Intraoperative Organ Motion Models with an Ensemble of Conditional Generative Adversarial Networks

In this paper, we describe how a patient-specific, ultrasound-probe-induced prostate motion model can be directly generated from a single preoperative MR image. Our motion model allows for sampling from the conditional distribution of dense displacement fields, is encoded by a generative neural network conditioned on a medical image, and accepts random noise as additional input. The generative network is trained by a minimax optimisation with a second discriminative neural network, tasked to distinguish generated samples from training motion data. In this work, we propose that 1) jointly optimising a third conditioning neural network that pre-processes the input image, can effectively extract patient-specific features for conditioning; and 2) combining multiple generative models trained separately with heuristically pre-disjointed training data sets can adequately mitigate the problem of mode collapse. Trained with diagnostic T2-weighted MR images from 143 real patients and 73,216 3D dense displacement fields from finite element simulations of intraoperative prostate motion due to transrectal ultrasound probe pressure, the proposed models produced physically-plausible patient-specific motion of prostate glands. The ability to capture biomechanically simulated motion was evaluated using two errors representing generalisability and specificity of the model. The median values, calculated from a 10-fold cross-validation, were 2.8+/-0.3 mm and 1.7+/-0.1 mm, respectively. We conclude that the introduced approach demonstrates the feasibility of applying state-of-the-art machine learning algorithms to generate organ motion models from patient images, and shows significant promise for future research.Comment: Accepted to MICCAI 201

Adversarial Deformation Regularization for Training Image Registration Neural Networks

We describe an adversarial learning approach to constrain convolutional neural network training for image registration, replacing heuristic smoothness measures of displacement fields often used in these tasks. Using minimally-invasive prostate cancer intervention as an example application, we demonstrate the feasibility of utilizing biomechanical simulations to regularize a weakly-supervised anatomical-label-driven registration network for aligning pre-procedural magnetic resonance (MR) and 3D intra-procedural transrectal ultrasound (TRUS) images. A discriminator network is optimized to distinguish the registration-predicted displacement fields from the motion data simulated by finite element analysis. During training, the registration network simultaneously aims to maximize similarity between anatomical labels that drives image alignment and to minimize an adversarial generator loss that measures divergence between the predicted- and simulated deformation. The end-to-end trained network enables efficient and fully-automated registration that only requires an MR and TRUS image pair as input, without anatomical labels or simulated data during inference. 108 pairs of labelled MR and TRUS images from 76 prostate cancer patients and 71,500 nonlinear finite-element simulations from 143 different patients were used for this study. We show that, with only gland segmentation as training labels, the proposed method can help predict physically plausible deformation without any other smoothness penalty. Based on cross-validation experiments using 834 pairs of independent validation landmarks, the proposed adversarial-regularized registration achieved a target registration error of 6.3 mm that is significantly lower than those from several other regularization methods.Comment: Accepted to MICCAI 201

Molecular markers reveal reproductive strategies of non‐pollinating fig wasps

1. Fig wasps have proved extremely useful study organisms for testing how reproductive decisions evolve in response to population structure. In particular, they provide textbook examples of how natural selection can favour female‐biased offspring sex ratios, lethal combat for mates and dimorphic mating strategies. 2. However, previous work has been challenged, because supposedly single species have been discovered to be a number of cryptic species. Consequently, new studies are required to determine population structure and reproductive decisions of individuals unambiguously assigned to species. 3. Microsatellites were used to determine species identity and reproductive patterns in three non‐pollinating Sycoscapter species associated with the same fig species. Foundress number was typically one to five and most figs contained more than one Sycoscapter species. Foundresses produced very small clutches of about one to four offspring, but one foundress may lay eggs in several figs. 4. Overall, the data were a poor match to theoretical predictions of solitary male clutches and gregarious clutches with n − 1 females. However, sex ratios were male‐biased in solitary clutches and female‐biased in gregarious ones. 5. At the brood level (all wasps in a fig), a decrease in sex ratio with increasing brood size was only significant in one species, and sex ratio was unrelated to foundress number. In addition, figs with more foundresses contain more wasp offspring. 6. Finally, 10–22% of females developed in patches without males. As males are wingless, these females disperse unmated and are constrained to produce only sons from unfertilised eggs

Multiparametric MR imaging for detection of clinically significant prostate cancer: a validation cohort study with transperineal template prostate mapping as the reference standard.

