Cardiovascular hemodynamics in mice with tumor necrosis factor receptor-associated factor 2 mediated cytoprotection in the heart.

Introduction: Many studies in mice have demonstrated that cardiac-specific innate immune signaling pathways can be reprogrammed to modulate inflammation in response to myocardial injury and improve outcomes. While the echocardiography standard parameters of left ventricular (LV) ejection fraction, fractional shortening, end-diastolic diameter, and others are used to assess cardiac function, their dependency on loading conditions somewhat limits their utility in completely reflecting the contractile function and global cardiovascular efficiency of the heart. A true measure of global cardiovascular efficiency should include the interaction between the ventricle and the aorta (ventricular-vascular coupling, VVC) as well as measures of aortic impedance and pulse wave velocity. Methods: We measured cardiac Doppler velocities, blood pressures, along with VVC, aortic impedance, and pulse wave velocity to evaluate global cardiac function in a mouse model of cardiac-restricted low levels of TRAF2 overexpression that conferred cytoprotection in the heart. Results: While previous studies reported that response to myocardial infarction and reperfusion was improved in the TRAF2 overexpressed mice, we found that TRAF2 mice had significantly lower cardiac systolic velocities and accelerations, diastolic atrial velocity, aortic pressures, rate-pressure product, LV contractility and relaxation, and stroke work when compared to littermate control mice. Also, we found significantly longer aortic ejection time, isovolumic contraction and relaxation times, and significantly higher mitral early/atrial ratio, myocardial performance index, and ventricular vascular coupling in the TRAF2 overexpression mice compared to their littermate controls. We found no significant differences in the aortic impedance and pulse wave velocity. Discussion: While the reported tolerance to ischemic insults in TRAF2 overexpression mice may suggest enhanced cardiac reserve, our results indicate diminished cardiac function in these mice.

The use of Lutetium-177 PSMA radioligand therapy with high dose rate brachytherapy for locally recurrent prostate cancer after previous definitive radiation therapy: a randomized, single-institution, phase I/II study (ROADSTER).

BACKGROUND: Isolated local failure (ILF) can occur in patients who initially receive definitive radiation therapy for prostate cancer. Salvage therapy for ILF includes high dose rate (HDR) brachytherapy. Prostate Specific Membrane Antigen (PSMA) Positron Emission Tomography (PET) can accurately detect ILF and can exclude extraprostatic disease. Lutetium-177 PSMA Radioligand Therapy (RLT) is a novel treatment for prostate cancer that can target prostate cancer accurately, while sparing radiation dose to normal tissues. METHODS: ROADSTER is a phase I/II randomized, single-institution study. Patients with an ILF of prostate cancer after definitive initial radiation therapy are eligible. The ILF will be confirmed with biopsy, magnetic resonance imaging (MRI) and PSMA PET. Patients will be randomized between HDR brachytherapy in two fractions (a standard of care salvage treatment at our institution) (cohort 1) or one treatment of intravenous Lutetium-177 PSMA RLT, followed by one fraction of HDR brachytherapy (cohort 2). The primary endpoints for the phase I portion of the study (n = 12) will be feasibility, defined as 10 or more patients completing the study protocol within 24 months of study activation; and safety, defined as zero or one patients in cohort 2 experiencing grade 3 or higher toxicity in the first 6 months post-treatment. If feasibility and safety are achieved, the study will expand to a phase II study (n = 30 total) where preliminary efficacy data will be evaluated. Secondary endpoints include changes in prostate specific antigen levels, acute toxicity, changes in quality of life, and changes in translational biomarkers. Translational endpoints will include interrogation of blood, urine, and tissue for markers of DNA damage and immune activation with each treatment. DISCUSSION: ROADSTER explores a novel salvage therapy for ILF after primary radiotherapy with combined Lutetium-177 PSMA RLT and HDR brachytherapy. The randomized phase I/II design will provide a contemporaneous patient population treated with HDR alone to facilitate assessment of feasibility, tolerability, and biologic effects of this novel therapy. TRIAL REGISTRATION: NCT05230251 (ClinicalTrials.gov).

