Development and Phantom Validation of a 3-D-Ultrasound-Guided System for Targeting MRI-Visible Lesions During Transrectal Prostate Biopsy

Smartglass augmented reality-assisted targeted prostate biopsy using cognitive point-of-care fusion technology

INTRODUCTION

MRI-guided targeted biopsy has become standard of care for diagnosis of prostate cancer, with establishment of several biopsy techniques and platforms. Augmented reality smart glasses have emerged as novel technology to support image-guided interventions. We aimed to investigate its usage while prostate biopsy.

METHODS

MRI with PIRADS-lesions ≥3 was uploaded to smart glasses (Vuzix Blade^R ) and augmented reality smart glasses-assisted targeted biopsy (SMART-TB) of the prostate was performed using cognitive fusion technology at the point of care. Detection rates were compared to systematic biopsy. Feasibility for SMART-TB was assessed (10 domains from bad [1] to excellent [10]).

RESULTS

SMART-TB was performed for four patients. Prostate cancer detection was more likely for SMART-TB (46%; 13/28) than for systematic biopsy (27%; 13/48). Feasibility scores were high [8-10] for practicality, multitasking, execution speed, comfort and device weight and low [1-4] for handling, battery and image quality. Median execution time: 28 min; Investment cost smart glass: 1017 USD.

CONCLUSION

First description of SMART-TB demonstrated convenient feasibility. This novel technology might enhance diagnosis of prostate cancer in future.

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.

Initial phantom studies for an office-based low-field MR system for prostate biopsy

Purpose

Prostate cancer is the second most prevalent cancer in US men, with about 192,000 new cases and 33,000 deaths predicted for 2020. With only a 31% 5-year survival rate for patients with an initial diagnosis of stage-four prostate cancer, the necessity for early screening and diagnosis is clear. In this paper, we present navigation accuracy results for Promaxo’s MR system intended to be used in a physician’s office for image-guided transperineal prostate biopsy.

Methods

The office-based low-field MR system was used to acquire images of prostate phantoms with needles inserted through a transperineal template. Coordinates of the estimated sample core locations in the office-based MR system were compared to ground truth needle coordinates identified in a 1.5T external reference scan. The error was measured as the distance between the planned target and the ground truth core center and as the shortest perpendicular distance between the planned target and the ground truth trajectory of the whole core.

Results

The average error between the planned target and the ground truth core center was 2.57 ± 1.02 mm, [1.93–3.21] 95% CI. The average error between the planned target to the actual core segment was 2.05 ± 1.24 mm, [1.53–2.56] 95% CI.

Conclusion

The average navigation errors were below the clinically significant threshold of 5 mm. The initial phantom results demonstrate the feasibility of the office-based system for prostate biopsy.

Arteriovenous fistula maturation and the influence of fluid dynamics

Arteriovenous fistula creation is the preferred vascular access for haemodialysis therapy, but has a large failure rate in the maturation period. This period generally lasts 6 to 8 weeks after surgical creation, in which the vein and artery undergo extensive vascular remodelling. In this review, we outline proposed mechanisms for both arteriovenous fistula maturation and arteriovenous fistula failure. Clinical, animal and computational studies have not yet shown a definitive link between any metric and disease development, although a number of theories based on wall shear stress metrics have been suggested. Recent work allowing patient-based longitudinal studies may hold the key to understanding arteriovenous fistula maturation processes.

SciKit-Surgery: compact libraries for surgical navigation

Purpose

This paper introduces the SciKit-Surgery libraries, designed to enable rapid development of clinical applications for image-guided interventions. SciKit-Surgery implements a family of compact, orthogonal, libraries accompanied by robust testing, documentation, and quality control. SciKit-Surgery libraries can be rapidly assembled into testable clinical applications and subsequently translated to production software without the need for software reimplementation. The aim is to support translation from single surgeon trials to multicentre trials in under 2 years.

Methods

At the time of publication, there were 13 SciKit-Surgery libraries provide functionality for visualisation and augmented reality in surgery, together with hardware interfaces for video, tracking, and ultrasound sources. The libraries are stand-alone, open source, and provide Python interfaces. This design approach enables fast development of robust applications and subsequent translation. The paper compares the libraries with existing platforms and uses two example applications to show how SciKit-Surgery libraries can be used in practice.