PURPOSE: To evaluate the diagnostic performance of multiparametric (MP) magnetic resonance (MR) imaging for prostate cancer detection by using transperineal template prostate mapping (TTPM) biopsies as the reference standard and to determine the potential ability of MP MR imaging to identify clinically significant prostate cancer. MATERIALS AND METHODS: Institutional review board exemption was granted by the local research ethics committee for this retrospective study. Included were 64 men (mean age, 62 years [range, 40-76]; mean prostate-specific antigen, 8.2 ng/mL [8.2 μg/L] [range, 2.1-43 ng/mL]), 51 with biopsy-proved cancer and 13 suspected of having clinically significant cancer that was biopsy negative or without prior biopsy. MP MR imaging included T2-weighted, dynamic contrast-enhanced and diffusion-weighted imaging (1.5 T, pelvic phased-array coil). Three radiologists independently reviewed images and were blinded to results of biopsy. Two-by-two tables were derived by using sectors of analysis of four quadrants, two lobes, and one whole prostate. Primary target definition for clinically significant disease necessary to be present within a sector of analysis on TTPM for that sector to be deemed positive was set at Gleason score of 3+4 or more and/or cancer core length involvement of 4 mm or more. Sensitivity, negative predictive value, and negative likelihood ratio were calculated to determine ability of MP MR imaging to rule out cancer. Specificity, positive predictive value, positive likelihood ratio, accuracy (overall fraction correct), and area under receiver operating characteristic curves were also calculated. RESULTS: Twenty-eight percent (71 of 256) of sectors had clinically significant cancer by primary endpoint definition. For primary endpoint definition (≥ 4 mm and/or Gleason score ≥ 3+4), sensitivity, negative predictive value, and negative likelihood ratios were 58%-73%, 84%-89%, and 0.3-0.5, respectively. Specificity, positive predictive value, and positive likelihood ratios were 71%-84%, 49%-63%, and 2.-3.44, respectively. Area under the curve values were 0.73-0.84. CONCLUSION: Results of this study indicate that MP MR imaging has a high negative predictive value to rule out clinically significant prostate cancer and may potentially have clinical use in diagnostic pathways of men at risk

Patient-reported outcome (PRO) questionnaires for men who have radical surgery for prostate cancer: a conceptual review of existing instruments.

To critically review conceptual frameworks for available patient-reported outcome (PRO) questionnaires in men having radical prostatectomy (RP), psychometrically evaluate each questionnaire, and identify whether each is appropriate for use at the level of the individual patient. We searched PubMed, the Reports and Publications database of the University of Oxford Patient-Reported Outcomes Measurement Group and the website of the International Consortium for Health Outcomes Measurement (ICHOM) for psychometric reviews of prostate cancer-specific PRO questionnaires. From these we identified relevant questionnaires and critically appraised the conceptual content, guided by the Wilson and Cleary framework and psychometric properties, using well established criteria. The searches found four reviews and one recommendation paper. We identified seven prostate cancer-specific PROs: the Expanded Prostate Cancer Index Composite-26 (EPIC-26), Expanded Prostate Cancer Index Composite-50 (EPIC-50), University of California-Los Angeles Prostate Cancer Index (UCLA-PCI), Functional Assessment of Cancer Therapy - Prostate Cancer Subscale (FACT-P PCS), European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire - prostate specific 25-item (EORTC QLQ-PR25), Prostate Cancer - Quality of Life (PC-QoL), and Symptom Tracking and Reporting (STAR). Six out of seven measures purported to measure health-related quality of life (HRQL), but items focused strongly on urinary and sexual symptoms/functioning. The remaining questionnaire (STAR) claimed to assess functional recovery after RP. The psychometric evidence for these questionnaires was incomplete and variable in quality; none had evidence that they were appropriate for use with individual patients. Several questionnaires provide the basis of measures of urinary and/or sexual symptoms/functioning. Further work should explore other aspects of HRQL that are important for men having RP. Further psychometric work is also needed to determine whether they can be used at the individual level

Label-driven weakly-supervised learning for multimodal deformable image registration