Validation of a surface-based deformable MRI-3D ultrasound image registration algorithm toward clinical implementation for interstitial prostate brachytherapy.

PURPOSE: The purpose of this study was to evaluate and clinically implement a deformable surface-based magnetic resonance imaging (MRI) to three-dimensional ultrasound (US) image registration algorithm for prostate brachytherapy (BT) with the aim to reduce operator dependence and facilitate dose escalation to an MRI-defined target. METHODS AND MATERIALS: Our surface-based deformable image registration (DIR) algorithm first translates and scales to align the US- and MR-defined prostate surfaces, followed by deformation of the MR-defined prostate surface to match the US-defined prostate surface. The algorithm performance was assessed in a phantom using three deformation levels, followed by validation in three retrospective high-dose-rate BT clinical cases. For comparison, manual rigid registration and cognitive fusion by physician were also employed. Registration accuracy was assessed using the Dice similarity coefficient (DSC) and target registration error (TRE) for embedded spherical landmarks. The algorithm was then implemented intraoperatively in a prospective clinical case. RESULTS: In the phantom, our DIR algorithm demonstrated a mean DSC and TRE of 0.74 ± 0.08 and 0.94 ± 0.49 mm, respectively, significantly improving the performance compared to manual rigid registration with 0.64 ± 0.16 and 1.88 ± 1.24 mm, respectively. Clinical results demonstrated reduced variability compared to the current standard of cognitive fusion by physicians. CONCLUSIONS: We successfully validated a DIR algorithm allowing for translation of MR-defined target and organ-at-risk contours into the intraoperative environment. Prospective clinical implementation demonstrated the intraoperative feasibility of our algorithm, facilitating targeted biopsies and dose escalation to the MR-defined lesion. This method provides the potential to standardize the registration procedure between physicians, reducing operator dependence.

Prostate cancer classification using radiomics and machine learning on mp-MRI validated using co-registered histology.

BACKGROUND: Multi-parametric magnetic resonance imaging (mp-MRI) is emerging as a useful tool for prostate cancer (PCa) detection but currently has unaddressed limitations. Computer aided diagnosis (CAD) systems have been developed to address these needs, but many approaches used to generate and validate the models have inherent biases. METHOD: All clinically significant PCa on histology was mapped to mp-MRI using a previously validated registration algorithm. Shape and size matched non-PCa regions were selected using a proposed sampling algorithm to eliminate biases towards shape and size. Further analysis was performed to assess biases regarding inter-zonal variability. RESULTS: A 5-feature Naïve-Bayes classifier produced an area under the receiver operating characteristic curve (AUC) of 0.80 validated using leave-one-patient-out cross-validation. As mean inter-class area mismatch increased, median AUC trended towards positively biasing classifiers to producing higher AUCs. Classifiers were invariant to differences in shape between PCa and non-PCa lesions (AUC: 0.82 vs 0.82). Performance for models trained and tested only in the peripheral zone was found to be lower than in the central gland (AUC: 0.75 vs 0.95). CONCLUSION: We developed a radiomics based machine learning system to classify PCa vs non-PCa tissue on mp-MRI validated on accurately co-registered mid-gland histology with a measured target registration error. Potential biases involved in model development were interrogated to provide considerations for future work in this area.

Targeting prostate lesions on multiparametric MRI with HDR brachytherapy: Optimal planning margins determined using whole-mount digital histology.

