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

Fabrication of Lateral Polysilicon Gap of Less than 50nm Using Conventional Lithography

We report a thermal oxidation process for the fabrication of nanogaps of less than 50 nmin dimension.Nanogaps of this dimension are necessary to eliminate contributions from double-layer capacitance in the dielectric detection of protein or nucleic acid. The method combines conventional photolithography and pattern-size reduction techniques. The gaps are fabricated on polysiliconcoated silicon substrate with gold electrodes. The dimensions of the structure are determined by scanning electron microscopy (SEM). An electrical characterization of the structures by dielectric analyzer (DA) shows an improved conductivity as well as enhanced permittivity and capacity with the reduction of gap size, suggesting its potential applications in the detection of biomolecule with very low level of power supply. Two chrome Masks are used to complete the work: the first Mask is for the nanogap pattern and the second one is for the electrodes. An improved resolution of pattern size is obtained by controlling the oxidation time. The method expected to enable fabrication of nanogaps with a wide ranging designs and dimensions on different substrates. It is a simple and cost-effective method and does not require complicated nanolithography process for fabricating desired nanogaps in a reproducible fashion

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

Systematic Review of Complications of Prostate Biopsy

AbstractContextProstate biopsy is commonly performed for cancer detection and management. The benefits and risks of prostate biopsy are germane to ongoing debates about prostate cancer screening and treatment.ObjectiveTo perform a systematic review of complications from prostate biopsy.Evidence acquisitionA literature search was performed using PubMed and Embase, supplemented with additional references. Articles were reviewed for data on the following complications: hematuria, rectal bleeding, hematospermia, infection, pain, lower urinary tract symptoms (LUTS), urinary retention, erectile dysfunction, and mortality.Evidence synthesisAfter biopsy, hematuria and hematospermia are common but typically mild and self-limiting. Severe rectal bleeding is uncommon. Despite antimicrobial prophylaxis, infectious complications are increasing over time and are the most common reason for hospitalization after biopsy. Pain may occur at several stages of prostate biopsy and can be mitigated by anesthetic agents and anxiety-reduction techniques. Up to 25% of men have transient LUTS after biopsy, and <2% have frank urinary retention, with slightly higher rates reported after transperineal template biopsy. Biopsy-related mortality is rare.ConclusionsPreparation for biopsy should include antimicrobial prophylaxis and pain management. Prostate biopsy is frequently associated with minor bleeding and urinary symptoms that usually do not require intervention. Infectious complications can be serious, requiring prompt management and continued work into preventative strategies

Diagnostic accuracy of magnetic resonance imaging targeted biopsy techniques compared to transrectal ultrasound guided biopsy of the prostate: a systematic review and meta-analysis

Background: Multiparametric MRI localizes cancer in the prostate, allowing for MRI guided biopsy (MRI-GB) 43 alongside transrectal ultrasound-guided systematic biopsy (TRUS-GB). Three MRI-GB approaches exist; visual estimation (COG-TB); fusion software-assisted (FUS-TB) and MRI ‘in-bore’ biopsy (IB-TB). It is unknown whether any of these are superior. We conducted a systematic review and meta-analysis to address three questions. First, whether MRI-GB is superior to TRUS-GB at detecting clinically significant PCa (csPCa). Second, whether MRI-GB is superior to TRUS-GB at avoiding detection of insignificant PCa. Third, whether any MRI-GB strategy is superior at detecting csPCa. Methods: A systematic literature review from 2015 to 2019 was performed in accordance with the START recommendations. Studies reporting PCa detection rates, employing MRI-GB and TRUS-GB were included and evaluated using the QUADAS-2 checklist. 1553 studies were found, of which 43 were included in the meta-analysis. Results: For csPCa, MRI-GB was superior in detection to TRUS-GB (0.83 vs. 0.63 [p = 0.02]). MRI-GB was superior in detection to TRUS-GB at avoiding detection of insignificant PCa. No MRI-GB technique was superior at detecting csPCa (IB-TB 0.87; COG TB 0.81; FUS-TB 0.81, [p = 0.55]). There was significant heterogeneity observed between the included studies. Conclusions: In patients with suspected PCa on MRI, MRI-GB offers superior rates of csPCa detection and reduces detection of insignificant PCa compared to TRUS-GB. No individual MRI-GB technique was found to be better in csPCa detection. Prospective adequately powered randomized controlled trials are required

