Intraprocedural Diffusion-weighted Imaging for Predicting Ablation Zone during MRI-guided Focused Ultrasound of Prostate Cancer.

Purpose To compare diffusion-weighted imaging (DWI) with thermal dosimetry as a noncontrast method to predict ablation margins in individuals with prostate cancer treated with MRI-guided focused ultrasound (MRgFUS) ablation. Materials and Methods This secondary analysis of a prospective trial (ClinicalTrials.gov no. NCT01657942) included 17 participants (mean age, 64 years ± 6 [SD]; all male) who were treated for prostate cancer using MRgFUS in whom DWI was performed immediately after treatment. Ablation contours from computed thermal dosimetry and DWI as drawn by two blinded radiologists were compared against the reference standard of ablation assessment, posttreatment contrast-enhanced nonperfused volume (NPV) contours. The ability of each method to predict the ablation zone was analyzed quantitively using Dice similarity coefficients (DSCs) and mean Hausdorff distances (mHDs). Results DWI revealed a hyperintense rim at the margin of the ablation zone. While DWI accurately helped predict treatment margins, thermal dose contours underestimated the extent of the ablation zone compared with the T1-weighted NPV imaging reference standard. Quantitatively, contour assessment between methods showed that DWI-drawn contours matched postcontrast NPV contours (mean DSC = 0.84 ± 0.05 for DWI, mHD = 0.27 mm ± 0.13) better than the thermal dose contours did (mean DSC = 0.64 ± 0.12, mHD = 1.53 mm ± 1.20) (P < .001). Conclusion This study demonstrates that DWI, which can visualize the ablation zone directly, is a promising noncontrast method that is robust to treatment-related bulk motion compared with thermal dosimetry and correlates better than thermal dosimetry with the reference standard T1-weighted NPV. Keywords: Interventional-Body, Ultrasound-High-Intensity Focused (HIFU), Genital/Reproductive, Prostate, Oncology, Imaging Sequences, MRI-guided Focused Ultrasound, MR Thermometry, Diffusionweighted Imaging, Prostate Cancer ClinicalTrials.gov Identifier no. NCT01657942 Supplemental material is available for this article. © RSNA, 2024.

RAPHIA: A deep learning pipeline for the registration of MRI and whole-mount histopathology images of the prostate.

Image registration can map the ground truth extent of prostate cancer from histopathology images onto MRI, facilitating the development of machine learning methods for early prostate cancer detection. Here, we present RAdiology PatHology Image Alignment (RAPHIA), an end-to-end pipeline for efficient and accurate registration of MRI and histopathology images. RAPHIA automates several time-consuming manual steps in existing approaches including prostate segmentation, estimation of the rotation angle and horizontal flipping in histopathology images, and estimation of MRI-histopathology slice correspondences. By utilizing deep learning registration networks, RAPHIA substantially reduces computational time. Furthermore, RAPHIA obviates the need for a multimodal image similarity metric by transferring histopathology image representations to MRI image representations and vice versa. With the assistance of RAPHIA, novice users achieved expert-level performance, and their mean error in estimating histopathology rotation angle was reduced by 51% (12 degrees vs 8 degrees), their mean accuracy of estimating histopathology flipping was increased by 5% (95.3% vs 100%), and their mean error in estimating MRI-histopathology slice correspondences was reduced by 45% (1.12 slices vs 0.62 slices). When compared to a recent conventional registration approach and a deep learning registration approach, RAPHIA achieved better mapping of histopathology cancer labels, with an improved mean Dice coefficient of cancer regions outlined on MRI and the deformed histopathology (0.44 vs 0.48 vs 0.50), and a reduced mean per-case processing time (51 vs 11 vs 4.5 min). The improved performance by RAPHIA allows efficient processing of large datasets for the development of machine learning models for prostate cancer detection on MRI. Our code is publicly available at: https://github.com/pimed/RAPHIA.

MR-guided focused ultrasound therapy of extra-abdominal desmoid tumors: a multicenter retrospective study of 105 patients.