Spatially aligning medical images from different modalities remains a challenging task, especially for intraoperative applications that require fast and robust algorithms. We propose a weakly-supervised, label-driven formulation for learning 3D voxel correspondence from higher-level label correspondence, thereby bypassing classical intensity-based image similarity measures. During training, a convolutional neural network is optimised by outputting a dense displacement field (DDF) that warps a set of available anatomical labels from the moving image to match their corresponding counterparts in the fixed image. These label pairs, including solid organs, ducts, vessels, point landmarks and other ad hoc structures, are only required at training time and can be spatially aligned by minimising a cross-entropy function of the warped moving label and the fixed label. During inference, the trained network takes a new image pair to predict an optimal DDF, resulting in a fully-automatic, label-free, real-time and deformable registration. For interventional applications where large global transformation prevails, we also propose a neural network architecture to jointly optimise the global- and local displacements. Experiment results are presented based on cross-validating registrations of 111 pairs of T2-weighted magnetic resonance images and 3D transrectal ultrasound images from prostate cancer patients with a total of over 4000 anatomical labels, yielding a median target registration error of 4.2 mm on landmark centroids and a median Dice of 0.88 on prostate glands.Comment: Accepted to ISBI 201

Prostate Imaging after Focal Ablation (PI-FAB): A Proposal for a Scoring System for Multiparametric MRI of the Prostate After Focal Therapy

At present there is no standardised system for scoring the appearance of the prostate on multiparametric magnetic resonance imaging (MRI) after focal ablation for localised prostate cancer. We propose a novel scoring system, the Prostate Imaging after Focal Ablation (PI-FAB) score, to fill this gap. PI-FAB involves a 3-point scale for rating MRI sequences in sequential order: (1) dynamic contrast-enhanced sequences; (2) diffusion-weighted imaging, split into assessment of the high-b-value sequence first and then the apparent diffusion coefficient map; and (3) T2-weighted imaging. It is essential that the pretreatment scan is also available to help with this assessment. We designed PI-FAB using our experience of reading postablation scans over the past 15 years and include details for four representative patients initially treated with high-intensity focus ultrasound at our institution to demonstrate the scoring system. We propose PI-FAB as a standardised method for evaluating prostate MRI scans after treatment with focal ablation. The next step is to evaluate its performance across multiple experienced readers of MRI after focal therapy in a clinical data set. PATIENT SUMMARY: We propose a scoring system called PI-FAB for assessing the appearance of magnetic resonance imaging scans of the prostate after focal treatment for localised prostate cancer. This will help clinicians in deciding on further follow-up

Butyrate conversion by sulfate-reducing and methanogenic communities from anoxic sediments of Aarhus Bay, Denmark

The conventional perception that the zone of sulfate reduction and methanogenesis are separated in high-and low-sulfate-containing marine sediments has recently been changed by studies demonstrating their co-occurrence in sediments. The presence of methanogens was linked to the presence of substrates that are not used by sulfate reducers. In the current study, we hypothesized that both groups can co-exist, consuming common substrates (H2 and/or acetate) in sediments. We enriched butyrate-degrading communities in sediment slurries originating from the sulfate, sulfate–methane transition, and methane zone of Aarhus Bay, Denmark. Sulfate was added at different concentrations (0, 3, 20 mM), and the slurries were incubated at 10◦ C and 25◦ C. During butyrate conversion, sulfate reduction and methanogenesis occurred simultaneously. The syntrophic butyrate degrader Syntrophomonas was enriched both in sulfate-amended and in sulfate-free slurries, indicating the occurrence of syntrophic conversions at both conditions. Archaeal community analysis revealed a dominance of Methanomicrobiaceae. The acetoclastic Methanosaetaceae reached high relative abundance in the absence of sulfate, while presence of acetoclastic Methanosarcinaceae was independent of the sulfate concentration, temperature, and the initial zone of the sediment. This study shows that there is no vertical separation of sulfate reducers, syntrophs, and methanogens in the sediment and that they all participate in the conversion of butyrate.</p

Sensory nerve transfers in the upper limb after peripheral nerve injury:a scoping review

Nerve transfer for motor nerve paralysis is an established technique for treating complex nerve injuries. However, nerve transfer for sensory reconstruction has not been widely used, and published research on this topic is limited compared to motor nerve transfer. The indications and outcomes of nerve transfer for the restoration of sensory function remain unproven. This scoping review examines the indications, outcomes and complications of sensory nerve transfer. In total, 22 studies were included; the major finding is that distal sensory nerve transfers are more successful than proximal ones in succeeding protective sensation. Although the risk of extension of the sensory deficit with donor site loss and morbidity from neuromas remain a barrier to wider adoption, these complications were not reported in the review. Further, the scarcity of studies and small patient series limit the ability to determine sensory nerve transfer success. However, sensory restoration remains an opportunity for surgeons to pursue.</p