Association of Baseline Magnetic Resonance Imaging Prostate Imaging Reporting and Data System Score With Prostate Cancer Active Surveillance Early Biopsy Reclassification: Data From the Michigan Urological Surgery Improvement Collaborative (MUSIC).

PURPOSE: The purpose of our study was to evaluate the association of baseline MRI Prostate Imaging Reporting and Data System (PI-RADS) score with biopsy reclassification in a multicenter active surveillance (AS) cohort. MATERIALS AND METHODS: We identified men in the Michigan Urological Surgery Improvement Collaborative registry (46 hospital-based/academic/private practice urology groups) with National Comprehensive Cancer Network (NCCN) low-risk and favorable intermediate-risk prostate cancer who underwent MRI within 6 months before or after initial biopsy and enrolled in AS from June 2016 to January 2021. The primary objective was to determine the association of baseline MRI PI-RADS score (≥4 lesion) with reclassification to high-grade prostate cancer (≥grade group 3) on surveillance biopsy. Multivariable Cox proportional hazards regression models were constructed and adjusted for pathologic, MRI, and clinical/biopsy factors, with landmark time of 6 months from diagnostic biopsy. We included an interaction term between PI-RADS score and NCCN group in the Cox model. RESULTS: A total of 1491 men were included with median age 64 years (IQR: 59-69) with median follow-up 11.0 months (IQR: 6.0-23.0) after landmark. Baseline PI-RADS ≥ 4 lesion was associated with an increased hazard of biopsy reclassification (HR: 2.3 [95% CI: 1.6-3.2], P < .001), along with grade group 2 vs 1 (HR: 2.5 [95% CI: 1.7-3.7], P < .001), and increasing age (per 10 years; HR: 1.8 [95% CI: 1.4-2.4], P < .001). The interaction between NCCN risk group with MRI findings was not significant (P = .7). CONCLUSIONS: In this multicenter cohort study of real-world data, baseline MRI PI-RADS score was significantly associated with early biopsy reclassification in men undergoing AS with NCCN low- or favorable intermediate-risk prostate cancer.

Prostatic Urethral Length on MRI Potentially Predicts Late Genitourinary Toxicity After Prostate Cancer Radiation.

RATIONALE AND OBJECTIVES: The purpose of our study was to evaluate pretreatment prostate quantitative magnetic resonance imaging (MRI) measurements and clinical characteristics in predicting genitourinary (GU) toxicity after radiotherapy (RT) for prostate cancer. MATERIALS AND METHODS: In this single-institution retrospective cohort study, we evaluated patients with prostate adenocarcinoma who underwent MRI within 6 months before completing definitive RT and follow-up information in our GU toxicity database from June 2016 to February 2023. MRI measurements included quantitative urethra, prostate, and bladder measurements. GU toxicity was physician-scored using the Common Terminology Criteria for Adverse Events (CTCAE v4.0) with acute toxicity defined as ≤180 days and late defined as >180 days. Multivariable logistic regression model was constructed for grade ≥2 acute toxicity and Cox proportional hazards regression for late toxicity, adjusted for clinical factors and RT method. RESULTS: A total of 361 men (median age 68 years, interquartile range [IQR] 62-73) were included; 14.4% (50/347) men experienced grade ≥2 acute toxicity. Brachytherapy (odds ratio [OR]: 2.9, 95% confidence interval [CI]: 1.5-5.8), P < 0.01) was associated with increased odds of acute GU toxicity, and longer MUL (OR: 0.41 [95%CI: 0.18-0.92], P = 0.03) with decreased odds. Median follow-up for late toxicity was 15.0 months (IQR: 9.0-28.0) with approximately 88.7% and 72.0% patients free of toxicity at 1 and 3 years, respectively. Only longer prostatic urethral length (hazard ratio [HR]: 1.6, 95%CI: 1.2-2.1, P < 0.01) was associated with increased risk of late GU toxicity, notably urinary frequency/urgency symptoms (HR: 1.7 [95%CI: 1.3-2.3], P < 0.01). CONCLUSION: Longer prostatic urethral length measured on prostate MRI is independently associated with higher risk of developing late grade ≥2 GU toxicity after radiation therapy for prostate cancer. This pretreatment metric may be potentially valuable in risk-stratification models for quality of life following prostate RT.

Impact of the bladder detrusor muscular ring on lower urinary tract symptoms due to benign prostatic hyperplasia: A quantitative MRI analysis.

