Evaluation of a Cascaded Deep Learning-based Algorithm for Prostate Lesion Detection at Biparametric MRI.

Background Multiparametric MRI (mpMRI) improves prostate cancer (PCa) detection compared with systematic biopsy, but its interpretation is prone to interreader variation, which results in performance inconsistency. Artificial intelligence (AI) models can assist in mpMRI interpretation, but large training data sets and extensive model testing are required. Purpose To evaluate a biparametric MRI AI algorithm for intraprostatic lesion detection and segmentation and to compare its performance with radiologist readings and biopsy results. Materials and Methods This secondary analysis of a prospective registry included consecutive patients with suspected or known PCa who underwent mpMRI, US-guided systematic biopsy, or combined systematic and MRI/US fusion-guided biopsy between April 2019 and September 2022. All lesions were prospectively evaluated using Prostate Imaging Reporting and Data System version 2.1. The lesion- and participant-level performance of a previously developed cascaded deep learning algorithm was compared with histopathologic outcomes and radiologist readings using sensitivity, positive predictive value (PPV), and Dice similarity coefficient (DSC). Results A total of 658 male participants (median age, 67 years [IQR, 61-71 years]) with 1029 MRI-visible lesions were included. At histopathologic analysis, 45% (294 of 658) of participants had lesions of International Society of Urological Pathology (ISUP) grade group (GG) 2 or higher. The algorithm identified 96% (282 of 294; 95% CI: 94%, 98%) of all participants with clinically significant PCa, whereas the radiologist identified 98% (287 of 294; 95% CI: 96%, 99%; P = .23). The algorithm identified 84% (103 of 122), 96% (152 of 159), 96% (47 of 49), 95% (38 of 40), and 98% (45 of 46) of participants with ISUP GG 1, 2, 3, 4, and 5 lesions, respectively. In the lesion-level analysis using radiologist ground truth, the detection sensitivity was 55% (569 of 1029; 95% CI: 52%, 58%), and the PPV was 57% (535 of 934; 95% CI: 54%, 61%). The mean number of false-positive lesions per participant was 0.61 (range, 0-3). The lesion segmentation DSC was 0.29. Conclusion The AI algorithm detected cancer-suspicious lesions on biparametric MRI scans with a performance comparable to that of an experienced radiologist. Moreover, the algorithm reliably predicted clinically significant lesions at histopathologic examination. ClinicalTrials.gov Identifier: NCT03354416 © RSNA, 2024 Supplemental material is available for this article.

Smartphone Augmented Reality Outperforms Conventional CT Guidance for Composite Ablation Margins in Phantom Models.

PURPOSE: To develop and evaluate a smartphone augmented reality (AR) system for a large 50-mm liver tumor ablation with treatment planning for composite overlapping ablation zones. MATERIALS AND METHODS: A smartphone AR application was developed to display tumor, probe, projected probe paths, ablated zones, and real-time percentage of the ablated target tumor volume. Fiducial markers were attached to phantoms and an ablation probe hub for tracking. The system was evaluated with tissue-mimicking thermochromic phantoms and gel phantoms. Four interventional radiologists performed 2 trials each of 3 probe insertions per trial using AR guidance versus computed tomography (CT) guidance approaches in 2 gel phantoms. Insertion points and optimal probe paths were predetermined. On Gel Phantom 2, serial ablated zones were saved and continuously displayed after each probe placement/adjustment, enabling feedback and iterative planning. The percentages of tumor ablated for AR guidance versus CT guidance, and with versus without display of recorded ablated zones, were compared among interventional radiologists with pairwise t-tests. RESULTS: The means of percentages of tumor ablated for CT freehand and AR guidance were 36% ± 7 and 47% ± 4 (P = .004), respectively. The mean composite percentages of tumor ablated for AR guidance were 43% ± 1 (without) and 50% ± 2 (with display of ablation zone) (P = .033). There was no strong correlation between AR-guided percentage of ablation and years of experience (r < 0.5), whereas there was a strong correlation between CT-guided percentage of ablation and years of experience (r > 0.9). CONCLUSIONS: A smartphone AR guidance system for dynamic iterative large liver tumor ablation was accurate, performed better than conventional CT guidance, especially for less experienced interventional radiologists, and enhanced more standardized performance across experience levels for ablation of a 50-mm tumor.

Image-Guided Transbronchial Pulmonary Cryoablation with a Flexible Cryoprobe in Swine: Performance and Radiology-Pathology Correlation.

