The impact of computed high b-value images on the diagnostic accuracy of DWI for prostate cancer: A receiver operating characteristics analysis.

To evaluate the performance of computed high b value diffusion-weighted images (DWI) in prostate cancer detection. 97 consecutive patients who had undergone multiparametric MRI of the prostate followed by biopsy were reviewed. Five radiologists independently scored 138 lesions on native high b-value images (b = 1200 s/mm2), apparent diffusion coefficient (ADC) maps, and computed high b-value images (contrast equivalent to b = 2000 s/mm2) to compare their diagnostic accuracy. Receiver operating characteristic (ROC) analysis and McNemar's test were performed to assess the relative performance of computed high b value DWI, native high b-value DWI and ADC maps. No significant difference existed in the area under the curve (AUC) for ROCs comparing B1200 (b = 1200 s/mm2) to computed B2000 (c-B2000) in 5 readers. In 4 of 5 readers c-B2000 had significantly increased sensitivity and/or decreased specificity compared to B1200 (McNemar's p < 0.05), at selected thresholds of interpretation. ADC maps were less accurate than B1200 or c-B2000 for 2 of 5 readers (P < 0.05). This study detected no consistent improvement in overall diagnostic accuracy using c-B2000, compared with B1200 images. Readers detected more cancer with c-B2000 images (increased sensitivity) but also more false positive findings (decreased specificity)

VORTEX: Physics-Driven Data Augmentations Using Consistency Training for Robust Accelerated MRI Reconstruction

Deep neural networks have enabled improved image quality and fast inference times for various inverse problems, including accelerated magnetic resonance imaging (MRI) reconstruction. However, such models require a large number of fully-sampled ground truth datasets, which are difficult to curate, and are sensitive to distribution drifts. In this work, we propose applying physics-driven data augmentations for consistency training that leverage our domain knowledge of the forward MRI data acquisition process and MRI physics to achieve improved label efficiency and robustness to clinically-relevant distribution drifts. Our approach, termed VORTEX, (1) demonstrates strong improvements over supervised baselines with and without data augmentation in robustness to signal-to-noise ratio change and motion corruption in data-limited regimes; (2) considerably outperforms state-of-the-art purely image-based data augmentation techniques and self-supervised reconstruction methods on both in-distribution and out-of-distribution data; and (3) enables composing heterogeneous image-based and physics-driven data augmentations. Our code is available at https://github.com/ad12/meddlr.Comment: Accepted to MIDL 202

Core handling and processing for the WAIS Divide ice-core project

On 1 December 2011 the West Antarctic Ice Sheet (WAIS) Divide ice-core project reached its final depth of 3405 m. The WAIS Divide ice core is not only the longest US ice core to date, but is also the highest-quality deep ice core, including ice from the brittle ice zone, that the US has ever recovered. The methods used at WAIS Divide to handle and log the drilled ice, the procedures used to safely retrograde the ice back to the US National Ice Core Laboratory (NICL) and the methods used to process and sample the ice at the NICL are described and discussed

Core handling and processing for the WAIS Divide ice-core project

On 1 December 2011 the West Antarctic Ice Sheet (WAIS) Divide ice-core project reached its final depth of 3405 m. The WAIS Divide ice core is not only the longest US ice core to date, but is also the highest-quality deep ice core, including ice from the brittle ice zone, that the US has ever recovered. The methods used at WAIS Divide to handle and log the drilled ice, the procedures used to safely retrograde the ice back to the US National Ice Core Laboratory (NICL) and the methods used to process and sample the ice at the NICL are described and discussed

Noise2Recon: Enabling Joint MRI Reconstruction and Denoising with Semi-Supervised and Self-Supervised Learning

Deep learning (DL) has shown promise for faster, high quality accelerated MRI reconstruction. However, supervised DL methods depend on extensive amounts of fully-sampled (labeled) data and are sensitive to out-of-distribution (OOD) shifts, particularly low signal-to-noise ratio (SNR) acquisitions. To alleviate this challenge, we propose Noise2Recon, a model-agnostic, consistency training method for joint MRI reconstruction and denoising that can use both fully-sampled (labeled) and undersampled (unlabeled) scans in semi-supervised and self-supervised settings. With limited or no labeled training data, Noise2Recon outperforms compressed sensing and deep learning baselines, including supervised networks, augmentation-based training, fine-tuned denoisers, and self-supervised methods, and matches performance of supervised models, which were trained with 14x more fully-sampled scans. Noise2Recon also outperforms all baselines, including state-of-the-art fine-tuning and augmentation techniques, among low-SNR scans and when generalizing to other OOD factors, such as changes in acceleration factors and different datasets. Augmentation extent and loss weighting hyperparameters had negligible impact on Noise2Recon compared to supervised methods, which may indicate increased training stability. Our code is available at https://github.com/ad12/meddlr

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset

Purpose: To organize a knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthritis progression. Methods: A dataset partition consisting of 3D knee MRI from 88 subjects at two timepoints with ground-truth articular (femoral, tibial, patellar) cartilage and meniscus segmentations was standardized. Challenge submissions and a majority-vote ensemble were evaluated using Dice score, average symmetric surface distance, volumetric overlap error, and coefficient of variation on a hold-out test set. Similarities in network segmentations were evaluated using pairwise Dice correlations. Articular cartilage thickness was computed per-scan and longitudinally. Correlation between thickness error and segmentation metrics was measured using Pearson's coefficient. Two empirical upper bounds for ensemble performance were computed using combinations of model outputs that consolidated true positives and true negatives. Results: Six teams (T1-T6) submitted entries for the challenge. No significant differences were observed across all segmentation metrics for all tissues (p=1.0) among the four top-performing networks (T2, T3, T4, T6). Dice correlations between network pairs were high (>0.85). Per-scan thickness errors were negligible among T1-T4 (p=0.99) and longitudinal changes showed minimal bias (<0.03mm). Low correlations (<0.41) were observed between segmentation metrics and thickness error. The majority-vote ensemble was comparable to top performing networks (p=1.0). Empirical upper bound performances were similar for both combinations (p=1.0). Conclusion: Diverse networks learned to segment the knee similarly where high segmentation accuracy did not correlate to cartilage thickness accuracy. Voting ensembles did not outperform individual networks but may help regularize individual models.Comment: Submitted to Radiology: Artificial Intelligence; Fixed typo

