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Focal laser ablation is a minimally invasive method of treating cancerous lesions in organs such as prostate, liver and brain. Oncologic control is achieved by inducing hyperthermia throughout the target while minimizing damage to surrounding tissue. Consequently, successful clinical outcomes are contingent upon achieving desired ablation volumes. Magnetic resonance thermometry is frequently used to monitor the formation of the induced thermal damage zone and inform the decision to terminate energy delivery. However, due to the associated cost and complexity there is growing interest in the development of alternative approaches. Here we investigate the utility of real-time interstitial interrogation of laser-tissue interaction as an inexpensive alternative monitoring modality that provides direct assessment of tissue coagulation without the need for organ specific calibration. The optical contrast mechanism was determined using a Monte Carlo model. Subsequently, four interstitial probe designs were manufactured and assessed in a tissue mimicking phantom under simultaneous magnetic resonance imaging. Finally, the optimal probe design was evaluated in ex vivo bovine muscle. It was found to be capable of providing sufficient feedback to achieve pre-defined ablation radii in the range 4-7 mm with a mean absolute error of 0.3 mm. This approach provides an inexpensive monitoring modality that may facilitate widespread adoption of focal laser ablation.

Objective To demonstrate enabling multi-institutional training without centralizing or sharing the underlying physical data via federated learning (FL). Materials and Methods Deep learning models were trained at each participating institution using local clinical data, and an additional model was trained using FL across all of the institutions. Results We found that the FL model exhibited superior performance and generalizability to the models trained at single institutions, with an overall performance level that was significantly better than that of any of the institutional models alone when evaluated on held-out test sets from each institution and an outside challenge dataset. Discussion The power of FL was successfully demonstrated across 3 academic institutions while avoiding the privacy risk associated with the transfer and pooling of patient data. Conclusion Federated learning is an effective methodology that merits further study to enable accelerated development of models across institutions, enabling greater generalizability in clinical use.

Background Microstructural MRI has the potential to improve diagnosis and characterization of prostate cancer (PCa), but validation with histopathology is lacking. Purpose To validate ex vivo diffusion-relaxation correlation spectrum imaging (DR-CSI) in the characterization of microstructural tissue compartments in prostate specimens from men with PCa by using registered whole-mount digital histopathology (WMHP) as the reference standard. Materials and Methods Men with PCa who underwent 3-T MRI and robotic-assisted radical prostatectomy between June 2018 and January 2019 were prospectively studied. After prostatectomy, the fresh whole prostate specimens were imaged in patient-specific three-dimensionally printed molds by using 3-T MRI with DR-CSI and were then sliced to create coregistered WMHP slides. The DR-CSI spectral signal component fractions (fA, fB, fC) were compared with epithelial, stromal, and luminal area fractions (fepithelium, fstroma, flumen) quantified in PCa and benign tissue regions. A linear mixed-effects model assessed the correlations between (fA, fB, fC) and (fepithelium, fstroma, flumen), and the strength of correlations was evaluated by using Spearman correlation coefficients. Differences between PCa and benign tissues in terms of DR-CSI signal components and microscopic tissue compartments were assessed using two-sided t tests. Results Prostate specimens from nine men (mean age, 65 years ± 7 [standard deviation]) were evaluated; 20 regions from 17 PCas, along with 20 benign tissue regions of interest, were analyzed. Three DR-CSI spectral signal components (spectral peaks) were consistently identified. The fA, fB, and fC were correlated with fepithelium, fstroma, and flumen (all P < .001), with Spearman correlation coefficients of 0.74 (95% confidence interval [CI]: 0.62, 0.83), 0.80 (95% CI: 0.66, 0.89), and 0.67 (95% CI: 0.51, 0.81), respectively. PCa exhibited differences compared with benign tissues in terms of increased fA (PCa vs benign, 0.37 ± 0.05 vs 0.27 ± 0.06; P < .001), decreased fC (PCa vs benign, 0.18 ± 0.06 vs 0.31 ± 0.13; P = .01), increased fepithelium (PCa vs benign, 0.44 ± 0.13 vs 0.26 ± 0.16; P < .001), and decreased flumen (PCa vs benign, 0.14 ± 0.08 vs 0.27 ± 0.18; P = .004). Conclusion Diffusion-relaxation correlation spectrum imaging signal components correlate with microscopic tissue compartments in the prostate and differ between cancer and benign tissue. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Lee and Hectors in this issue.