PURPOSE: To evaluate the performance of a prototype flexible transbronchial cryoprobe compared with that of percutaneous transthoracic cryoablation and to define cone-beam computed tomography (CT) imaging and pathology cryolesion features in an in vivo swine model. MATERIALS AND METHODS: Transbronchial cryoablation was performed with a prototype flexible cryoprobe (3 central and 3 peripheral lung ablations in 3 swine) and compared with transthoracic cryoablation performed with a commercially available rigid cryoprobe (2 peripheral lung ablations in 1 swine). Procedural time and cryoablation success rates for endobronchial navigation and cryoneedle deployment were measured. Intraoperative cone-beam CT imaging features of cryolesions were characterized and correlated with gross pathology and hematoxylin and eosin-stained sections of the explanted cryolesions. RESULTS: The flexible cryoprobe was successfully navigated and delivered to each target through a steerable guiding sheath (6/6). At 4 minutes after ablation, 5 of 6 transbronchial and 2 of 2 transthoracic cryolesions were visible on cone-beam CT. The volumes on cone-beam CT images were 55.5 cm3 (SE ± 8.0) for central transbronchial ablations (n = 2), 72.5 cm3 (SE ± 8.1) for peripheral transbronchial ablations (n = 3), and 79.5 cm3 (SE ±11.6) for peripheral transthoracic ablations (n = 2). Pneumothorax developed in 1 animal after transbronchial ablation and during ablation in the transthoracic cryoablation. Images of cryoablation zones on cone-beam CT correlated well with the matched gross pathology and histopathology sections of the cryolesions. CONCLUSIONS: Transbronchial cryoablation with a flexible cryoprobe, delivered through a steerable guiding sheath, is feasible. Transbronchial cryoablation zones are imageable with cone-beam CT, with gross pathology and histopathology similar to those of transthoracic cryoablation.

PI-RADS Version 2.0 Versus Version 2.1: Comparison of Prostate Cancer Gleason Grade Upgrade and Downgrade Rates From MRI-Targeted Biopsy to Radical Prostatectomy.

BACKGROUND. Precise risk stratification through MRI/ultrasound (US) fusion-guided targeted biopsy (TBx) can guide optimal prostate cancer (PCa) management. OBJECTIVE. The purpose of this study was to compare PI-RADS version 2.0 (v2.0) and PI-RADS version 2.1 (v2.1) in terms of the rates of International Society of Urological Pathology (ISUP) grade group (GG) upgrade and downgrade from TBx to radical prostatectomy (RP). METHODS. This study entailed a retrospective post hoc analysis of patients who underwent 3-T prostate MRI at a single institution from May 2015 to March 2023 as part of three prospective clinical trials. Trial participants who underwent MRI followed by MRI/US fusion-guided TBx and RP within a 1-year interval were identified. A single genitourinary radiologist performed clinical interpretations of the MRI examinations using PI-RADS v2.0 from May 2015 to March 2019 and PI-RADS v2.1 from April 2019 to March 2023. Upgrade and downgrade rates from TBx to RP were compared using chi-square tests. Clinically significant cancer was defined as ISUP GG2 or greater. RESULTS. The final analysis included 308 patients (median age, 65 years; median PSA density, 0.16 ng/mL2). The v2.0 group (n = 177) and v2.1 group (n = 131) showed no significant difference in terms of upgrade rate (29% vs 22%, respectively; p = .15), downgrade rate (19% vs 21%, p = .76), clinically significant upgrade rate (14% vs 10%, p = .27), or clinically significant downgrade rate (1% vs 1%, p > .99). The upgrade rate and downgrade rate were also not significantly different between the v2.0 and v2.1 groups when stratifying by index lesion PI-RADS category or index lesion zone, as well as when assessed only in patients without a prior PCa diagnosis (all p > .01). Among patients with GG2 or GG3 at RP (n = 121 for v2.0; n = 103 for v2.1), the concordance rate between TBx and RP was not significantly different between the v2.0 and v2.1 groups (53% vs 57%, p = .51). CONCLUSION. Upgrade and downgrade rates from TBx to RP were not significantly different between patients whose MRI examinations were clinically interpreted using v2.0 or v2.1. CLINICAL IMPACT. Implementation of the most recent PI-RADS update did not improve the incongruence in PCa grade assessment between TBx and surgery.

Artificial Intelligence and Infectious Disease Imaging.

The mass production of the graphics processing unit and the coronavirus disease 2019 (COVID-19) pandemic have provided the means and the motivation, respectively, for rapid developments in artificial intelligence (AI) and medical imaging techniques. This has led to new opportunities to improve patient care but also new challenges that must be overcome before these techniques are put into practice. In particular, early AI models reported high performances but failed to perform as well on new data. However, these mistakes motivated further innovation focused on developing models that were not only accurate but also stable and generalizable to new data. The recent developments in AI in response to the COVID-19 pandemic will reap future dividends by facilitating, expediting, and informing other medical AI applications and educating the broad academic audience on the topic. Furthermore, AI research on imaging animal models of infectious diseases offers a unique problem space that can fill in evidence gaps that exist in clinical infectious disease research. Here, we aim to provide a focused assessment of the AI techniques leveraged in the infectious disease imaging research space, highlight the unique challenges, and discuss burgeoning solutions.

Is prostatic adenocarcinoma with cribriform architecture more difficult to detect on prostate MRI?