OBJECTIVE: To assess the safety and efficacy of magnetic resonance-guided focused ultrasound (MRgFUS) for the treatment extra-abdominal desmoids. METHODS: A total of 105 patients with desmoid fibromatosis (79 females, 26 males; 35 ± 14 years) were treated with MRgFUS between 2011 and 2021 in three centers. Total and viable tumors were evaluated per patient at last follow-up after treatment. Response and progression-free survival (PFS) were assessed with (modified) response evaluation criteria in solid tumors (RECIST v.1.1 and mRECIST). Change in Numerical Rating Scale (NRS) pain and 36-item Short Form Health Survey (SF-36) scores were compared. Treatment-related adverse events were recorded. RESULTS: The median initial tumor volume was 114 mL (IQR 314 mL). After MRgFUS, median total and viable tumor volume decreased to 51 mL (95% CI: 30-71 mL, n = 101, p < 0.0001) and 29 mL (95% CI: 17-57 mL, n = 88, p < 0.0001), respectively, at last follow-up (median: 15 months, 95% CI: 11-20 months). Based on total tumor measurements (RECIST), 86% (95% CI: 75-93%) had at least stable disease or better at last follow-up, but 50% (95% CI: 38-62%) of remaining viable nodules (mRECIST) progressed within the tumor. Median PFS was reached at 17 and 13 months for total and viable tumors, respectively. NRS decreased from 6 (IQR 3) to 3 (IQR 4) (p < 0.001). SF-36 scores improved (physical health (41 (IQR 15) to 46 (IQR 12); p = 0.05, and mental health (49 (IQR 17) to 53 (IQR 9); p = 0.02)). Complications occurred in 36%, most commonly 1st/2nd degree skin burns. CONCLUSION: MRgFUS reduced tumor volume, reduced pain, and improved quality of life in this series of 105 patients with extra-abdominal desmoid fibromatosis. CLINICAL RELEVANCE STATEMENT: Imaging-guided ablation is being increasingly used as an alternative to surgery, radiation, and medical therapy for the treatment of desmoid fibromatosis. MR-guided high-intensity focused ultrasound is an incisionless ablation technique that can be used to reduce tumor burden effectively and safely. KEY POINTS: • Desmoid fibromatosis was treated with MR-guided high-intensity focused ultrasound in 105 patients. • MR-guided focused ultrasound ablation reduced tumor volume and pain and improved quality of life. • MR-guided focused ultrasound is a treatment option for patients with extra-abdominal desmoid tumors.

High-Intensity Focused Ultrasound Surgery for Tumor Ablation: A Review of Current Applications.

The management of cancer with alternative approaches is a matter of clinical interest worldwide. High-intensity focused ultrasound (HIFU) surgery is a noninvasive technique performed under US or MRI guidance. The most studied therapeutic uses of HIFU involve thermal tissue ablation, demonstrating both palliative and curative potential. However, concurrent mechanical bioeffects also provide opportunities in terms of augmented drug delivery and immunosensitization. The safety and efficacy of HIFU integration with current cancer treatment strategies are being actively investigated in managing primary and secondary tumors, including cancers of the breast, prostate, pancreas, liver, kidney, and bone. Current primary HIFU indications are pain palliation, complete ablation of localized earlystage tumors, or debulking of unresectable late-stage cancers. This review presents the latest HIFU applications, from investigational to clinically approved, in the field of tumor ablation. Keywords: Ultrasound, Ultrasound-High Intensity Focused (HIFU), Interventional-MSK, Interventional-Body, Oncology, Technology Assessment, Tumor Response, MR Imaging © RSNA, 2023.

What predicts durable symptom relief of uterine fibroids treated with MRI-guided focused ultrasound? A multicenter trial in 8 academic centers.

OBJECTIVE: To identify variables predictive of durable clinical success after MRI-guided focused ultrasound (MRgFUS) treatment of uterine fibroids. MATERIALS AND METHODS: In this prospective, multicenter trial, 99 women with symptomatic uterine fibroids were treated using MRgFUS. Pelvic MRI was obtained at baseline and treatment day. The Uterine Fibroid Symptom-Quality of Life questionnaire was used to calculate a symptom severity score (SSS) at baseline and 6, 12, 24, and 36 months following treatment. Clinical, imaging, and treatment variables were correlated with symptom reduction sustained through the 12- and 24-month time points using univariable and multivariable logistic regression analyses. A novel parameter, the ratio of non-perfused volume to total fibroid load (NPV/TFL), was developed to determine association with durable outcomes. RESULTS: Post-treatment, mean symptom severity decreased at the 6-, 12-, 24-, and 36-month follow-ups (p < 0.001, all time points). In univariable analysis, three variables predicted treatment success (defined by ≥ 30-point improvement in SSS) sustained at both the 12-month and 24-month time points: increasing ratio of NPV/TFL (p = 0.002), decreasing total fibroid load (p = 0.04), and the absence of T2-weighted Funaki type 2 fibroids (p = 0.02). In multivariable analysis, the NPV/TFL was the sole predictor of durable clinical success (p = 0.01). Patients with ratios below 30% had less improvement in SSS and lacked durable clinical response compared with those between 30-79 (p = 0.03) and ≥ 80% (p = 0.01). CONCLUSION: Increased non-perfused volume relative to total fibroid volume was significantly associated with durable reduction of symptoms of abnormal uterine bleeding and bulk bother. CLINICAL RELEVANCE STATEMENT: Patient selection for sustained clinical benefit should emphasize those with likelihood of achieving high ablation ratios, as determined by imaging (e.g., device access, Funaki type) and by considering the total fibroid load, not just the primary symptomatic fibroid. TRIAL REGISTRATION: Clinical trial ID: NCT01285960. KEY POINTS: • Patient selection/treatment approach associated with durable symptom relief in MRI-guided focused ultrasound ablation of uterine fibroids remains unclear. • The ablation ratio, non-perfused volume/total fibroid volume, was positively associated with sustained symptom relief in both bleeding and bulk bother at 1- and 2-year follow-ups. • Selecting patients with imaging features that favor a high ratio of ablation to total fibroid load (including non-targeted fibroids) is the main factor in predicting durability of symptom relief after uterine fibroid treatment.