OBJECTIVE To detail the development of an electronic report that graphically conveys all relevant information from targeted prostate biopsy. METHODS The Urology Integrated Diagnostic Report (Uro-IDR) is based on a published framework (RadPath) which enables the compilation of diagnostic data from urology, radiology, and pathology. Each component of the Uro-IDR is generated by the contributing clinician, is assembled in one document, and provides correlation of the 3 inputs at a glance. Upon completion, the Uro-IDR is automatically linked to the electronic medical record as an interactive file and can also be downloaded for offline sharing as a PDF. RESULTS At our institution, 1638 individual Uro-IDRs were generated between June 2016 and April 2019. There were 5715 views of these documents via the EMR. The average turnaround time for the creation of an individual report decreased from nearly 8 days at the time of its launch to 2 days after 6 months of use. The average time for report generation was 22 seconds for the pathologist and 69 seconds for the radiologist. An instructive video is linked to this article. CONCLUSION The Uro-IDR has proven to be a feasible, efficient, clinically useful form to concisely transmit key information about targeted prostate biopsy to both clinicians and patients.

INTRODUCTION AND OBJECTIVE:Focal Laser ablation (FLA) is a promising new treatment for prostate cancer (PCa). FLA has been performed successfully by radiologists inside an MRI. However, in-bore FLA...

INTRODUCTION AND OBJECTIVE:Micro-Ultrasound (microUS) is an emerging technology for visualization of prostate cancer with 300% improved resolution compared to conventional US. Initial experience us...

Introduction: A functional tool to optimize patient selection for magnetic resonance imaging (MRI)-guided prostate biopsy (MRGB) is an unmet clinical need. We sought to develop a prostate cancer risk calculator (PCRC-MRI) that combines MRI and clinical characteristics to aid decision-making for MRGB in North American men. Methods: Two prospective registries containing 2354 consecutive men undergoing MRGB (September 2009 to April 2019) were analyzed. Patients were randomized into five groups, with one group randomly assigned to be the validation cohort against the other four groups as the discovery cohort. The primary outcome was detection of clinically significant prostate cancer (csPCa) defined as Gleason grade group greater than or equal to 2. Variables included age, ethnicity, digital rectal exam (DRE), prior biopsy, prostate-specific antigen (PSA), prostate volume, PSA density, and MRI score. Odds ratios were calculated from multivariate logistic regression comparing two models: one with clinical variables only (clinical) against a second combining clinical variables with MRI data (clinical+MRI). Results: csPCa was present in 942 (40%) of the 2354 men available for study. The positive and negative predictive values for csPCa in the clinical+MRI model were 57% and 89%, respectively. The area under the curve of the clinical+MRI model was superior to the clinical model in discovery (0.843 vs. 0.707, p

OBJECTIVE: To study the relationship of maximum cancer core length, on targeted biopsy of MRI-visible index lesions, to volume of that tumor found at prostatectomy. PATIENTS AND METHODS: 205 men undergoing fusion biopsy and radical prostatectomy were divided into two groups: 136 in whom the maximum cancer core length came from an index MRI-visible lesion (targeted) and 69 in whom maximum cancer core length came from a non-targeted lesion. MRI was 3T multi-parametric and biopsy was via MRI-US fusion. RESULTS: In the targeted biopsy group, maximum cancer core length correlated with volume of clinically-significant index tumors (ρ=0.44–0.60, p10 mm) and MRI lesion diameter (>20 mm) were independently associated with tumor volume. Targeted maximum cancer core lengths >10 mm and Gleason scores >7 were each associated with pathological T3 disease (OR, 5.73 and 5.04, respectively), but MRI lesion diameter lesion was not. CONCLUSIONS: Maximum cancer core length on a targeted biopsy from an MRI-visible lesion is an independent predictor of both cancer volume and pathologic stage. This relationship does not exist for MCCL from a non-targeted biopsy core. Quantifying cancer core length on MRI-targeted biopsies may have a value, not previously described, to risk-stratify patients with prostate cancer before treatment.