BACKGROUND: Cribriform (CBFM) pattern on prostate biopsy has been implicated as a predictor for high-risk features, potentially leading to adverse outcomes after definitive treatment. This study aims to investigate whether the CBFM pattern containing prostate cancers (PCa) were associated with false negative magnetic resonance imaging (MRI) and determine the association between MRI and histopathological disease burden. METHODS: Patients who underwent multiparametric magnetic resonance imaging (mpMRI), combined 12-core transrectal ultrasound (TRUS) guided systematic (SB) and MRI/US fusion-guided biopsy were retrospectively queried for the presence of CBFM pattern at biopsy. Biopsy cores and lesions were categorized as follows: C0 = benign, C1 = PCa with no CBFM pattern, C2 = PCa with CBFM pattern. Correlation between cancer core length (CCL) and measured MRI lesion dimension were assessed using a modified Pearson correlation test for clustered data. Differences between the biopsy core groups were assessed with the Wilcoxon-signed rank test with clustering. RESULTS: Between 2015 and 2022, a total of 131 consecutive patients with CBFM pattern on prostate biopsy and pre-biopsy mpMRI were included. Clinical feature analysis included 1572 systematic biopsy cores (1149 C0, 272 C1, 151 C2) and 736 MRI-targeted biopsy cores (253 C0, 272 C1, 211 C2). Of the 131 patients with confirmed CBFM pathology, targeted biopsy (TBx) alone identified CBFM in 76.3% (100/131) of patients and detected PCa in 97.7% (128/131) patients. SBx biopsy alone detected CBFM in 61.1% (80/131) of patients and PCa in 90.8% (119/131) patients. TBx and SBx had equivalent detection in patients with smaller prostates (p = 0.045). For both PCa lesion groups there was a positive and significant correlation between maximum MRI lesion dimension and CCL (C1 lesions: p < 0.01, C2 lesions: p < 0.001). There was a significant difference in CCL between C1 and C2 lesions for T2 scores of 3 and 5 (p ≤ 0.01, p ≤ 0.01, respectively) and PI-RADS 5 lesions (p ≤ 0.01), with C2 lesions having larger CCL, despite no significant difference in MRI lesion dimension. CONCLUSIONS: The extent of disease for CBFM-containing tumors is difficult to capture on mpMRI. When comparing MRI lesions of similar dimensions and PIRADS scores, CBFM-containing tumors appear to have larger cancer yield on biopsy. Proper staging and planning of therapeutic interventions is reliant on accurate mpMRI estimation. Special considerations should be taken for patients with CBFM pattern on prostate biopsy.

MRI-Targeted, Systematic, and Combined Biopsy for Prostate Cancer Diagnosis.

BACKGROUND: The use of 12-core systematic prostate biopsy is associated with diagnostic inaccuracy that contributes to both overdiagnosis and underdiagnosis of prostate cancer. Biopsies performed with magnetic resonance imaging (MRI) targeting may reduce the misclassification of prostate cancer in men with MRI-visible lesions. METHODS: Men with MRI-visible prostate lesions underwent both MRI-targeted and systematic biopsy. The primary outcome was cancer detection according to grade group (i.e., a clustering of Gleason grades). Grade group 1 refers to clinically insignificant disease; grade group 2 or higher, cancer with favorable intermediate risk or worse; and grade group 3 or higher, cancer with unfavorable intermediate risk or worse. Among the men who underwent subsequent radical prostatectomy, upgrading and downgrading of grade group from biopsy to whole-mount histopathological analysis of surgical specimens were recorded. Secondary outcomes were the detection of cancers of grade group 2 or higher and grade group 3 or higher, cancer detection stratified by previous biopsy status, and grade reclassification between biopsy and radical prostatectomy. RESULTS: A total of 2103 men underwent both biopsy methods; cancer was diagnosed in 1312 (62.4%) by a combination of the two methods (combined biopsy), and 404 (19.2%) underwent radical prostatectomy. Cancer detection rates on MRI-targeted biopsy were significantly lower than on systematic biopsy for grade group 1 cancers and significantly higher for grade groups 3 through 5 (P<0.01 for all comparisons). Combined biopsy led to cancer diagnoses in 208 more men (9.9%) than with either method alone and to upgrading to a higher grade group in 458 men (21.8%). However, if only MRI-target biopsies had been performed, 8.8% of clinically significant cancers (grade group ≥3) would have been misclassified. Among the 404 men who underwent subsequent radical prostatectomy, combined biopsy was associated with the fewest upgrades to grade group 3 or higher on histopathological analysis of surgical specimens (3.5%), as compared with MRI-targeted biopsy (8.7%) and systematic biopsy (16.8%). CONCLUSIONS: Among patients with MRI-visible lesions, combined biopsy led to more detection of all prostate cancers. However, MRI-targeted biopsy alone underestimated the histologic grade of some tumors. After radical prostatectomy, upgrades to grade group 3 or higher on histopathological analysis were substantially lower after combined biopsy. (Funded by the National Institutes of Health and others; Trio Study ClinicalTrials.gov number, NCT00102544.).

