing, 71% (69/83) completed testing. Follow-up telephone interviews revealed that 14 ARRs did not complete testing despite reporting interest for the following reasons: concern about genetic discrimination, fear of a positive result and belief that the pathogenic variant was not relevant to his/her health. Five ARRs reported that they remained interested in testing and the telephone call prompted completion of testing. Even when facilitated by a medical team with prioritization of relative convenience, significant barriers to cascade testing ARRs for hereditary breast and ovarian cancer syndrome persist due to concern about genetic discrimination, cost, and fear of positive test results.

Room for improvement in capturing cancer family history in a gynecologic oncology outpatient setting.

The literature demonstrates that the quality of cancer family history (CFH) as currently collected in the outpatient setting is inadequate to assess disease risk. Prior to implementation of a web-based application for cancer family history collection, we aimed to review the quality of collected CFH in a gynecologic oncology outpatient clinic and determine contributing patient factors. Medical records were reviewed for 200 new patients presenting between 4/2019-7/2019. CFH was collected during the patient interview and evaluated for inclusion of eight elements based on standards set by the genetics community. Univariate and multivariable linear regression analyses were utilized to evaluate the effect of patient characteristics on the number of relatives included in the CFH. Among our cohort of 200 patients, CFH was documented for 185 patients (92.5%). On univariate analysis, patients with a family history of cancer and prior genetic testing had significantly greater median number of relatives included in the CFH. On multivariable analysis, patients with family members with cancer had significantly more relatives included. Our data are consistent with the literature, suggesting that the current collection methods may not adequately capture all measures of a high quality CFH. Patients reporting no family history of cancer and those without prior genetic testing were least likely to have CFH that included key quality elements and these patients might benefit from health information technology CFH collection tools.

Leveraging Health Information Technology to Collect Family Cancer History: A Systematic Review and Meta-Analysis.

PURPOSE: Collection of family cancer histories (FCHs) can identify individuals at risk for familial cancer syndromes. The aim of this study is to evaluate the literature on existing strategies whereby providers use information technology to assemble FCH. METHODS: A systematic search of online databases (Ovid MEDLINE, Cochrane, and Embase) between 1980 and 2020 was performed. Statistical heterogeneity was assessed through the chi-square test (ie, Cochrane Q test) and the inconsistency statistic (I2). A random-effects analysis was used to calculate the pooled proportions and means. RESULTS: The comprehensive search produced 4,005 publications. Twenty-eight studies met inclusion criteria. Twenty-seven information technology tools were evaluated. Eighteen out of 28 studies were electronic surveys administered before visits (18, 64.3%). Five studies administered tablet surveys in offices (5, 17.8%). Four studies collected electronic survey via kiosk before visits (4, 14.3%), and one study used animated virtual counselor during visits (1, 3.6%). Among the studies that use an FCH tool, the pooled estimate of the overall completion rate was 86% (CI, 72% to 96%), 84% (CI, 65% to 97%) for electronic surveys before visits, 89% (CI, 0.74 to 0.98) for tablet surveys, and 85% (CI, 0.66 to 0.98) for surveys via kiosk. Mean time required for completion was 31.0 minutes (CI, 26.1 to 35.9), and the pooled estimate of proportions of participants referred to genetic testing was 12% (CI, 4% to 23%). CONCLUSION: Our review found that electronic FCH collection can be completed successfully by patients in a time-efficient manner with high rates of satisfaction.

Depth-dependent intracortical myelin organization in the living human brain determined by in vivo ultra-high field magnetic resonance imaging.

BACKGROUND: Intracortical myelin is a key determinant of neuronal synchrony and plasticity that underpin optimal brain function. Magnetic resonance imaging (MRI) facilitates the examination of intracortical myelin but presents with methodological challenges. Here we describe a whole-brain approach for the in vivo investigation of intracortical myelin in the human brain using ultra-high field MRI. METHODS: Twenty-five healthy adults were imaged in a 7 Tesla MRI scanner using diffusion-weighted imaging and a T1-weighted sequence optimized for intracortical myelin contrast. Using an automated pipeline, T1 values were extracted at 20 depth-levels from each of 148 cortical regions. In each cortical region, T1 values were used to infer myelin concentration and to construct a non-linearity index as a measure the spatial distribution of myelin across the cortical ribbon. The relationship of myelin concentration and the non-linearity index with other neuroanatomical properties were investigated. Five patients with multiple sclerosis were also assessed using the same protocol as positive controls. RESULTS: Intracortical T1 values decreased between the outer brain surface and the gray-white matter boundary following a slope that showed a slight leveling between 50% and 75% of cortical depth. Higher-order regions in the prefrontal, cingulate and insular cortices, displayed higher non-linearity indices than sensorimotor regions. Across all regions, there was a positive association between T1 values and non-linearity indices (P < 10-5). Both T1 values (P < 10-5) and non-linearity indices (P < 10-15) were associated with cortical thickness. Higher myelin concentration but only in the deepest cortical levels was associated with increased subcortical fractional anisotropy (P = 0.05). CONCLUSIONS: We demonstrate the usefulness of an automatic, whole-brain method to perform depth-dependent examination of intracortical myelin organization. The extracted metrics, T1 values and the non-linearity index, have characteristic patterns across cortical regions, and are associated with thickness and underlying white matter microstructure.