PURPOSE: The appropriate number of systematic biopsy cores to retrieve during magnetic resonance imaging (MRI)-targeted prostate biopsy is not well defined. We aimed to demonstrate a biopsy sampling approach that reduces required core count while maintaining diagnostic performance. MATERIALS AND METHODS: We collected data from a cohort of 971 men who underwent MRI-ultrasound fusion targeted biopsy for suspected prostate cancer. A regional targeted biopsy (RTB) was evaluated retrospectively; only cores within 2 cm of the margin of a radiologist-defined region of interest were considered part of the RTB. We compared detection rates for clinically significant prostate cancer (csPCa) and cancer upgrading rate on final whole mount pathology after prostatectomy between RTB, combined, MRI-targeted, and systematic biopsy. RESULTS: A total of 16,459 total cores from 971 men were included in the study data sets, of which 1,535 (9%) contained csPCa. The csPCa detection rates for systematic, MRI-targeted, combined, and RTB were 27.0% (262/971), 38.3% (372/971), 44.8% (435/971), and 44.0% (427/971), respectively. Combined biopsy detected significantly more csPCa than systematic and MRI-targeted biopsy (p

In this article, we describe and illustrate an outpatient procedure for focal laser ablation (FLA) of prostate cancer (PCa). The procedure is conceptually similar to a fusion biopsy and is performed under local anesthesia in a clinic setting; treatment time is usually less than one hour. Laser insertion is guided by ultrasound; lesion targeting is via magnetic resonance imaging-ultrasound (MRI/US) fusion, as in targeted prostate biopsy. Real-time ablation monitoring is achieved utilizing a thermal probe adjacent to the laser fiber. The video demonstrates procedure planning, patient preparation, various steps during the procedure, and treatment monitoring. Safety, feasibility, and efficacy of this approach have been established during a previous trial. Outpatient FLA under local anesthesia is an option for management of intermediate risk prostate cancer.

Purpose Developing large-scale datasets with research-quality annotations is challenging due to the high cost of refining clinically generated markup into high precision annotations. We evaluated the direct use of a large dataset with only clinically generated annotations in development of high-performance segmentation models for small research-quality challenge datasets. Materials and methods We used a large retrospective dataset from our institution comprised of 1,620 clinically generated segmentations, and two challenge datasets (PROMISE12: 50 patients, ProstateX-2: 99 patients). We trained a 3D U-Net convolutional neural network (CNN) segmentation model using our entire dataset, and used that model as a template to train models on the challenge datasets. We also trained versions of the template model using ablated proportions of our dataset, and evaluated the relative benefit of those templates for the final models. Finally, we trained a version of the template model using an out-of-domain brain cancer dataset, and evaluated the relevant benefit of that template for the final models. We used five-fold cross-validation (CV) for all training and evaluation across our entire dataset. Results Our model achieves state-of-the-art performance on our large dataset (mean overall Dice 0.916, average Hausdorff distance 0.135 across CV folds). Using this model as a pre-trained template for refining on two external datasets significantly enhanced performance (30% and 49% enhancement in Dice scores respectively). Mean overall Dice and mean average Hausdorff distance were 0.912 and 0.15 for the ProstateX-2 dataset, and 0.852 and 0.581 for the PROMISE12 dataset. Using even small quantities of data to train the template enhanced performance, with significant improvements using 5% or more of the data. Conclusion We trained a state-of-the-art model using unrefined clinical prostate annotations and found that its use as a template model significantly improved performance in other prostate segmentation tasks, even when trained with only 5% of the original dataset.

INTRODUCTION AND OBJECTIVE:MRI guidance provides increased accuracy of prostate biopsy, and use of the PIRADS score helps determine cancer likelihood. However, when used alone the PIRADS score, esp...

PurposeWe assessed focal therapy eligibility in men who underwent multiparametric magnetic resonance imaging and targeted biopsy with correlation to whole mount histology after radical prostatectomy.Materials and methodsSubjects were selected from among the 454 men in whom targeted biopsy proven prostate cancer was derived from regions of interest on multiparametric magnetic resonance imaging from 2010 to 2016. Focal therapy eligibility was limited to a maximum Gleason score of 4 + 3 in regions of interest with or without other foci of low risk prostate cancer (Gleason score 3 + 3 and less than 4 mm). Men who did not meet NCCN® intermediate risk criteria were classified as ineligible for focal therapy. Of the 454 men 64 underwent radical prostatectomy and biopsy findings were compared to final pathology findings.ResultsOf the 454 men with a biopsy proven region of interest 175 (38.5%) were eligible for focal therapy. Fusion biopsy, which combined targeted and template biopsy, had 80.0% sensitivity (12 of 15 cases), 73.5% specificity (36 of 49) and 75.0% accuracy (48 of 64) for focal therapy eligibility. Targeted cores alone yielded 73.3% sensitivity (11 of 15 cases), 47.9% specificity (23 of 48) and 54.7% accuracy (35 of 64). Gleason score and extension across the midline differed in 4 and 9, respectively, of the 13 cases that showed discordant biopsy and whole mount histology.ConclusionsUsing intermediate risk eligibility criteria more than a third of men with a targeted biopsy proven lesion identified on multiparametric magnetic resonance imaging would have been eligible for focal therapy. Eligibility determined by fusion biopsy was concordant with whole mount histology in 75% of cases. Improved selection criteria are needed to reliably determine focal therapy eligibility.