Prospective Evaluation of PI-RADS Version 2.1 for Prostate Cancer Detection and Investigation of Multiparametric MRI-derived Markers.

Background Data regarding the prospective performance of Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 alone and in combination with quantitative MRI features for prostate cancer detection is limited. Purpose To assess lesion-based clinically significant prostate cancer (csPCa) rates in different PI-RADS version 2.1 categories and to identify MRI features that could improve csPCa detection. Materials and Methods This single-center prospective study included men with suspected or known prostate cancer who underwent multiparametric MRI and MRI/US-guided biopsy from April 2019 to December 2021. MRI scans were prospectively evaluated using PI-RADS version 2.1. Atypical transition zone (TZ) nodules were upgraded to category 3 if marked diffusion restriction was present. Lesions with an International Society of Urological Pathology (ISUP) grade of 2 or higher (range, 1-5) were considered csPCa. MRI features, including three-dimensional diameter, relative lesion volume (lesion volume divided by prostate volume), sphericity, and surface to volume ratio (SVR), were obtained from lesion contours delineated by the radiologist. Univariable and multivariable analyses were conducted at the lesion and participant levels to determine features associated with csPCa. Results In total, 454 men (median age, 67 years [IQR, 62-73 years]) with 838 lesions were included. The csPCa rates for lesions categorized as PI-RADS 1 (n = 3), 2 (n = 170), 3 (n = 197), 4 (n = 319), and 5 (n = 149) were 0%, 9%, 14%, 37%, and 77%, respectively. csPCa rates of PI-RADS 4 lesions were lower than PI-RADS 5 lesions (P < .001) but higher than PI-RADS 3 lesions (P < .001). Upgraded PI-RADS 3 TZ lesions were less likely to harbor csPCa compared with their nonupgraded counterparts (4% [one of 26] vs 20% [20 of 99], P = .02). Predictors of csPCa included relative lesion volume (odds ratio [OR], 1.6; P < .001), SVR (OR, 6.2; P = .02), and extraprostatic extension (EPE) scores of 2 (OR, 9.3; P < .001) and 3 (OR, 4.1; P = .02). Conclusion The rates of csPCa differed between consecutive PI-RADS categories of 3 and higher. MRI features, including lesion volume, shape, and EPE scores of 2 and 3, predicted csPCa. Upgrading of PI-RADS category 3 TZ lesions may result in unnecessary biopsies. ClinicalTrials.gov registration no. NCT03354416 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Goh in this issue.

Deep Learning-Based T2-weighted MR Image Quality Assessment and Its Impact on Prostate Cancer Detection Rates.

BACKGROUND: Image quality evaluation of prostate MRI is important for successful implementation of MRI into localized prostate cancer diagnosis. PURPOSE: To examine the impact of image quality on prostate cancer detection using an in-house previously developed artificial intelligence (AI) algorithm. STUDY TYPE: Retrospective. SUBJECTS: 615 consecutive patients (median age 67 [interquartile range [IQR]: 61-71] years) with elevated serum PSA (median PSA 6.6 [IQR: 4.6-9.8] ng/mL) prior to prostate biopsy. FIELD STRENGTH/SEQUENCE: 3.0T/T2-weighted turbo-spin-echo MRI, high b-value echo-planar diffusion-weighted imaging, and gradient recalled echo dynamic contrast-enhanced. ASSESSMENTS: Scans were prospectively evaluated during clinical readout using PI-RADSv2.1 by one genitourinary radiologist with 17 years of experience. For each patient, T2-weighted images (T2WIs) were classified as high-quality or low-quality based on evaluation of both general distortions (eg, motion, distortion, noise, and aliasing) and perceptual distortions (eg, obscured delineation of prostatic capsule, prostatic zones, and excess rectal gas) by a previously developed in-house AI algorithm. Patients with PI-RADS category 1 underwent 12-core ultrasound-guided systematic biopsy while those with PI-RADS category 2-5 underwent combined systematic and targeted biopsies. Patient-level cancer detection rates (CDRs) were calculated for clinically significant prostate cancer (csPCa, International Society of Urological Pathology Grade Group ≥2) by each biopsy method and compared between high- and low-quality images in each PI-RADS category. STATISTICAL TESTS: Fisher's exact test. Bootstrap 95% confidence intervals (CI). A P value <0.05 was considered statistically significant. RESULTS: 385 (63%) T2WIs were classified as high-quality and 230 (37%) as low-quality by AI. Targeted biopsy with high-quality T2WIs resulted in significantly higher clinically significant CDR than low-quality images for PI-RADS category 4 lesions (52% [95% CI: 43-61] vs. 32% [95% CI: 22-42]). For combined biopsy, there was no significant difference in patient-level CDRs for PI-RADS 4 between high- and low-quality T2WIs (56% [95% CI: 47-64] vs. 44% [95% CI: 34-55]; P = 0.09). DATA CONCLUSION: Higher quality T2WIs were associated with better targeted biopsy clinically significant cancer detection performance for PI-RADS 4 lesions. Combined biopsy might be needed when T2WI is lower quality. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1.