Electroacupuncture activates corticotrophin-releasing hormone-containing neurons in the paraventricular nucleus of the hypothalammus to alleviate edema in a rat model of inflammation

<p>Abstract</p> <p>Background</p> <p>Studies show that electroacupuncture (EA) has beneficial effects in patients with inflammatory diseases. This study investigated the mechanisms of EA anti-inflammation, using a rat model of complete Freund's adjuvant (CFA)-induced hind paw inflammation and hyperalgesia.</p> <p>Design</p> <p>Four experiments were conducted on male Sprague-Dawley rats (n = 6–7/per group). Inflammation was induced by injecting CFA into the plantar surface of one hind paw. Experiment 1 examined whether EA increases plasma adrenocorticotropic hormone (ACTH) levels. Experiments 2 and 3 studied the effects of the ACTH and corticotropin-releasing hormone (CRH) receptor antagonists, ACTH_(11–24)and astressin, on the EA anti-edema. Experiment 4 determined whether EA activates CRH neurons in the paraventricular nucleus of the hypothalammus. EA treatment, 10 Hz at 3 mA and 0.1 ms pulse width, was given twice for 20 min each, once immediately post and again 2 hr post-CFA. Plasma ACTH levels, paw thickness, and paw withdrawal latency to a noxious thermal stimulus were measured 2 h and 5 h after the CFA.</p> <p>Results</p> <p>EA significantly increased ACTH levels 5 h (2 folds) after CFA compared to sham EA control, but EA alone in naive rats and CFA alone did not induce significant increases in ACTH. ACTH_(11–24)and astressin blocked EA anti-edema but not EA anti-hyperalgesia. EA induced phosphorylation of NR1, an essential subunit of the N-methyl-D-aspartic acid (NMDA) receptor, in CRH-containing neurons of the paraventricular nucleus.</p> <p>Conclusion</p> <p>The data demonstrate that EA activates CRH neurons to significantly increase plasma ACTH levels and suppress edema through CRH and ACTH receptors in a rat model of inflammation.</p

Estimating the Population Size of Female Sex Workers in Zimbabwe: Comparison of Estimates Obtained Using Different Methods in Twenty Sites and Development of a National-Level Estimate.

BACKGROUND: National-level population size estimates (PSEs) for hidden populations are required for HIV programming and modelling. Various estimation methods are available at the site-level, but it remains unclear which are optimal and how best to obtain national-level estimates. SETTING: Zimbabwe. METHODS: Using 2015-2017 data from respondent-driven sampling (RDS) surveys among female sex workers (FSW) aged 18+ years, mappings, and program records, we calculated PSEs for each of the 20 sites across Zimbabwe, using up to 3 methods per site (service and unique object multipliers, census, and capture-recapture). We compared estimates from different methods, and calculated site medians. We estimated prevalence of sex work at each site using census data available on the number of 15-49-year-old women, generated a list of all "hotspot" sites for sex work nationally, and matched sites into strata in which the prevalence of sex work from sites with PSEs was applied to those without. Directly and indirectly estimated PSEs for all hotspot sites were summed to provide a national-level PSE, incorporating an adjustment accounting for sex work outside hotspots. RESULTS: Median site PSEs ranged from 12,863 in Harare to 247 in a rural growth-point. Multiplier methods produced the highest PSEs. We identified 55 hotspots estimated to include 95% of all FSW. FSW nationally were estimated to number 40,491, 1.23% of women aged 15-49 years, (plausibility bounds 28,177-58,797, 0.86-1.79%, those under 18 considered sexually exploited minors). CONCLUSION: There are large numbers of FSW estimated in Zimbabwe. Uncertainty in population size estimation should be reflected in policy-making

New insights on the Draco dwarf spheroidal galaxy from SDSS: a larger radius and no tidal tails

We have investigated the spatial extent and structure of the Draco dwarf spheroidal galaxy using deep wide-field multicolor CCD photometry from the Sloan Digital Sky Survey (SDSS). Our study covers an area of 27 square degrees around the center of the Draco dwarf. We show that the spatial distribution of Draco's red giants, red horizontal branch stars and subgiants down to i=21.7 mag does not provide evidence for the existence of tidally induced tails or a halo of unbound stars. The radial profile can be fit by King models as well as by a generalized exponential. The core radius and the limiting (or tidal) radius along the major axis are 7.7' and 40.1', respectively, making Draco 40% larger than previously measured. Down to our magnitude limit tidal effects can only exist at a level of 10^-3 of the central surface density of Draco or below. The regular structure of Draco found from the new data argues against it being a portion of an unbound tidal stream and lends support to the assumption of dynamical equilibrium. We estimate Draco's total mass to be 2.2 - 3.5 times 10^7 solar masses. We obtain an overall mass-to-light ratio of 146+-42 or 92+-28 solar masses depending on the details of the mass and luminosity estimates. In summary, our results strengthen the case for a strongly dark matter dominated, bound stellar system. (Abstract strongly abridged).Comment: 30 pages, 11 figures (in part with degraded resolution). Accepted for publication in the Astronomical Journa