PURPOSE: Multiparametric magnetic resonance imaging (mpMRI) has demonstrated the ability to localize intraprostatic lesions. It is our goal to determine how to optimally target the underlying histopathological cancer within the setting of high-dose-rate brachytherapy (HDR-BT). METHODS AND MATERIALS: Ten prostatectomy patients had pathologist-annotated mid-gland histology registered to pre-procedural mpMRI, which were interpreted by four different observers. Simulated HDR-BT plans with realistic catheter placements were generated by registering the mpMRI lesions and corresponding histology annotations to previously performed clinical HDR-BT implants. Inverse treatment planning was used to generate treatment plans that treated the entire gland to a single dose of 15 Gy, as well as focally targeted plans that aimed to escalate dose to the mpMRI lesions to 20.25 Gy. Three margins to the lesion were explored: 0 mm, 1 mm, and 2 mm. The analysis compared the dose that would have been delivered to the corresponding histologically-defined cancer with the different treatment planning techniques. RESULTS: mpMRI-targeted plans delivered a significantly higher dose to the histologically-defined cancer (p < 0.001), in comparison to the standard treatment plans. Additionally, adding a 1 mm margin resulted in significantly higher D98, and D90 to the histologically-defined cancer in comparison to the 0 mm margin targeted plans (p = 0.019 & p = 0.0026). There was no significant difference between plans using 1 mm and 2 mm margins. CONCLUSIONS: Adding a 1 mm margin to intraprostatic mpMRI lesions significantly increased the dose to histologically-defined cancer, in comparison applying no margin. No significant effect was observed by further expanding the margins.

Simple prostatectomy using the open and robotic approaches for lower urinary tract symptoms: A retrospective, case-control series.

INTRODUCTION: We aimed to assess the outcome of our series of simple prostatectomy at our institution using the open simple prostatectomy (OSP) and robotic-assisted simple prostatectomy (RASP) approaches. METHODS: We conducted a retrospective chart review of men who underwent OSP and RASP at Western University, in London, ON. Preoperative, intraoperative, and postoperative data were collected and analyzed. RESULTS: From 2012-2020, 29 men underwent a simple prostatectomy at our institution. Eight patients underwent an OSP and 21 patients underwent a RASP. The median age was 69 years. Preoperative median prostate volume was 153 cm³ (range 80-432). The surgical indications were failed medical treatment, urinary retention, hydronephrosis, cystolithiasis, and recurrent hematuria. The median operative time was 137.5 minutes in OSP and 185 minutes in RASP (p=0.04). Median estimated blood loss was 2300 ml (range 600-4000) and 100 ml (range 50-400) in the open and robotic procedures, respectively (p=0.4). The mean length of hospital stay was shorter in the RASP group, one day vs. three days (z=4.152, p&lt;0.005). Perioperative complication rates were significantly lower in the group undergoing RASP, with no complications recorded in this group (p=0.004). Both groups demonstrated excellent functional results, with most patients reporting complete urinary continence (p=0.8). CONCLUSIONS: We report very good perioperative outcomes, with a minimal risk profile and excellent functional results, leading to marked improvement in patients' symptoms at followup after both the OSP and RASP approaches. RASP was associated with a shorter length of hospital stay, decreased blood loss, and a lower complication rate.

Short-duration dynamic [18F]DCFPyL PET and CT perfusion imaging to localize dominant intraprostatic lesions in prostate cancer: validation against digital histopathology and comparison to [18F]DCFPyL PET/MR at 120 minutes.

PURPOSE: Localized prostate cancer (PCa) in patients is characterized by a dominant focus in the gland (dominant intraprostatic lesion, DIL). Accurate DIL identification may enable more accurate diagnosis and therapy through more precise targeting of biopsy, radiotherapy and focal ablative therapies. The goal of this study is to validate the performance of [18F]DCFPyL PET and CT perfusion (CTP) for detecting and localizing DIL against digital histopathological images. METHODS: Multi-modality image sets: in vivo T2-weighted (T2w)-MRI, 22-min dynamic [18F]DCFPyL PET/CT, CTP, and 2-h post-injection PET/MR were acquired in patients prior to radical prostatectomy. The explanted gland with implanted fiducial markers was imaged with T2w-MRI. All images were co-registered to the pathologist-annotated digital images of whole-mount mid-gland histology sections using fiducial markers and anatomical landmarks. Regions of interest encompassing DIL and non-DIL tissue were drawn on the digital histopathological images and superimposed on PET and CTP parametric maps. Logistic regression with backward elimination of parameters was used to select the most sensitive parameter set to distinguish DIL from non-DIL voxels. Leave-one-patient-out cross-validation was performed to determine diagnostic performance. RESULTS: [18F]DCFPyL PET and CTP parametric maps of 15 patients were analyzed. SUVLate and a model combining Ki and k4 of [18F]DCFPyL achieved the most accurate performance distinguishing DIL from non-DIL voxels. Both detection models achieved an AUC of 0.90 and an error rate of < 10%. Compared to digital histopathology, the detected DILs had a mean dice similarity coefficient of 0.8 for the Ki and k4 model and 0.7 for SUVLate. CONCLUSIONS: We have validated using co-registered digital histopathological images that parameters from kinetic analysis of 22-min dynamic [18F]DCFPyL PET can accurately localize DILs in PCa for targeting of biopsy, radiotherapy, and focal ablative therapies. Short-duration dynamic [18F]DCFPyL PET was not inferior to SUVLate in this diagnostic task. CLINICAL TRIAL REGISTRATION NUMBER: NCT04009174 (ClinicalTrials.gov).