Multiparametric prostate magnetic resonance imaging in the evaluation of prostate cancer.

Imaging has traditionally played a minor role in the diagnosis and staging of prostate cancer. However, recent controversies generated by the use of prostate-specific antigen (PSA) screening followed by random biopsy have encouraged the development of new imaging methods for prostate cancer. Multiparametric magnetic resonance imaging (mpMRI) has emerged as the imaging method best able to detect clinically significant prostate cancers and to guide biopsies. Here, the authors explain what mpMRI is and how it is used clinically, especially with regard to high-risk populations, and we discuss the impact of mpMRI on treatment decisions for men with prostate cancer. CA Cancer J Clin 2016;66:326-336. © 2015 American Cancer Society.

Comparison of MRI-Based Staging and Pathologic Staging for Predicting Biochemical Recurrence of Prostate Cancer After Radical Prostatectomy.

BACKGROUND. Currently most clinical models for predicting biochemical recurrence (BCR) of prostate cancer (PCa) after radical prostatectomy (RP) incorporate staging information from RP specimens, creating a gap in preoperative risk assessment. OBJECTIVE. The purpose of our study was to compare the utility of presurgical staging information from MRI and postsurgical staging information from RP pathology in predicting BCR in patients with PCa. METHODS. This retrospective study included 604 patients (median age, 60 years) with PCa who underwent prostate MRI before RP from June 2007 to December 2018. A single genitourinary radiologist assessed MRI examinations for extraprostatic extension (EPE) and seminal vesicle invasion (SVI) during clinical interpretations. The utility of EPE and SVI on MRI and RP pathology for BCR prediction was assessed through Kaplan-Meier and Cox proportional hazards analyses. Established clinical BCR prediction models, including the University of California San Francisco Cancer of the Prostate Risk Assessment (UCSF-CAPRA) model and the Cancer of the Prostate Risk Assessment Postsurgical (CAPRA-S) model, were evaluated in a subset of 374 patients with available Gleason grade groups from biopsy and RP pathology; two CAPRA-MRI models (CAPRA-S model with modifications to replace RP pathologic staging features with MRI staging features) were also assessed. RESULTS. Univariable predictors of BCR included EPE on MRI (HR = 3.6), SVI on MRI (HR = 4.4), EPE on RP pathology (HR = 5.0), and SVI on RP pathology (HR = 4.6) (all p < .001). Three-year BCR-free survival (RFS) rates for patients without versus with EPE were 84% versus 59% for MRI and 89% versus 58% for RP pathology, and 3-year RFS rates for patients without versus with SVI were 82% versus 50% for MRI and 83% versus 54% for RP histology (all p < .001). For patients with T3 disease on RP pathology, 3-year RFS rates were 67% and 41% for patients without and with T3 disease on MRI. AUCs of CAPRA models, including CAPRA-MRI models, ranged from 0.743 to 0.778. AUCs were not significantly different between CAPRA-S and CAPRA-MRI models (p > .05). RFS rates were significantly different between low- and intermediate-risk groups for only CAPRA-MRI models (80% vs 51% and 74% vs 44%; both p < .001). CONCLUSION. Presurgical MRI-based staging features perform comparably to postsurgical pathologic staging features for predicting BCR. CLINICAL IMPACT. MRI staging can preoperatively identify patients at high BCR risk, helping to inform early clinical decision-making. TRIAL REGISTRATION. ClinicalTrials.gov NCT00026884 and NCT02594202.

A Phase II Study of Pembrolizumab in Combination with Capecitabine and Oxaliplatin with Molecular Profiling in Patients with Advanced Biliary Tract Carcinoma.

BACKGROUND: We conducted a phase II study of the combination of pembrolizumab with capecitabine and oxaliplatin (CAPOX) in patients with advanced biliary tract carcinoma (BTC) to assess response rate and clinical efficacy. Exploratory objectives included correlative studies of immune marker expression, tumor evolution, and immune infiltration in response to treatment. PATIENTS AND METHODS: Adult patients with histologically confirmed BTC were enrolled and received oxaliplatin and pembrolizumab on day 1 of cycles 1-6. Capecitabine was administered orally twice daily as intermittent treatment, with the first dose on day 1 and the last dose on day 14 of cycles 1-6. Starting on cycle 7, pembrolizumab monotherapy was continued until disease progression. The primary endpoint was progression-free survival (PFS). Secondary endpoints were safety, tolerability, feasibility, and response rate. Immunohistochemistry (IHC) for PD-L1 and immune infiltrates was analyzed in paired tumor biopsies, as well as bulk transcriptome and exome profiling for five patients and single-cell RNA sequencing for one partial responder. RESULTS: Eleven patients enrolled, three of whom had received no prior systemic therapy. Treatment was well tolerated, and the most common treatment-related grade 3 or 4 adverse events were lymphocytopenia, anemia, and decreased platelet count. Three patients (27.3%) achieved a partial response, and six (54%) had stable disease. The disease control rate was 81.8%. The median PFS was 4.1 months with a 6-month PFS rate of 45.5%. Molecular profiling suggests qualitative differences in immune infiltration and clonal evolution based on response. CONCLUSION: Capecitabine and oxaliplatin in combination with pembrolizumab is tolerable and a potentially effective treatment for refractory advanced BTC. This study highlights a design framework for the precise characterization of individual BTC tumors. TRIAL REGISTRATION: This study was registered in ClinicalTrials.gov (NCT03111732).