Focused Ultrasound and External Beam Radiation Therapy for Painful Bone Metastases: A Phase II Clinical Trial.

Background Recent consensus statements and clinical trials have assessed the value of MRI-guided focused ultrasound surgery for pain palliation of bone metastases; however, a comparison with external beam radiation therapy (EBRT) has not been performed. Purpose To compare safety and effectiveness data of MRI-guided focused ultrasound and EBRT in the treatment of bone metastases. Materials and Methods Participants with painful bone metastases, excluding skull and vertebral bodies, were enrolled in a prospective open-label nonrandomized phase II study between January 2017 and May 2019 and underwent either MRI-guided focused ultrasound or EBRT. The primary end point was the overall response rate at 1-month following treatment, assessed via the numeric rating scale (NRS) for pain (0-10 scale, with zero meaning "no pain" and 10 meaning "the worst pain imaginable"). Secondary end points were improvements at 12-month follow-up in NRS and quality of life (QoL) measures, including the Brief Pain Inventory (BPI), QoL-Questionnaire Cancer-15 Palliative Care (QLQ-C15-PAL), and QoL-Questionnaire Bone Metastases-22 (QLQ-BM22) and analysis of adverse events. Statistical analyses, including linear regression, χ2 test, and Student t test followed the per-protocol principle. Results Among 198 participants, 100 underwent MRI-guided focused ultrasound (mean age, 63 years ± 13 [SD]; 51 women), and 98 underwent EBRT (mean age, 65 years ± 14; 52 women). The overall response rates at 1-month follow-up were 91% (91 of 100) and 67% (66 of 98), respectively, in the focused ultrasound and EBRT arms (P < .001), and complete response rates were 43% (43 of 100) and 16% (16 of 98) (P < .001). The mean baseline NRS score was 7.0 ± 2.1 for focused ultrasound and 6.6 ± 2.4 for EBRT (P = .16); at 1-month follow-up, they were reduced to 3.2 ± 0.3 and 5.1 ± 0.3 (P < .001), respectively. QLQ-C15-PAL for physical function (P = .002), appetite (P < .001), nausea and vomiting (P < .001), dyspnea (P < .001), and QoL (P < .001) scores were lower in the focused ultrasound group. The overall adverse event rates were 15% (15 of 100) after focused ultrasound and 24% (24 of 98) after EBRT. Conclusion MRI-guided focused ultrasound surgery and external beam radiation therapy showed similar improvements in pain palliation and quality of life, with low adverse event rates. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Kelekis in this issue.

A Pilot Study of 68Ga-PSMA11 and 68Ga-RM2 PET/MRI for Biopsy Guidance in Patients with Suspected Prostate Cancer.

Targeting of lesions seen on multiparametric MRI (mpMRI) improves prostate cancer (PC) detection at biopsy. However, 20%-65% of highly suspicious lesions on mpMRI (PI-RADS [Prostate Imaging-Reporting and Data System] 4 or 5) are false-positives (FPs), while 5%-10% of clinically significant PC (csPC) are missed. Prostate-specific membrane antigen (PSMA) and gastrin-releasing peptide receptors (GRPRs) are both overexpressed in PC. We therefore aimed to evaluate the potential of 68Ga-PSMA11 and 68Ga-RM2 PET/MRI for biopsy guidance in patients with suspected PC. Methods: A highly selective cohort of 13 men, aged 58.0 ± 7.1 y, with suspected PC (persistently high prostate-specific antigen [PSA] and PSA density) but negative or equivocal mpMRI results or negative biopsy were prospectively enrolled to undergo 68Ga-PSMA11 and 68Ga-RM2 PET/MRI. PET/MRI included whole-body and dedicated pelvic imaging after a delay of 20 min. All patients had targeted biopsy of any lesions seen on PET followed by standard 12-core biopsy. The SUVmax of suspected PC lesions was collected and compared with gold standard biopsy. Results: PSA and PSA density at enrollment were 9.8 ± 6.0 (range, 1.5-25.5) ng/mL and 0.20 ± 0.18 (range, 0.06-0.68) ng/mL2, respectively. Standardized systematic biopsy revealed a total of 14 PCs in 8 participants: 7 were csPC and 7 were nonclinically significant PC (ncsPC). 68Ga-PSMA11 identified 25 lesions, of which 11 (44%) were true-positive (TP) (5 csPC). 68Ga-RM2 showed 27 lesions, of which 14 (52%) were TP, identifying all 7 csPC and also 7 ncsPC. There were 17 concordant lesions in 11 patients versus 14 discordant lesions in 7 patients between 68Ga-PSMA11 and 68Ga-RM2 PET. Incongruent lesions had the highest rate of FP (12 FP vs. 2 TP). SUVmax was significantly higher for TP than FP lesions in delayed pelvic imaging for 68Ga-PSMA11 (6.49 ± 4.14 vs. 4.05 ± 1.55, P = 0.023) but not for whole-body images, nor for 68Ga-RM2. Conclusion: Our results show that 68Ga-PSMA11 and 68Ga-RM2 PET/MRI are feasible for biopsy guidance in suspected PC. Both radiopharmaceuticals detected additional clinically significant cancers not seen on mpMRI in this selective cohort. 68Ga-RM2 PET/MRI identified all csPC confirmed at biopsy.