Here, we present a protocol to perform targeted prostate biopsy using a magnetic resonance imaging-ultrasound (MRI/US) fusion system. Prostate cancer has traditionally been diagnosed via transrectal ultrasound (TRUS) biopsy. Though considered the gold standard, TRUS is unable to visualize most prostate cancer lesions and therefore requires sampling of the entire prostate. This biopsy method often undergrades prostate cancer and fails to detect up to 35% of cancers on initial biopsy. Prostate MRI has been shown to have excellent sensitivity in the detection of cancerous lesions, and advancements in MRI technology during the last decade have led to the development of targeted biopsy. In targeted biopsy, a software platform overlays MRI data onto live TRUS images to create a fused MRI/US three-dimensional model of the prostate. Regions suspicious for malignancy on MRI are contoured by a radiologist, uploaded into the fusion system, and then displayed within the live MRI/US fused model. The urologist is then able to directly biopsy these targets. When compared to conventional TRUS biopsy, MRI/US fusion technology has been demonstrated to improve the detection of clinically significant cancer while reducing insignificant cancer detection. This technology, therefore, has the potential to diagnose prostate cancer primarily in men who would benefit from treatment.

INTRODUCTION AND OBJECTIVES:Focal therapies such as hemi-gland ablation (HGA) are evolving treatment options for prostate cancer. However, limitations in current diagnostics--biopsy Gleason score, ...

INTRODUCTION AND OBJECTIVES:High-intensity focused ultrasound (HIFU) can be used to ablate prostate cancer (CaP) focally, non-invasively, and with minimal side effects. In this video, we present a ...

INTRODUCTION AND OBJECTIVES:MRI-targeted biopsy has improved the accuracy of prostate cancer diagnosis, but regions of interest (ROIs) are often labeled as equivocal category 3 lesions based on PIR...

INTRODUCTION AND OBJECTIVES:Hemiablation is a less morbid treatment alternative for select patients with unilateral prostate cancer. The accuracy of contemporary diagnostic techniques to identify a...

PURPOSE: To develop a phantom with optical and thermal properties matched to human prostate. This phantom will provide a platform for the development and characterization of 980nm laser interstitial thermal therapy (LITT) systems. METHODS: A polyacrylamide gel was doped with Naphthol Green B, Intralipid, and Bovine Serum Albumin (BSA). The necessary concentration of each ingredient was determined by measuring the optical properties via fluence measurements and light diffusion theory. LITT was then performed under the same conditions as a previous clinical trial in which temperature was monitored via a thermal probe. The thermal data and induced coagulation zone were compared to clinical data to illustrate the similarity between the phantom and patient. LITT was also performed under magnetic resonance thermometry (MRT). RESULTS: The requisite concentrations of Naphthol Green B, Intralipid and BSA were found to be 0.144% (w/v), 8.06% (v/v) and 31.4% (v/v) respectively. In the native state, the absorption coefficient and reduced scattering coefficient ([Formula: see text]) were found to be 0.66 ± 0.06 cm(−1) and 8.27 ± 0.50 cm(−1) respectively, with [Formula: see text] increasing to 17.63 ± 1.41 cm(−1) after coagulation. The thermal response of the phantom was similar to that observed clinically with maximum thermal probe measurements of 64.2°C and 66.9°C respectively. The shape of the induced coagulation zone was qualitatively and quantitatively similar to the MRT zone of elevated temperature and the coagulation zone observed clinically. CONCLUSIONS: A phantom which simulates optical and thermal response to 980nm LITT was constructed and demonstrated to be similar to human prostate.