Why Does Magnetic Resonance Imaging-Targeted Biopsy Miss Clinically Significant Cancer?

PURPOSE: Multiple studies demonstrate magnetic resonance imaging (MRI)-targeted biopsy detects more clinically significant cancer than systematic biopsy; however, some clinically significant cancers are detected by systematic biopsy only. While these events are rare, we sought to perform a retrospective analysis of these cases to ascertain the reasons that MRI-targeted biopsy missed clinically significant cancer which was subsequently detected on systematic prostate biopsy. MATERIALS AND METHODS: Patients were enrolled in a prospective study comparing cancer detection rates by transrectal MRI-targeted fusion biopsy and systematic 12-core biopsy. Patients with an elevated prostate specific antigen (PSA), abnormal digital rectal examination, or imaging findings concerning for prostate cancer underwent prostate MRI and subsequent MRI-targeted and systematic biopsy in the same setting. The subset of patients with grade group (GG) ≥3 cancer found on systematic biopsy and GG ≤2 cancer (or no cancer) on MRI-targeted biopsy was classified as MRI-targeted biopsy misses. A retrospective analysis of the MRI and MRI-targeted biopsy real-time screen captures determined the cause of MRI-targeted biopsy miss. Multivariable logistic regression analysis compared baseline characteristics of patients with MRI-targeted biopsy misses to GG-matched patients whose clinically significant cancer was detected by MRI-targeted biopsy. RESULTS: Over the study period of 2007 to 2019, 2,103 patients met study inclusion criteria and underwent combined MRI-targeted and systematic prostate biopsies. A total of 41 (1.9%) men were classified as MRI-targeted biopsy misses. Most MRI-targeted biopsy misses were due to errors in lesion targeting (21, 51.2%), followed by MRI-invisible lesions (17, 40.5%) and MRI lesions missed by the radiologist (3, 7.1%). On logistic regression analysis, lower Prostate Imaging-Reporting and Data System (PI-RADSTM) score was associated with having clinically significant cancer missed on MRI-targeted biopsy. CONCLUSIONS: While uncommon, most MRI-targeted biopsy misses are due to errors in lesion targeting, which highlights the importance of accurate co-registration and targeting when using software-based fusion platforms. Additionally, some patients will harbor MRI-invisible lesions which are untargetable by MRI-targeted platforms. The presence of a low PI-RADS score despite a high PSA is suggestive of harboring an MRI-invisible lesion.

Magnetic Resonance Imaging-Guided Biopsy in Active Surveillance of Prostate Cancer.

PURPOSE: The underlying premise of prostate cancer active surveillance (AS) is that cancers likely to metastasize will be recognized and eliminated before cancer-related disease can ensue. Our study was designed to determine the prostate cancer upgrading rate when biopsy guided by magnetic resonance imaging (MRGBx) is used before entry and during AS. MATERIALS AND METHODS: The cohort included 519 men with low- or intermediate-risk prostate cancer who enrolled in prospective studies (NCT00949819 and NCT00102544) between February 2008 and February 2020. Subjects were preliminarily diagnosed with Gleason Grade Group (GG) 1 cancer; AS began when subsequent MRGBx confirmed GG1 or GG2. Participants underwent confirmatory MRGBx (targeted and systematic) followed by surveillance MRGBx approximately every 12 to 24 months. The primary outcome was tumor upgrading to ≥GG3. RESULTS: Upgrading to ≥GG3 was found in 92 men after a median followup of 4.8 years (IQR 3.1-6.5) after confirmatory MRGBx. Upgrade-free probability after 5 years was 0.85 (95% CI 0.81-0.88). Cancer detected in a magnetic resonance imaging lesion at confirmatory MRGBx increased risk of subsequent upgrading during AS (HR 2.8; 95% CI 1.3-6.0), as did presence of GG2 (HR 2.9; 95% CI 1.1-8.2) In men who upgraded ≥GG3 during AS, upgrading was detected by targeted cores only in 27%, systematic cores only in 25% and both in 47%. In 63 men undergoing prostatectomy, upgrading from MRGBx was found in only 5 (8%). CONCLUSIONS: When AS begins and follows with MRGBx (targeted and systematic), upgrading rate (≥GG3) is greater when tumor is initially present within a magnetic resonance imaging lesion or when pathology is GG2 than when these features are absent.

Chest imaging in patients with acute respiratory failure because of coronavirus disease 2019.