A Pilot Study of 68Ga-PSMA11 and 68Ga-RM2 PET/MRI for Evaluation of Prostate Cancer Response to High-Intensity Focused Ultrasound Therapy.

Focal therapy for localized prostate cancer (PC) using high-intensity focused ultrasound (HIFU) is gaining in popularity as it is noninvasive and associated with fewer side effects than standard whole-gland treatments. However, better methods to evaluate response to HIFU ablation are an unmet need. Prostate-specific membrane antigen (PSMA) and gastrin-releasing peptide receptors are both overexpressed in PC. In this study, we evaluated a novel approach of using both 68Ga-RM2 and 68Ga-PSMA11 PET/MRI in each patient before and after HIFU to assess the accuracy of target tumor localization and response to treatment. Methods: Fourteen men, 64.5 ± 8.0 y old (range, 48-78 y), with newly diagnosed PC were prospectively enrolled. Before HIFU, the patients underwent prostate biopsy, multiparametric MRI, 68Ga-PSMA11, and 68Ga-RM2 PET/MRI. Response to treatment was assessed at a minimum of 6 mo after HIFU with prostate biopsy (n = 13), as well as 68Ga-PSMA11 and 68Ga-RM2 PET/MRI (n = 14). The SUVmax and SUVpeak of known or suspected PC lesions were collected. Results: Pre-HIFU biopsy revealed 18 cancers, of which 14 were clinically significant (Gleason score ≥ 3 + 4). Multiparametric MRI identified 18 lesions; 14 of them were at least score 4 in the Prostate Imaging-Reporting and Data System. 68Ga-PSMA11 and 68Ga-RM2 PET/MRI each showed 23 positive intraprostatic lesions; 21 were congruent in 13 patients, and 5 were incongruent in 5 patients. Before HIFU, 68Ga-PSMA11 identified all target tumors, whereas 68Ga-RM2 PET/MRI missed 2 tumors. After HIFU, 68Ga-RM2 and 68Ga-PSMA11 PET/MRI both identified clinically significant residual disease in 1 patient. Three significant ipsilateral recurrent lesions were identified, whereas 1 was missed by 68Ga-PSMA11. The pretreatment level of prostate-specific antigen decreased significantly after HIFU, by 66%. Concordantly, the pretreatment SUVmax decreased significantly after HIFU for 68Ga-PSMA11 (P = 0.001) and 68Ga-RM2 (P = 0.005). Conclusion: This pilot study showed that 68Ga-PSMA11 and 68Ga-RM2 PET/MRI identified the target tumor for HIFU in 100% and 86% of cases, respectively, and accurately verified response to treatment. PET may be a useful tool in the guidance and monitoring of treatment success in patients receiving focal therapy for PC. These preliminary findings warrant larger studies for validation.

The Association of Tissue Change and Treatment Success During High-intensity Focused Ultrasound Focal Therapy for Prostate Cancer.

BACKGROUND: Tissue preservation strategies have been increasingly used for the management of localized prostate cancer. Focal ablation using ultrasound-guided high-intensity focused ultrasound (HIFU) has demonstrated promising short and medium-term oncological outcomes. Advancements in HIFU therapy such as the introduction of tissue change monitoring (TCM) aim to further improve treatment efficacy. OBJECTIVE: To evaluate the association between intraoperative TCM during HIFU focal therapy for localized prostate cancer and oncological outcomes 12 mo afterward. DESIGN, SETTING, AND PARTICIPANTS: Seventy consecutive men at a single institution with prostate cancer were prospectively enrolled. Men with prior treatment, metastases, or pelvic radiation were excluded to obtain a final cohort of 55 men. INTERVENTION: All men underwent HIFU focal therapy followed by magnetic resonance (MR)-fusion biopsy 12 mo later. Tissue change was quantified intraoperatively by measuring the backscatter of ultrasound waves during ablation. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Gleason grade group (GG) ≥2 cancer on postablation biopsy was the primary outcome. Secondary outcomes included GG ≥1 cancer, Prostate Imaging Reporting and Data System (PI-RADS) scores ≥3, and evidence of tissue destruction on post-treatment magnetic resonance imaging (MRI). A Student's t - test analysis was performed to evaluate the mean TCM scores and efficacy of ablation measured by histopathology. Multivariate logistic regression was also performed to identify the odds of residual cancer for each unit increase in the TCM score. RESULTS AND LIMITATIONS: A lower mean TCM score within the region of the tumor (0.70 vs 0.97, p = 0.02) was associated with the presence of persistent GG ≥2 cancer after HIFU treatment. Adjusting for initial prostate-specific antigen, PI-RADS score, Gleason GG, positive cores, and age, each incremental increase of TCM was associated with an 89% reduction in the odds (odds ratio: 0.11, confidence interval: 0.01-0.97) of having residual GG ≥2 cancer on postablation biopsy. Men with higher mean TCM scores (0.99 vs 0.72, p = 0.02) at the time of treatment were less likely to have abnormal MRI (PI-RADS ≥3) at 12 mo postoperatively. Cases with high TCM scores also had greater tissue destruction measured on MRI and fewer visible lesions on postablation MRI. CONCLUSIONS: Tissue change measured using TCM values during focal HIFU of the prostate was associated with histopathology and radiological outcomes 12 mo after the procedure. PATIENT SUMMARY: In this report, we looked at how well ultrasound changes of the prostate during focal high-intensity focused ultrasound (HIFU) therapy for the treatment of prostate cancer predict patient outcomes. We found that greater tissue change measured by the HIFU device was associated with less residual cancer at 1 yr. This tool should be used to ensure optimal ablation of the cancer and may improve focal therapy outcomes in the future.