Multivariate Associations Among Behavioral, Clinical, and Multimodal Imaging Phenotypes in Patients With Psychosis.

Importance: Alterations in multiple neuroimaging phenotypes have been reported in psychotic disorders. However, neuroimaging measures can be influenced by factors that are not directly related to psychosis and may confound the interpretation of case-control differences. Therefore, a detailed characterization of the contribution of these factors to neuroimaging phenotypes in psychosis is warranted. Objective: To quantify the association between neuroimaging measures and behavioral, health, and demographic variables in psychosis using an integrated multivariate approach. Design, Setting, and Participants: This imaging study was conducted at a university research hospital from June 26, 2014, to March 9, 2017. High-resolution multimodal magnetic resonance imaging data were obtained from 100 patients with schizophrenia, 40 patients with bipolar disorder, and 50 healthy volunteers; computed were cortical thickness, subcortical volumes, white matter fractional anisotropy, task-related brain activation (during working memory and emotional recognition), and resting-state functional connectivity. Ascertained in all participants were nonimaging measures pertaining to clinical features, cognition, substance use, psychological trauma, physical activity, and body mass index. The association between imaging and nonimaging measures was modeled using sparse canonical correlation analysis with robust reliability testing. Main Outcomes and Measures: Multivariate patterns of the association between nonimaging and neuroimaging measures in patients with psychosis and healthy volunteers. Results: The analyses were performed in 92 patients with schizophrenia (23 female [25.0%]; mean [SD] age, 27.0 [7.6] years), 37 patients with bipolar disorder (12 female [32.4%]; mean [SD] age, 27.5 [8.1] years), and 48 healthy volunteers (20 female [41.7%]; mean [SD] age, 29.8 [8.5] years). The imaging and nonimaging data sets showed significant covariation (r = 0.63, P < .001), which was independent of diagnosis. Among the nonimaging variables examined, age (r = -0.53), IQ (r = 0.36), and body mass index (r = -0.25) were associated with multiple imaging phenotypes; cannabis use (r = 0.23) and other substance use (r = 0.33) were associated with subcortical volumes, and alcohol use was associated with white matter integrity (r = -0.15). Within the multivariate models, positive symptoms retained associations with the global neuroimaging (r = -0.13), the cortical thickness (r = -0.22), and the task-related activation variates (r = -0.18); negative symptoms were mostly associated with measures of subcortical volume (r = 0.23), and depression/anxiety was associated with measures of white matter integrity (r = 0.12). Conclusions and Relevance: Multivariate analyses provide a more accurate characterization of the association between brain alterations and psychosis because they enable the modeling of other key factors that influence neuroimaging phenotypes.

Reproducibility of myelin content-based human habenula segmentation at 3 Tesla.

In vivo morphological study of the human habenula, a pair of small epithalamic nuclei adjacent to the dorsomedial thalamus, has recently gained significant interest for its role in reward and aversion processing. However, segmenting the habenula from in vivo magnetic resonance imaging (MRI) is challenging due to the habenula's small size and low anatomical contrast. Although manual and semi-automated habenula segmentation methods have been reported, the test-retest reproducibility of the segmented habenula volume and the consistency of the boundaries of habenula segmentation have not been investigated. In this study, we evaluated the intra- and inter-site reproducibility of in vivo human habenula segmentation from 3T MRI (0.7-0.8 mm isotropic resolution) using our previously proposed semi-automated myelin contrast-based method and its fully-automated version, as well as a previously published manual geometry-based method. The habenula segmentation using our semi-automated method showed consistent boundary definition (high Dice coefficient, low mean distance, and moderate Hausdorff distance) and reproducible volume measurement (low coefficient of variation). Furthermore, the habenula boundary in our semi-automated segmentation from 3T MRI agreed well with that in the manual segmentation from 7T MRI (0.5 mm isotropic resolution) of the same subjects. Overall, our proposed semi-automated habenula segmentation showed reliable and reproducible habenula localization, while its fully-automated version offers an efficient way for large sample analysis.