PURPOSE OF REVIEW: This review aims to explore the different imaging modalities, such as chest radiography (CXR), computed tomography (CT), ultrasound, PET/CT scan, and MRI to describe the main features for the evaluation of the chest in COVID-19 patients with ARDS. RECENT FINDINGS: This article includes a systematic literature search, evidencing the different chest imaging modalities used in patients with ARDS from COVID-19. Literature evidences different possible approaches going from the conventional CXR and CT to the LUS, MRI, and PET/CT. SUMMARY: CT is the technique with higher sensitivity and definition for studying chest in COVID-19 patients. LUS or bedside CXR are critical in patients requiring close and repeated monitoring. Moreover, LUS and CXR reduce the radiation burden and the risk of infection compared with CT. PET/CT and MRI, especially in ARDS patients, are not usually used for diagnostic or follow-up purposes.

Proceedings from the Society of Interventional Radiology Foundation Research Consensus Panel on Artificial Intelligence in Interventional Radiology: From Code to Bedside.

Artificial intelligence (AI)-based technologies are the most rapidly growing field of innovation in healthcare with the promise to achieve substantial improvements in delivery of patient care across all disciplines of medicine. Recent advances in imaging technology along with marked expansion of readily available advanced health information, data offer a unique opportunity for interventional radiology (IR) to reinvent itself as a data-driven specialty. Additionally, the growth of AI-based applications in diagnostic imaging is expected to have downstream effects on all image-guidance modalities. Therefore, the Society of Interventional Radiology Foundation has called upon 13 key opinion leaders in the field of IR to develop research priorities for clinical applications of AI in IR. The objectives of the assembled research consensus panel were to assess the availability and understand the applicability of AI for IR, estimate current needs and clinical use cases, and assemble a list of research priorities for the development of AI in IR. Individual panel members proposed and all participants voted upon consensus statements to rank them according to their overall impact for IR. The results identified the top priorities for the IR research community and provide organizing principles for innovative academic-industrial research collaborations that will leverage both clinical expertise and cutting-edge technology to benefit patient care in IR.

Woodchuck Hepatic Anatomy and Vascular Alterations Due to Hepatocellular Carcinoma with Angiographic Atlas of the Abdomen and Pelvis.

PURPOSE: To characterize the hepatic and abdominal angiographic anatomy of woodchucks and vascular changes associated with hepatocellular carcinoma (HCC). MATERIALS AND METHODS: Twenty-nine woodchucks (23 with viral-associated HCC, 6 without) underwent multiphasic computed tomography (CT). Fourteen woodchucks (8 with HCC) also underwent diagnostic angiography. Hepatic arterial diameters were measured on the CT scans. Woodchucks were divided into 3 groups: non-tumor-bearing, largest tumor supplied by the right hepatic artery (RHA), and largest tumor supplied by the left hepatic artery (LHA). Statistical analysis with a repeated measures model was performed to determine the effects of tumor location (right, left), vessel measured (RHA, LHA), and interaction between the 2 on vessel diameter. Lobar arteries supplying HCC were compared with those that did not. RESULTS: CT anatomy and normal and variant vascular anatomy were defined. In woodchucks with HCC, LHA and RHA supplying tumors had mean diameters of 2.0 mm ± 0.3 and 1.6 mm ± 0.3 versus 1.5 mm ± 0.3 and 1.1 mm ± 0.2 for non-tumor-supplying arteries (P = .0002 and P < .0001), respectively. Lobar arteries supplying tumors were similarly ectatic. The right lateral lobe artery had the most profound increase in the mean diameter when supplying tumors, measuring 1.7 mm ± 0.1 versus 1.0 mm ± 0.1 in the non-tumor-supplying artery (P < .0001). There were no differences in the diameters of the aorta and celiac, common, and proper hepatic arteries between tumor- and non-tumor-bearing woodchucks. An angiographic atlas of the abdominal vessels was generated. CONCLUSIONS: HCC tumoral vasculature in woodchucks was ectatic compared with normal vasculature. This phenomenon recapitulates human HCC and may facilitate investigation of transcatheter and drug delivery therapies in an HCC animal model.

Angular needle tracker and stabilizer for image-guided interventions.

INTRODUCTION: Minimally invasive image-guided interventions have changed the face of procedural medicine. For these procedures, safety and efficacy depend on precise needle placement. Needle targeting devices help improve the accuracy of needle placement, but their use has not seen broad penetration. Some of these devices are costly and require major modifications to the clinical workflow. In this article, we developed a low-cost, disposable, and easy-to-use angulation tracking device, which was based on a redesigned commercial passive needle holder. MATERIAL AND METHODS: The new design provided real-time angulation information for needle tracking. In this design, two potentiometers were used as angulation sensors, and they were connected to two axes of the passive needle holder's arch structure through a 3 D-printed bridge structure. A control unit included an Arduino Pro Mini, a Bluetooth module, and two rechargeable batteries. The angulation was calculated and communicated in real time to a novel developed smartphone app, where real-time angulation information was displayed for guiding the operator to position the needle to the planned angles. RESULTS: The open-air test results showed that the average errors are 1.03° and 1.08° for left-right angulation and head-foot angulation, respectively. The animal cadaver tests revealed that the novel system had an average angular error of 3.2° and a radial distance error of 3.1 mm. CONCLUSIONS: The accuracy was comparable with some commercially available solutions. The novel and low-cost needle tracking device may find a role as part of a real-time precision approach to both planning and implementation of image-guided therapies.