A review of artificial intelligence in prostate cancer detection on imaging.

A multitude of studies have explored the role of artificial intelligence (AI) in providing diagnostic support to radiologists, pathologists, and urologists in prostate cancer detection, risk-stratification, and management. This review provides a comprehensive overview of relevant literature regarding the use of AI models in (1) detecting prostate cancer on radiology images (magnetic resonance and ultrasound imaging), (2) detecting prostate cancer on histopathology images of prostate biopsy tissue, and (3) assisting in supporting tasks for prostate cancer detection (prostate gland segmentation, MRI-histopathology registration, MRI-ultrasound registration). We discuss both the potential of these AI models to assist in the clinical workflow of prostate cancer diagnosis, as well as the current limitations including variability in training data sets, algorithms, and evaluation criteria. We also discuss ongoing challenges and what is needed to bridge the gap between academic research on AI for prostate cancer and commercial solutions that improve routine clinical care.

Evaluation of post-ablation mpMRI as a predictor of residual prostate cancer after focal high intensity focused ultrasound (HIFU) ablation.

PURPOSE: To evaluate the performance of multiparametric magnetic resonance imaging (mpMRI) and PSA testing in follow-up after high intensity focused ultrasound (HIFU) focal therapy for localized prostate cancer. METHODS: A total of 73 men with localized prostate cancer were prospectively enrolled and underwent focal HIFU followed by per-protocol PSA and mpMRI with systematic plus targeted biopsies at 12 months after treatment. We evaluated the association between post-treatment mpMRI and PSA with disease persistence on the post-ablation biopsy. We also assessed post-treatment functional and oncological outcomes. RESULTS: Median age was 69 years (Interquartile Range (IQR): 66-74) and median PSA was 6.9 ng/dL (IQR: 5.3-9.9). Of 19 men with persistent GG ≥ 2 disease, 58% (11 men) had no visible lesions on MRI. In the 14 men with PIRADS 4 or 5 lesions, 7 (50%) had either no cancer or GG 1 cancer at biopsy. Men with false negative mpMRI findings had higher PSA density (0.16 vs. 0.07 ng/mL2, P = 0.01). No change occurred in the mean Sexual Health Inventory for Men (SHIM) survey scores (17.0 at baseline vs. 17.7 post-treatment, P = 0.75) or International Prostate Symptom Score (IPSS) (8.1 at baseline vs. 7.7 at 24 months, P = 0.81) after treatment. CONCLUSIONS: Persistent GG ≥ 2 cancer may occur after focal HIFU. mpMRI alone without confirmatory biopsy may be insufficient to rule out residual cancer, especially in patients with higher PSA density. Our study also validates previously published studies demonstrating preservation of urinary and sexual function after HIFU treatment.

A Review of Imaging Methods to Assess Ultrasound-Mediated Ablation.

Ultrasound ablation techniques are minimally invasive alternatives to surgical resection and have rapidly increased in use. The response of tissue to HIFU ablation differs based on the relative contributions of thermal and mechanical effects, which can be varied to achieve optimal ablation parameters for a given tissue type and location. In tumor ablation, similar to surgical resection, it is desirable to include a safety margin of ablated tissue around the entirety of the tumor. A factor in optimizing ablative techniques is minimizing the recurrence rate, which can be due to incomplete ablation of the target tissue. Further, combining focal ablation with immunotherapy is likely to be key for effective treatment of metastatic cancer, and therefore characterizing the impact of ablation on the tumor microenvironment will be important. Thus, visualization and quantification of the extent of ablation is an integral component of ablative procedures. The aim of this review article is to describe the radiological findings after ultrasound ablation across multiple imaging modalities. This review presents readers with a general overview of the current and emerging imaging methods to assess the efficacy of ultrasound ablative treatments.

Comparison between MR and CT imaging used to correct for skull-induced phase aberrations during transcranial focused ultrasound.

