A Novel Unsupervised Segmentation Approach Quantifies Tumor Tissue Populations Using Multiparametric MRI: First Results with Histological Validation

PURPOSE: We aimed to precisely estimate intra-tumoral heterogeneity using spatially regularized spectral clustering (SRSC) on multiparametric MRI data and compare the efficacy of SRSC with the previously reported segmentation techniques in MRI studies. PROCEDURES: Six NMRI nu/nu mice bearing subcutaneous human glioblastoma U87 MG tumors were scanned using a dedicated small animal 7T magnetic resonance imaging (MRI) scanner. The data consisted of T2 weighted images, apparent diffusion coefficient maps, and pre- and post-contrast T2 and T2* maps. Following each scan, the tumors were excised into 2–3-mm thin slices parallel to the axial field of view and processed for histological staining. The MRI data were segmented using SRSC, K-means, fuzzy C-means, and Gaussian mixture modeling to estimate the fractional population of necrotic, peri-necrotic, and viable regions and validated with the fractional population obtained from histology. RESULTS: While the aforementioned methods overestimated peri-necrotic and underestimated viable fractions, SRSC accurately predicted the fractional population of all three tumor tissue types and exhibited strong correlations (r(necrotic) = 0.92, r(peri-necrotic) = 0.82 and r(viable) = 0.98) with the histology. CONCLUSIONS: The precise identification of necrotic, peri-necrotic and viable areas using SRSC may greatly assist in cancer treatment planning and add a new dimension to MRI-guided tumor biopsy procedures. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11307-016-1009-y) contains supplementary material, which is available to authorized users

ClinVAP: a reporting strategy from variants to therapeutic options

Motivation Next-generation sequencing has become routine in oncology and opens up new avenues of therapies, particularly in personalized oncology setting. An increasing number of cases also implies a need for a more robust, automated and reproducible processing of long lists of variants for cancer diagnosis and therapy. While solutions for the large-scale analysis of somatic variants have been implemented, existing solutions often have issues with reproducibility, scalability and interoperability. Results Clinical Variant Annotation Pipeline (ClinVAP) is an automated pipeline which annotates, filters and prioritizes somatic single nucleotide variants provided in variant call format. It augments the variant information with documented or predicted clinical effect. These annotated variants are prioritized based on driver gene status and druggability. ClinVAP is available as a fully containerized, self-contained pipeline maximizing reproducibility and scalability allowing the analysis of larger scale data. The resulting JSON-based report is suited for automated downstream processing, but ClinVAP can also automatically render the information into a user-defined template to yield a human-readable report.ISSN:1367-4803ISSN:1460-205

Community forestry frameworks in sub-Saharan Africa and the impact on sustainable development

Community based forest management (CBFM) has been implemented in Africa since the 1980s. Three main objectives, which are currently part of the sustainable development goals (SDGs), underlie the formation of CBFM. They are (1) enhancing community engagement in forest management, (2) reducing rural poverty, and (3) promoting forest resources conservation. We examine CBFM frameworks in sub-Saharan Africa (SSA) and CBFM schemes' contribution to selected sustainable development goals relevant to the forestry sector. Five SSA countries, Ethiopia, Kenya, Cameroon, Uganda, and Tanzania were chosen for the study because of their long-term engagement in CBFM. The analysis was based on desk review of literature from Web of Science, Scopus, and Google Scholar, and interviews with individuals representing institutions leading CBFM implementation in the countries selected. We found countries were strong in devising policy and legal provisions and articulating formalities for establishing CBFM. Major weaknesses were observed in monitoring CBFM performance, benefit sharing, and product management. The analysis of CBFM schemes' contribution to SDGs was largely positive, though with several cases of no considerable impact and few reports of negative impacts. The contributions of CBFM schemes to SDGs was constrained by weaknesses in the CBFM frameworks. Enhancing CBFM schemes contribution to SDGs requires addressing the major weaknesses observed in the CBFM frameworks

Advanced Monitoring Is Associated with Fewer Alarm Events During Planned Moderate Procedure-Related Sedation

BackgroundDiagnostic and interventional procedures are often facilitated by moderate procedure-related sedation. Many studies support the overall safety of this sedation; however, adverse cardiovascular and respiratory events are reported in up to 70% of these procedures, more frequently in very young, very old, or sicker patients. Monitoring with pulse oximetry may underreport hypoventilation during sedation, particularly if supplemental oxygen is provided. Capnometry may result in false alarms during sedation when patients mouth breathe or displace sampling devices. Advanced monitor use during sedation may allow event detection before complications develop. This 2-part pilot study used advanced monitors during planned moderate sedation to (1) determine incidences of desaturation, low respiratory rate, and deeper than intended sedation alarm events; and (2) determine whether advanced monitor use is associated with fewer alarm events.MethodsAdult patients undergoing scheduled gastroenterology or interventional radiology procedures with planned moderate sedation given by dedicated sedation nurses under the direction of procedural physicians (procedural sedation team) were monitored per standard protocols (electrocardiography blood pressure, pulse oximetry, and capnometry) and advanced monitors (acoustic respiratory monitoring and processed electroencephalograpy). Data were collected to computers for analysis. Advanced monitor parameters were not visible to teams in part 1 (standard) but were visible to teams in part 2 (advanced). Alarm events were defined as desaturation-SpO2 ≤92%; respiratory depression, acoustic respiratory rate ≤8 breaths per minute, and deeper than intended sedation, indicated by processed electroencephalograpy. The number of alarm events was compared.ResultsOf 100 patients enrolled, 10 were excluded for data collection computer malfunction or consent withdrawal. Data were analyzed from 90 patients (44 standard and 46 advanced). Advanced had fewer total alarms than standard (Wilcoxon-Mann-Whitney = 2.073, P = 0.038; Wilcoxon-Mann-Whitney odds, 1.67; 95% confidence interval [CI], 1.04-2.88). Similar numbers of standard and advanced had ≥1 alarm event (Wald difference, -10.2%; 95% CI, -26.4% to 7.0%; P = 0.237). Fewer advanced patients had ≥1 respiratory depression event (Wald difference, -22.1%; 95% CI, -40.9% to -2.4%; P = 0.036) or ≥1 desaturation event (Wald difference, -24.2%; 95% CI, -42.8% to -3.6%; P = 0.021); but there was no significant difference in deeper than intended sedation events (Wald difference, -1.38%; 95% CI, -20.21% to 17.49%; P = 0.887).ConclusionsUse of advanced monitoring parameters during planned moderate sedation was associated with fewer alarm events, patients experiencing desaturation, and patients experiencing respiratory depression alarm events. This pilot study suggests that further study into the safety and outcome impacts of advanced monitoring during procedure-related sedation is warranted

Assessment of network module identification across complex diseases

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