Single-cell atlas of tumor cell evolution in response to therapy in hepatocellular carcinoma and intrahepatic cholangiocarcinoma.

BACKGROUND & AIMS: Intratumor molecular heterogeneity is a key feature of tumorigenesis and is linked to treatment failure and patient prognosis. Herein, we aimed to determine what drives tumor cell evolution by performing single-cell transcriptomic analysis. METHODS: We analyzed 46 hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA) biopsies from 37 patients enrolled in interventional studies at the NIH Clinical Center, with 16 biopsies collected before and after treatment from 7 patients. We developed a novel machine learning-based consensus clustering approach to track cellular states of 57,000 malignant and non-malignant cells including tumor cell transcriptome-based functional clonality analysis. We determined tumor cell relationships using RNA velocity and reverse graph embedding. We also studied longitudinal samples from 4 patients to determine tumor cellular state and its evolution. We validated our findings in bulk transcriptomic data from 488 patients with HCC and 277 patients with iCCA. RESULTS: Using transcriptomic clusters as a surrogate for functional clonality, we observed an increase in tumor cell state heterogeneity which was tightly linked to patient prognosis. Furthermore, increased functional clonality was accompanied by a polarized immune cell landscape which included an increase in pre-exhausted T cells. We found that SPP1 expression was tightly associated with tumor cell evolution and microenvironmental reprogramming. Finally, we developed a user-friendly online interface as a knowledge base for a single-cell atlas of liver cancer. CONCLUSIONS: Our study offers insight into the collective behavior of tumor cell communities in liver cancer as well as potential drivers of tumor evolution in response to therapy. LAY SUMMARY: Intratumor molecular heterogeneity is a key feature of tumorigenesis that is linked to treatment failure and patient prognosis. In this study, we present a single-cell atlas of liver tumors from patients treated with immunotherapy and describe intratumoral cell states and their hierarchical relationship. We suggest osteopontin, encoded by the gene SPP1, as a candidate regulator of tumor evolution in response to treatment.

Prognostic Features of Biochemical Recurrence of Prostate Cancer Following Radical Prostatectomy Based on Multiparametric MRI and Immunohistochemistry Analysis of MRI-guided Biopsy Specimens.

Background Although prostate MRI is routinely used for the detection and staging of localized prostate cancer, imaging-based assessment and targeted molecular sampling for risk stratification are an active area of research. Purpose To evaluate features of preoperative MRI and MRI-guided biopsy immunohistochemistry (IHC) findings associated with biochemical recurrence (BCR) of prostate cancer after surgery. Materials and Methods In this retrospective case-control study, patients underwent multiparametric MRI before MRI-guided biopsy followed by radical prostatectomy between 2008 and 2016. Lesions were retrospectively scored with the Prostate Imaging Reporting and Data System (PI-RADS) (version 2) by radiologists who were blinded to the clinical-pathologic results. The IHC staining, including stains for the ETS-related gene, phosphatase and tensin homolog, androgen receptor, prostate specific antigen, and p53, was performed with targeted biopsy specimens of the index lesion (highest suspicion at MRI and pathologic grade) and scored by pathologists who were blinded to clinical-pathologic outcomes. Cox proportional hazards regression analysis was used to evaluate associations with recurrence-free survival (RFS). Results The median RFS was 31.7 months (range, 1-101 months) for 39 patients (median age, 62 years; age range, 47-76 years) without BCR and 14.6 months (range, 1-61 months) for 40 patients (median age, 59 years; age range, 47-73 years) with BCR. MRI features that showed a significant relationship with the RFS interval included an index lesion with a PI-RADS score of 5 (hazard ratio [HR], 2.10; 95% CI: 1.05, 4.21; P = .04); index lesion burden, defined as ratio of index lesion volume to prostate volume (HR, 1.55; 95% CI: 1.2, 2.1; P = .003); and suspicion of extraprostatic extension (EPE) (HR, 2.18; 95% CI: 1.1, 4.2; P = .02). Presurgical multivariable analysis indicated that suspicion of EPE at MRI (adjusted HR, 2.19; 95% CI: 1.1, 4.3; P = .02) and p53 stain intensity (adjusted HR, 2.22; 95% CI: 1.0, 4.7; P = .04) were significantly associated with RFS. Conclusion MRI features, including Prostate Imaging Reporting and Data System score, index lesion burden, extraprostatic extension, and preoperative guided biopsy p53 immunohistochemistry stain intensity are associated with biochemical relapse of prostate cancer after surgery. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Costa in this issue.