The ReIMAGINE multimodal warehouse: using artificial intelligence for accurate risk stratification of prostate cancer

Introduction. Prostate cancer (PCa) is the most frequent cancer diagnosis in men worldwide. Our ability to identify those men whose cancer will decrease their lifespan and/or quality of life remains poor. The ReIMAGINE Consortium has been established to improve PCa diagnosis. Materials and methods. MRI will likely become the future cornerstone of the risk-stratification process for men at risk of early prostate cancer. We will, for the first time, be able to combine the underlying molecular changes in PCa with the state-of-the-art imaging. ReIMAGINE Screening invites men for MRI and PSA evaluation. ReIMAGINE Risk includes men at risk of prostate cancer based on MRI, and includes biomarker testing. Results. Baseline clinical information, genomics, blood, urine, fresh prostate tissue samples, digital pathology and radiomics data will be analysed. Data will be de-identified, stored with correlated mpMRI disease endotypes and linked with long term follow-up outcomes in an instance of the Philips Clinical Data Lake, consisting of cloud-based software. The ReIMAGINE platform includes application programming interfaces and a user interface that allows users to browse data, select cohorts, manage users and access rights, query data, and more. Connection to analytics tools such as Python allows statistical and stratification method pipelines to run profiling regression analyses. Discussion. The ReIMAGINE Multimodal Warehouse comprises a unique data source for PCa research, to improve risk stratification for PCa and inform clinical practice. The de-identified dataset characterized by clinical, imaging, genomics and digital pathology PCa patient phenotypes will be a valuable resource for the scientific and medical community

The ReIMAGINE prostate cancer risk study protocol: A prospective cohort study in men with a suspicion of prostate cancer who are referred onto an MRI-based diagnostic pathway with donation of tissue, blood and urine for biomarker analyses

INTRODUCTION: The ReIMAGINE Consortium was conceived to develop risk-stratification models that might incorporate the full range of novel prostate cancer (PCa) diagnostics (both commercial and academic). METHODS: ReIMAGINE Risk is an ethics approved (19/LO/1128) multicentre, prospective, observational cohort study which will recruit 1000 treatment-naive men undergoing a multi-parametric MRI (mpMRI) due to an elevated PSA (≤20ng/ml) or abnormal prostate examination who subsequently had a suspicious mpMRI (score≥3, stage ≤T3bN0M0). Primary outcomes include the detection of ≥Gleason 7 PCa at baseline and time to clinical progression, metastasis and death. Baseline blood, urine, and biopsy cores for fresh prostate tissue samples (2 targeted and 1 non-targeted) will be biobanked for future analysis. High-resolution scanning of pathology whole-slide imaging and MRI-DICOM images will be collected. Consortium partners will be granted access to data and biobanks to develop and validate biomarkers using correlation to mpMRI, biopsy-based disease status and long-term clinical outcomes. RESULTS: Recruitment began in September 2019(n = 533). A first site opened in September 2019 (n = 296), a second in November 2019 (n = 210) and a third in December 2020 (n = 27). Acceptance to the study has been 65% and a mean of 36.5ml(SD+/-10.0), 12.9ml(SD+/-3.7) and 2.8ml(SD+/-0.7) urine, plasma and serum donated for research, respectively. There are currently 4 academic and 15 commercial partners spanning imaging (~9 radiomics, artificial intelligence/machine learning), fluidic (~3 blood-based and ~2urine-based) and tissue-based (~1) biomarkers. CONCLUSION: The consortium will develop, or adjust, risk models for PCa, and provide a platform for evaluating the role of novel diagnostics in the era of pre-biopsy MRI and targeted biopsy

Multiparametric MRI followed by targeted prostate biopsy for men with suspected prostate cancer: a clinical decision analysis.