Objective: This investigation was performed to evaluate the registration accuracy between magnetic resonance imaging (MRI) and pathology using three-dimensional (3-D) printed molds. Methods: Tissue-mimicking prostate phantoms were manufactured with embedded fiducials. The fiducials were used to measure and compare target registration error (TRE) between phantoms that were sliced by hand versus phantoms that were sliced within 3-D-printed molds. Subsequently, ten radical prostatectomy specimens were placed inside molds, scanned with MRI, and then sliced. The ex vivo scan was used to assess the true location of whole mount (WM) slides relative to in vivo MRI. The TRE between WM and in vivo MRI was measured using anatomic landmarks. Results: Manually sliced phantoms had a 4.1-mm mean TRE, whereas mold-sliced phantoms had a 1.9-mm mean TRE. Similarly, mold-assisted slicing reduced mean angular misalignment around the left-right (LR) anatomic axis from 10.7° to 4.5°. However, ex vivo MRI revealed that excised prostates were misaligned within molds, including a mean 14° rotation about the LR axis. The mean in-plane TRE was 3.3 mm using molds alone and 2.2 mm after registration was corrected with ex vivo MRI. Conclusion: Patient-specific molds improved accuracy relative to manual slicing techniques in a phantom model. However, the registration accuracy of surgically resected specimens was limited by their imperfect fit within molds. This limitation can be overcome with the addition of ex vivo imaging. Significance: The accuracy of 3-D-printed molds was characterized, quantifying their utility for facilitating MRI-pathology registration.

Robots ultrasound (RUS) can be defined as the combination of ultrasound imaging with a robotic system in medical interventions. With their potential for high precision, dexterity, and repeatability, robots are often uniquely suited for ultrasound integration. Although the field is relatively young, it has already generated a multitude of robotic systems for application in dozens of medical procedures. This paper reviews the robotic ultrasound systems that have been developed over the past two decades and describes their potential impact on modern medicine. The RUS projects reviewed include extracorporeal devices, needle guidance systems, and intraoperative systems.

PurposeWe evaluated the accuracy of magnetic resonance imaging in determining the size and shape of localized prostate cancer.Materials and methodsThe subjects were 114 men who underwent multiparametric magnetic resonance imaging before radical prostatectomy with patientspecific mold processing of the specimen from 2013 to 2015. T2-weighted images were used to contour the prostate capsule and cancer suspicious regions of interest. The contours were used to design and print 3-dimensional custom molds, which permitted alignment of excised prostates with magnetic resonance imaging scans. Tumors were reconstructed in 3 dimensions from digitized wholemount sections. Tumors were then matched with regions of interest and the relative geometries were compared.ResultsOf the 222 tumors evident on whole mount sections 118 had been identified on magnetic resonance imaging. For the 118 regions of interest mean volume was 0.8 cc and the longest 3-dimensional diameter was 17 mm. However, for matched pathological tumors, of which most were Gleason score 3 + 4 or greater, mean volume was 2.5 cc and the longest 3-dimensional diameter was 28mm. The median tumor had a 13.5 mm maximal extent beyond the magnetic resonance imaging contour and 80% of cancer volume from matched tumors wasoutside region of interest boundaries. Size estimation was most accurate in the axial plane and least accurate along the base-apex axis.ConclusionsMagnetic resonance imaging consistently underestimates the size and extent of prostate tumors. Prostate cancer foci had an average diameter 11mm longer and a volume 3 times greater than T2-weighted magnetic resonance imaging segmentations. These results may have important implications for the assessment andtreatment of prostate cancer.

We have developed a system for evaluating magnetic resonance imaging of prostate cancer, using patient-specific 3D printed molds to facilitate MR-histology correlation. Prior to radical prostatectomy a patient receives a multiparametric MRI, which an expert genitourinary radiologist uses to identify and contour regions suspicious for disease. The same MR series is used to generate a prostate contour, which is the basis for design of a patient-specific mold. The 3D printed mold contains a series of evenly spaced parallel slits, each of which corresponds to a known MRI slice. After surgery, the patient’s specimen is enclosed within the mold, and all whole-mount levels are obtained simultaneously through use of a multi-bladed slicing device. The levels are then formalin fixed, processed, and delivered to an expert pathologist, who identifies and grades all lesions within the slides. Finally, the lesion contours are loaded into custom software, which elastically warps them to fit the MR prostate contour. The suspicious regions on MR can then be directly compared to lesions on histology. Furthermore, the false-negative and false-positive regions on MR can be retrospectively examined, with the ultimate goal of developing methods for improving the predictive accuracy of MRI. This work presents the details of our analysis method, following a patient from diagnosis through the MR-histology correlation process. For this patient MRI successfully predicted the presence of cancer, but true lesion volume and extent were underestimated. Most cancer-positive regions missed on MR were observed to have patterns of low T2 signal, suggesting that there is potential to improve sensitivity.