BACKGROUND: The etiology of lower urinary tract symptoms secondary to benign prostatic hyperplasia (LUTS/BPH) remains uncertain. OBJECTIVE: The purpose of our study was to quantitatively analyze anatomic characteristics on magnetic resonance imaging (MRI) to assess novel independent factors for symptoms. METHODS: This retrospective single-institution study evaluated treatment-naïve men who underwent prostate MRI within 3 months of international prostate symptom score (IPSS) scoring from June 2021 to February 2022. Factors measured on MRI included: size of the detrusor muscular ring (DMR) surrounding the bladder outlet, central gland (CG) mean apparent diffusion coefficient (ADC), levator hiatus (LH) volume, intrapelvic volume, intravesicular prostate protrusion (IPP) volume, CG volume, peripheral zone (PZ) volume, prostate urethra angle (PUA), and PZ background ordinal score. Multivariable logistic regression and receiver operating characteristic analysis were used to analyze factors for moderate/severe (IPSS ≥ 8) and severe LUTS/BPH (IPSS ≥ 20). RESULTS: A total of 303 men (mean age: 66.1 [SD: 8.1]) were included: 154 demonstrated moderate or severe symptoms with 28 severe and 149 with asymptomatic/mild symptoms. Increasing age [p = 0.02; odds ratio (OR): 1.05 (1.01-1.08)], PUA [p = 0.02; OR: 1.05 (1.01-1.09)], LH volume [p = 0.04; OR: 1.02 (1.00-1.05)], and DMR size measured as diameter [p < 0.001; OR: 5.0 (3.01-8.38)] or area [p < 0.001; OR: 1.92 (1.47-2.49)] were significantly independently associated with moderate/severe symptoms, with BMI [p = 0.02; OR: 0.93 (0.88-0.99)] inversely related. For every one cm increase in DMR diameter, patients had approximately five times the odds for moderate/severe symptoms. Increasing DMR size [diameter p < 0.001; OR: 2.74 (1.76-4.27) or area p < 0.001; OR: 1.37 (1.18-1.58)] was independently associated with severe symptoms. Optimal criterion cutoff of DMR diameter for moderate/severe symptoms was 1.2 cm [sensitivity: 77.3; specificity: 71.8; AUC: 0.80 (0.75-0.84)]. Inter-reader reliability was excellent for DMR diameter [ICC = 0.92 (0.90-0.94)]. CONCLUSION: Expansion of the DMR surrounding the bladder outlet is a novel anatomic factor independently associated with moderate and severe LUTS/BPH, taking into account prostate volumes, including quantified IPP volume, which were unrelated. Detrusor ring diameter, easily and reliably measured on routine prostate MRI, may relate to detrusor dysfunction from chronic stretching of this histologically distinct smooth muscle around the bladder neck.

Erratum: Author Correction: PENet-a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging.

[This corrects the article DOI: 10.1038/s41746-020-0266-y.].

PENet-a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging.

Pulmonary embolism (PE) is a life-threatening clinical problem and computed tomography pulmonary angiography (CTPA) is the gold standard for diagnosis. Prompt diagnosis and immediate treatment are critical to avoid high morbidity and mortality rates, yet PE remains among the diagnoses most frequently missed or delayed. In this study, we developed a deep learning model-PENet, to automatically detect PE on volumetric CTPA scans as an end-to-end solution for this purpose. The PENet is a 77-layer 3D convolutional neural network (CNN) pretrained on the Kinetics-600 dataset and fine-tuned on a retrospective CTPA dataset collected from a single academic institution. The PENet model performance was evaluated in detecting PE on data from two different institutions: one as a hold-out dataset from the same institution as the training data and a second collected from an external institution to evaluate model generalizability to an unrelated population dataset. PENet achieved an AUROC of 0.84 [0.82-0.87] on detecting PE on the hold out internal test set and 0.85 [0.81-0.88] on external dataset. PENet also outperformed current state-of-the-art 3D CNN models. The results represent successful application of an end-to-end 3D CNN model for the complex task of PE diagnosis without requiring computationally intensive and time consuming preprocessing and demonstrates sustained performance on data from an external institution. Our model could be applied as a triage tool to automatically identify clinically important PEs allowing for prioritization for diagnostic radiology interpretation and improved care pathways via more efficient diagnosis.

Cytokine induced phenotypic and epigenetic signatures are key to establishing specific macrophage phenotypes.

Macrophages (MΦ) play an essential role in innate immune responses and can either display a pro-inflammatory, classically activated phenotype (M1) or undergo an alternative activation program (M2) promoting immune regulation. M-CSF is used to differentiate monocytes into MΦ and IFN-γ or IL-4+IL-13 to further polarize these cells towards M1 or M2, respectively. Recently, differentiation using only GM-CSF or M-CSF has been described to induce a M1- or M2-like phenotype, respectively. In this study, we combined both approaches by differentiating human MΦ in GM-CSF or M-CSF followed by polarization with either IFN-γ or IL-4+IL-13. We describe the phenotypic differences between CD14(hi) CD163(hi) CD206(int) FOLR2-expressing M-CSF MΦ and CD14(lo) CD163(lo) CD206(hi) GM-CSF MΦ but show that both macrophage populations reacted similarly to further polarization with IFN-γ or IL-4+IL-13 with up- and down-regulation of common M1 and M2 marker genes. We also show that high expression of the mannose receptor (CD206), a marker of alternative activation, is a distinct feature of GM-CSF MΦ. Changes of the chromatin structure carried out by chromatin modification enzymes (CME) have been shown to regulate myeloid differentiation. We analyzed the expression patterns of CME during MΦ polarization and show that M1 up-regulate the histone methyltransferase MLL and demethylase KDM6B, while resting and M2 MΦ were characterized by DNA methyltransferases and histone deacetylases. We demonstrate that MLL regulates CXCL10 expression and that this effect could be abrogated using a MLL-Menin inhibitor. Taken together we describe the distinct phenotypic differences of GM-CSF or M-CSF MΦ and demonstrate that MΦ polarization is regulated by specific epigenetic mechanisms. In addition, we describe a novel role for MLL as marker for classical activation. Our findings provide new insights into MΦ polarization that could be helpful to distinguish MΦ activation states.