OBJECTIVE: To compare the diagnostic outcomes of the current approach of transrectal ultrasound (TRUS)-guided biopsy in men with suspected prostate cancer to an alternative approach using multiparametric MRI (mpMRI), followed by MRI-targeted biopsy if positive. DESIGN: Clinical decision analysis was used to synthesise data from recently emerging evidence in a format that is relevant for clinical decision making. POPULATION: A hypothetical cohort of 1000 men with suspected prostate cancer. INTERVENTIONS: mpMRI and, if positive, MRI-targeted biopsy compared with TRUS-guided biopsy in all men. OUTCOME MEASURES: We report the number of men expected to undergo a biopsy as well as the numbers of correctly identified patients with or without prostate cancer. A probabilistic sensitivity analysis was carried out using Monte Carlo simulation to explore the impact of statistical uncertainty in the diagnostic parameters. RESULTS: In 1000 men, mpMRI followed by MRI-targeted biopsy 'clinically dominates' TRUS-guided biopsy as it results in fewer expected biopsies (600 vs 1000), more men being correctly identified as having clinically significant cancer (320 vs 250), and fewer men being falsely identified (20 vs 50). The mpMRI-based strategy dominated TRUS-guided biopsy in 86% of the simulations in the probabilistic sensitivity analysis. CONCLUSIONS: Our analysis suggests that mpMRI followed by MRI-targeted biopsy is likely to result in fewer and better biopsies than TRUS-guided biopsy. Future research in prostate cancer should focus on providing precise estimates of key diagnostic parameters

Optimising the Diagnosis of Prostate Cancer in the Era of Multiparametric Magnetic Resonance Imaging : A Cost-effectiveness Analysis Based on the Prostate MR Imaging Study (PROMIS)

Background The current recommendation of using transrectal ultrasound-guided biopsy (TRUSB) to diagnose prostate cancer misses clinically significant (CS) cancers. More sensitive biopsies (eg, template prostate mapping biopsy [TPMB]) are too resource intensive for routine use, and there is little evidence on multiparametric magnetic resonance imaging (MPMRI). Objective To identify the most effective and cost-effective way of using these tests to detect CS prostate cancer. Design, setting, and participants Cost-effectiveness modelling of health outcomes and costs of men referred to secondary care with a suspicion of prostate cancer prior to any biopsy in the UK National Health Service using information from the diagnostic Prostate MR Imaging Study (PROMIS). Intervention Combinations of MPMRI, TRUSB, and TPMB, using different definitions and diagnostic cut-offs for CS cancer. Outcome measurements and statistical analysis Strategies that detect the most CS cancers given testing costs, and incremental cost-effectiveness ratios (ICERs) in quality-adjusted life years (QALYs) given long-term costs. Results and limitations The use of MPMRI first and then up to two MRI-targeted TRUSBs detects more CS cancers per pound spent than a strategy using TRUSB first (sensitivity = 0.95 [95% confidence interval {CI} 0.92–0.98] vs 0.91 [95% CI 0.86–0.94]) and is cost effective (ICER = £7,076 [€8350/QALY gained]). The limitations stem from the evidence base in the accuracy of MRI-targeted biopsy and the long-term outcomes of men with CS prostate cancer. Conclusions An MPMRI-first strategy is effective and cost effective for the diagnosis of CS prostate cancer. These findings are sensitive to the test costs, sensitivity of MRI-targeted TRUSB, and long-term outcomes of men with cancer, which warrant more empirical research. This analysis can inform the development of clinical guidelines. Patient summary We found that, under certain assumptions, the use of multiparametric magnetic resonance imaging first and then up to two transrectal ultrasound-guided biopsy is better than the current clinical standard and is good value for money. The use of multiparametric magnetic resonance imaging before transrectal ultrasound-guided biopsy can detect more clinically significant prostate cancer and be cost effective compared with the use of imaging post-biopsy