Results

Using the number of lines of code and the occurrence of cross-dependencies as proxy measurements of code complexity, two example applications using SciKit-Surgery libraries are analysed. The SciKit-Surgery libraries demonstrate ability to support rapid development of testable clinical applications. By maintaining stricter orthogonality between libraries, the number, and complexity of dependencies can be reduced. The SciKit-Surgery libraries also demonstrate the potential to support wider dissemination of novel research.

Conclusion

The SciKit-Surgery libraries utilise the modularity of the Python language and the standard data types of the NumPy package to provide an easy-to-use, well-tested, and extensible set of tools for the development of applications for image-guided interventions. The example application built on SciKit-Surgery has a simpler dependency structure than the same application built using a monolithic platform, making ongoing clinical translation more feasible.

Weakly-supervised convolutional neural networks for multimodal image registration

One of the fundamental challenges in supervised learning for multimodal image registration is the lack of ground-truth for voxel-level spatial correspondence. This work describes a method to infer voxel-level transformation from higher-level correspondence information contained in anatomical labels. We argue that such labels are more reliable and practical to obtain for reference sets of image pairs than voxel-level correspondence. Typical anatomical labels of interest may include solid organs, vessels, ducts, structure boundaries and other subject-specific ad hoc landmarks. The proposed end-to-end convolutional neural network approach aims to predict displacement fields to align multiple labelled corresponding structures for individual image pairs during the training, while only unlabelled image pairs are used as the network input for inference. We highlight the versatility of the proposed strategy, for training, utilising diverse types of anatomical labels, which need not to be identifiable over all training image pairs. At inference, the resulting 3D deformable image registration algorithm runs in real-time and is fully-automated without requiring any anatomical labels or initialisation. Several network architecture variants are compared for registering T2-weighted magnetic resonance images and 3D transrectal ultrasound images from prostate cancer patients. A median target registration error of 3.6 mm on landmark centroids and a median Dice of 0.87 on prostate glands are achieved from cross-validation experiments, in which 108 pairs of multimodal images from 76 patients were tested with high-quality anatomical labels.

A Methodology for Non-Invasive 3-D Surveillance of Arteriovenous Fistulae Using Freehand Ultrasound

OBJECTIVE

Surveillance techniques for arteriovenous fistulae are required to maintain functional vascular access, with two-dimensional duplex ultrasound the most widely used imaging modality. This paper presents a surveillance method for an arteriovenous fistula using a freehand three-dimensional (3-D) ultrasound system. A patient-case study highlights the applicability in a clinical environment.

METHODS

The freehand ultrasound system uses optical tracking to determine the vascular probe location, and as the probe is swept down a patient's arm, each B-mode slice is spatially arranged to be post-processed as a volume. The volume is segmented to obtain the 3-D vasculature for high detail analysis.

RESULTS

The results follow a patient with stenosis, undergoing surgery to have a stent placement. A surveillance scan was taken pre-surgery, postsurgery, and at a two-month follow-up. Vasculature changes are quantified using detailed analysis, and the benefits of using 3-D imaging are shown through 3-D printing and visualization.

CONCLUSION AND SIGNIFICANCE

Non-invasive 3-D surveillance of arteriovenous fistulae is possible, and a patient-specific geometry was created using ultrasound and optical tracking. Access to this non-invasive 3-D surveillance technique will enable future studies to determine patient-specific remodeling behavior, in terms of geometry and hemodynamics over time.

Freehand 3-D Ultrasound Imaging: A Systematic Review

Two-dimensional ultrasound (US) imaging has been successfully used in clinical applications as a low-cost, portable and non-invasive image modality for more than three decades. Recent advances in computer science and technology illustrate the promise of the 3-D US modality as a medical imaging technique that is comparable to other prevalent modalities and that overcomes certain drawbacks of 2-D US. This systematic review covers freehand 3-D US imaging between 1970 and 2017, highlighting the current trends in research fields, the research methods, the main limitations, the leading researchers, standard assessment criteria and clinical applications. Freehand 3-D US systems are more prevalent in the academic environment, whereas in clinical applications and industrial research, most studies have focused on 3-D US transducers and improvement of hardware performance. This topic is still an interesting active area for researchers, and there remain many unsolved problems to be addressed.