Transcranial focused ultrasound with the InSightec Exablate system uses thermal ablation for the treatment of movement and mood disorders and blood brain barrier disruption for tumor therapy. The system uses computed tomography (CT) images to calculate phase corrections that account for aberrations caused by the human skull. This work investigates whether magnetic resonance (MR) images can be used as an alternative to CT images to calculate phase corrections. Phase corrections were calculated using the gold standard hydrophone method and the standard of care InSightec ray tracing method. MR binary image mask, MR-simulated-CT (MRsimCT), and CT images of three ex vivo human skulls were supplied as inputs to the InSightec ray tracing method. The degassed ex vivo human skulls were sonicated with a 670 kHz hemispherical phased array transducer (InSightec Exablate 4000). 3D raster scans of the beam profiles were acquired using a hydrophone mounted on a 3-axis positioner system. Focal spots were evaluated using six metrics: pressure at the target, peak pressure, intensity at the target, peak intensity, positioning error, and focal spot volume. Targets at the geometric focus and 5 mm lateral to the geometric focus were investigated. There was no statistical difference between any of the metrics at either target using either MRsimCT or CT for phase aberration correction. As opposed to the MRsimCT, the use of CT images for aberration correction requires registration to the treatment day MR images; CT misregistration within a range of ± 2 degrees of rotation error along three dimensions was shown to reduce focal spot intensity by up to 9.4%. MRsimCT images used for phase aberration correction for the skull produce similar results as CT-based correction, while avoiding both CT to MR registration errors and unnecessary patient exposure to ionizing radiation.

Management of Patients with Newly Diagnosed Desmoid Tumors in a First-Line Setting.

The initial management of desmoid tumors (DTs) is shifting from surgery towards active surveillance, with systemic and locally ablative treatments reserved for enlarging and/or symptomatic disease. However, it remains unclear which patients would benefit most from an initial conservative rather than interventional approach. To answer this question, we retrospectively analyzed adult and pediatric patients with DTs treated at a tertiary academic cancer center between 1992 and 2022. Outcomes measured were progression-free survival (PFS) and time to next treatment (TTNT) after first-line therapy. A total of 262 treatment-naïve patients were eligible for analysis with a median age of 36.5 years (range, 0−87 years). The 5-year PFS and the median TTNT (months) after first-line treatment were, respectively: 50.6% and 69.1 mo for surgery; 64.9% and 149.5 mo for surgery plus adjuvant radiotherapy; 57.1% and 44.7 mo for surgery plus adjuvant systemic therapy; 24.9% and 4.4 mo for chemotherapy; 26.7% and 5.3 mo for hormonal therapy; 41.3% and 29.6 mo for tyrosine kinase inhibitors (TKIs); 44.4% and 8.9 mo for cryoablation and high intensity focused ultrasound; and 43.1% and 32.7 mo for active surveillance. Age ≤ 40 years (p < 0.001), DTs involving the extremities (p < 0.001), a maximum tumor diameter > 60 mm (p = 0.04), and hormonal therapy (p = 0.03) predicted a higher risk of progression. Overall, our results suggest that active surveillance should be considered initially for patients with smaller asymptomatic DTs, while upfront TKIs, local ablation, and surgery achieve similar outcomes in those with more aggressive disease.

MRI-guided focused ultrasound focal therapy for patients with intermediate-risk prostate cancer: a phase 2b, multicentre study.

BACKGROUND: Men with grade group 2 or 3 prostate cancer are often considered ineligible for active surveillance; some patients with grade group 2 prostate cancer who are managed with active surveillance will have early disease progression requiring radical therapy. This study aimed to investigate whether MRI-guided focused ultrasound focal therapy can safely reduce treatment burden for patients with localised grade group 2 or 3 intermediate-risk prostate cancer. METHODS: In this single-arm, multicentre, phase 2b study conducted at eight health-care centres in the USA, we recruited men aged 50 years and older with unilateral, MRI-visible, primary, intermediate-risk, previously untreated prostate adenocarcinoma (prostate-specific antigen ≤20 ng/mL, grade group 2 or 3; tumour classification ≤T2) confirmed on combined biopsy (combining MRI-targeted and systematic biopsies). MRI-guided focused ultrasound energy, sequentially titrated to temperatures sufficient for tissue ablation (about 60-70°C), was delivered to the index lesion and a planned margin of 5 mm or more of normal tissue, using real-time magnetic resonance thermometry for intraoperative monitoring. Co-primary outcomes were oncological outcomes (absence of grade group 2 and higher cancer in the treated area at 6-month and 24-month combined biopsy; when 24-month biopsy data were not available and grade group 2 or higher cancer had occurred in the treated area at 6 months, the 6-month biopsy results were included in the final analysis) and safety (adverse events up to 24 months) in all patients enrolled in the study. This study is registered with ClinicalTrials.gov, NCT01657942, and is no longer recruiting. FINDINGS: Between May 4, 2017, and Dec 21, 2018, we assessed 194 patients for eligibility and treated 101 patients with MRI-guided focused ultrasound. Median age was 63 years (IQR 58-67) and median concentration of prostate-specific antigen was 5·7 ng/mL (IQR 4·2-7·5). Most cancers were grade group 2 (79 [78%] of 101). At 24 months, 78 (88% [95% CI 79-94]) of 89 men had no evidence of grade group 2 or higher prostate cancer in the treated area. No grade 4 or grade 5 treatment-related adverse events were reported, and only one grade 3 adverse event (urinary tract infection) was reported. There were no treatment-related deaths. INTERPRETATION: 24-month biopsy outcomes show that MRI-guided focused ultrasound focal therapy is safe and effectively treats grade group 2 or 3 prostate cancer. These results support focal therapy for select patients and its use in comparative trials to determine if a tissue-preserving approach is effective in delaying or eliminating the need for radical whole-gland treatment in the long term. FUNDING: Insightec and the National Cancer Institute.

Computational Detection of Extraprostatic Extension of Prostate Cancer on Multiparametric MRI Using Deep Learning.

The localization of extraprostatic extension (EPE), i.e., local spread of prostate cancer beyond the prostate capsular boundary, is important for risk stratification and surgical planning. However, the sensitivity of EPE detection by radiologists on MRI is low (57% on average). In this paper, we propose a method for computational detection of EPE on multiparametric MRI using deep learning. Ground truth labels of cancers and EPE were obtained in 123 patients (38 with EPE) by registering pre-surgical MRI with whole-mount digital histopathology images from radical prostatectomy. Our approach has two stages. First, we trained deep learning models using the MRI as input to generate cancer probability maps both inside and outside the prostate. Second, we built an image post-processing pipeline that generates predictions for EPE location based on the cancer probability maps and clinical knowledge. We used five-fold cross-validation to train our approach using data from 74 patients and tested it using data from an independent set of 49 patients. We compared two deep learning models for cancer detection: (i) UNet and (ii) the Correlated Signature Network for Indolent and Aggressive prostate cancer detection (CorrSigNIA). The best end-to-end model for EPE detection, which we call EPENet, was based on the CorrSigNIA cancer detection model. EPENet was successful at detecting cancers with extraprostatic extension, achieving a mean area under the receiver operator characteristic curve of 0.72 at the patient-level. On the test set, EPENet had 80.0% sensitivity and 28.2% specificity at the patient-level compared to 50.0% sensitivity and 76.9% specificity for the radiologists. To account for spatial location of predictions during evaluation, we also computed results at the sextant-level, where the prostate was divided into sextants according to standard systematic 12-core biopsy procedure. At the sextant-level, EPENet achieved mean sensitivity 61.1% and mean specificity 58.3%. Our approach has the potential to provide the location of extraprostatic extension using MRI alone, thus serving as an independent diagnostic aid to radiologists and facilitating treatment planning.

68Ga-PSMA-11 PET/MRI in Patients with Newly Diagnosed Intermediate- or High-Risk Prostate Adenocarcinoma: PET Findings Correlate with Outcomes After Definitive Treatment.

Prostate-specific membrane antigen (PSMA) PET offers an accuracy superior to other imaging modalities in initial staging of prostate cancer and is more likely to affect management. We examined the prognostic value of 68Ga-PSMA-11 uptake in the primary lesion and presence of metastatic disease on PET in newly diagnosed prostate cancer patients before initial therapy. Methods: In a prospective study from April 2016 to December 2020, 68Ga-PSMA-11 PET/MRI was performed in men with a new diagnosis of intermediate- or high-grade prostate cancer who were candidates for prostatectomy. Patients were followed up after initial therapy for up to 5 y. We examined the Kendall correlation between PET (intense uptake in the primary lesion and presence of metastatic disease) and clinical and pathologic findings (grade group, extraprostatic extension, nodal involvement) relevant for risk stratification, and examined the relationship between PET findings and outcome using Kaplan-Meier analysis. Results: Seventy-three men (age, 64.0 ± 6.3 y) were imaged. Seventy-two had focal uptake in the prostate, and in 20 (27%) PSMA-avid metastatic disease was identified. Uptake correlated with grade group and prostate-specific antigen (PSA). Presence of PSMA metastasis correlated with grade group and pathologic nodal stage. PSMA PET had higher per-patient positivity than nodal dissection in patients with only 5-15 nodes removed (8/41 vs. 3/41) but lower positivity if more than 15 nodes were removed (13/21 vs. 10/21). High uptake in the primary lesion (SUVmax > 12.5, P = 0.008) and presence of PSMA metastasis (P = 0.013) were associated with biochemical failure, and corresponding hazard ratios for recurrence within 2 y (4.93 and 3.95, respectively) were similar to or higher than other clinicopathologic prognostic factors. Conclusion: 68Ga-PSMA-11 PET can risk-stratify patients with intermediate- or high-grade prostate cancer before prostatectomy based on degree of uptake in the prostate and presence of metastatic disease.

Correlation of 68Ga-RM2 PET with Postsurgery Histopathology Findings in Patients with Newly Diagnosed Intermediate- or High-Risk Prostate Cancer.

68Ga-RM2 targets gastrin-releasing peptide receptors (GRPRs), which are overexpressed in prostate cancer (PC). Here, we compared preoperative 68Ga-RM2 PET to postsurgery histopathology in patients with newly diagnosed intermediate- or high-risk PC. Methods: Forty-one men, 64.0 ± 6.7 y old, were prospectively enrolled. PET images were acquired 42-72 min (median ± SD, 52.5 ± 6.5 min) after injection of 118.4-247.9 MBq (median ± SD, 138.0 ± 22.2 MBq) of 68Ga-RM2. PET findings were compared with preoperative multiparametric MRI (mpMRI) (n = 36) and 68Ga-PSMA11 PET (n = 17) and correlated to postprostatectomy whole-mount histopathology (n = 32) and time to biochemical recurrence. Nine participants decided to undergo radiation therapy after study enrollment. Results: All participants had intermediate- (n = 17) or high-risk (n = 24) PC and were scheduled for prostatectomy. Prostate-specific antigen was 8.8 ± 77.4 (range, 2.5-504) and 7.6 ± 5.3 ng/mL (range, 2.5-28.0 ng/mL) when participants who ultimately underwent radiation treatment were excluded. Preoperative 68Ga-RM2 PET identified 70 intraprostatic foci of uptake in 40 of 41 patients. Postprostatectomy histopathology was available in 32 patients in which 68Ga-RM2 PET identified 50 of 54 intraprostatic lesions (detection rate = 93%). 68Ga-RM2 uptake was recorded in 19 nonenlarged pelvic lymph nodes in 6 patients. Pathology confirmed lymph node metastases in 16 lesions, and follow-up imaging confirmed nodal metastases in 2 lesions. 68Ga-PSMA11 and 68Ga-RM2 PET identified 27 and 26 intraprostatic lesions, respectively, and 5 pelvic lymph nodes each in 17 patients. Concordance between 68Ga-RM2 and 68Ga-PSMA11 PET was found in 18 prostatic lesions in 11 patients and 4 lymph nodes in 2 patients. Noncongruent findings were observed in 6 patients (intraprostatic lesions in 4 patients and nodal lesions in 2 patients). Sensitivity and accuracy rates for 68Ga-RM2 and 68Ga-PSMA11 (98% and 89% for 68Ga-RM2 and 95% and 89% for 68Ga-PSMA11) were higher than those for mpMRI (77% and 77%, respectively). Specificity was highest for mpMRI with 75% followed by 68Ga-PSMA11 (67%) and 68Ga-RM2 (65%). Conclusion: 68Ga-RM2 PET accurately detects intermediate- and high-risk primary PC, with a detection rate of 93%. In addition, 68Ga-RM2 PET showed significantly higher specificity and accuracy than mpMRI and a performance similar to 68Ga-PSMA11 PET. These findings need to be confirmed in larger studies to identify which patients will benefit from one or the other or both radiopharmaceuticals.

Bridging the gap between prostate radiology and pathology through machine learning.

BACKGROUND: Prostate cancer remains the second deadliest cancer for American men despite clinical advancements. Currently, magnetic resonance imaging (MRI) is considered the most sensitive non-invasive imaging modality that enables visualization, detection, and localization of prostate cancer, and is increasingly used to guide targeted biopsies for prostate cancer diagnosis. However, its utility remains limited due to high rates of false positives and false negatives as well as low inter-reader agreements. PURPOSE: Machine learning methods to detect and localize cancer on prostate MRI can help standardize radiologist interpretations. However, existing machine learning methods vary not only in model architecture, but also in the ground truth labeling strategies used for model training. We compare different labeling strategies and the effects they have on the performance of different machine learning models for prostate cancer detection on MRI. METHODS: Four different deep learning models (SPCNet, U-Net, branched U-Net, and DeepLabv3+) were trained to detect prostate cancer on MRI using 75 patients with radical prostatectomy, and evaluated using 40 patients with radical prostatectomy and 275 patients with targeted biopsy. Each deep learning model was trained with four different label types: pathology-confirmed radiologist labels, pathologist labels on whole-mount histopathology images, and lesion-level and pixel-level digital pathologist labels (previously validated deep learning algorithm on histopathology images to predict pixel-level Gleason patterns) on whole-mount histopathology images. The pathologist and digital pathologist labels (collectively referred to as pathology labels) were mapped onto pre-operative MRI using an automated MRI-histopathology registration platform. RESULTS: Radiologist labels missed cancers (ROC-AUC: 0.75-0.84), had lower lesion volumes (~68% of pathology lesions), and lower Dice overlaps (0.24-0.28) when compared with pathology labels. Consequently, machine learning models trained with radiologist labels also showed inferior performance compared to models trained with pathology labels. Digital pathologist labels showed high concordance with pathologist labels of cancer (lesion ROC-AUC: 0.97-1, lesion Dice: 0.75-0.93). Machine learning models trained with digital pathologist labels had the highest lesion detection rates in the radical prostatectomy cohort (aggressive lesion ROC-AUC: 0.91-0.94), and had generalizable and comparable performance to pathologist label-trained-models in the targeted biopsy cohort (aggressive lesion ROC-AUC: 0.87-0.88), irrespective of the deep learning architecture. Moreover, machine learning models trained with pixel-level digital pathologist labels were able to selectively identify aggressive and indolent cancer components in mixed lesions on MRI, which is not possible with any human-annotated label type. CONCLUSIONS: Machine learning models for prostate MRI interpretation that are trained with digital pathologist labels showed higher or comparable performance with pathologist label-trained models in both radical prostatectomy and targeted biopsy cohort. Digital pathologist labels can reduce challenges associated with human annotations, including labor, time, inter- and intra-reader variability, and can help bridge the gap between prostate radiology and pathology by enabling the training of reliable machine learning models to detect and localize prostate cancer on MRI.