Prostate specific membrane antigen positron emission tomography for lesion-directed high-dose-rate brachytherapy dose escalation.

BACKGROUND AND PURPOSE: Prostate specific membrane antigen positron emission tomography imaging (PSMA-PET) has demonstrated potential for intra-prostatic lesion localization. We leveraged our existing database of co-registered PSMA-PET imaging with cross sectional digitized pathology to model dose coverage of histologically-defined prostate cancer when tailoring brachytherapy dose escalation based on PSMA-PET imaging. MATERIALS AND METHODS: Using a previously-developed automated approach, we created segmentation volumes delineating underlying dominant intraprostatic lesions for ten men with co-registered pathology-imaging datasets. To simulate realistic high-dose-rate brachytherapy (HDR-BT) treatments, we registered the PSMA-PET-defined segmentation volumes and underlying cancer to 3D trans-rectal ultrasound images of HDR-BT cases where 15 Gray (Gy) was delivered. We applied dose/volume optimization to focally target the dominant intraprostatic lesion identified on PSMA-PET. We then compared histopathology dose for all high-grade cancer within whole-gland treatment plans versus PSMA-PET-targeted plans. Histopathology dose was analyzed for all clinically significant cancer with a Gleason score of 7or greater. RESULTS: The standard whole-gland plans achieved a median [interquartile range] D98 of 15.2 [13.8-16.4] Gy to the histologically-defined cancer, while the targeted plans achieved a significantly higher D98 of 16.5 [15.0-19.0] Gy (p = 0.007). CONCLUSION: This study is the first to use digital histology to confirm the effectiveness of PSMA-PET HDR-BT dose escalation using automatically generated contours. Based on the findings of this study, PSMA-PET lesion dose escalation can lead to increased dose to the ground truth histologically defined cancer.

Supervised Exercise Immediately After Bariatric Surgery: the Study Protocol of the EFIBAR Randomized Controlled Trial.

BACKGROUND: Previous studies have investigated weight loss caused by exercise following bariatric surgery. However, in most cases, the training program is poorly reported; the exercise type, volume, and intensity are briefly mentioned; and the sample size, selection criteria, and follow-up time vary greatly across studies. PURPOSE: The EFIBAR study aims to investigate over 1 year the effects of a 16-week supervised exercise program, initiated immediately after bariatric surgery, on weight loss (primary outcome), body composition, cardiometabolic risk, physical fitness, and quality of life in patients with severe/extreme obesity. MATERIAL AND METHODS: The EFIBAR study is a parallel-group, superiority, randomized controlled trial (RCT), comprising 80 surgery patients. Half of the participants, randomly selected, perform a 16-week supervised exercise program, including both strength and aerobic training, starting immediately after the surgery (7-14 days). For each participant, all primary and secondary outcomes are measured at three different time points: (i) before the surgery, (ii) after the intervention (≈4 months), and (iii) 1 year after the surgery. CONCLUSION: The EFIBAR study will provide new insights into the multidimensional benefits of exercise in adults with severe/extreme obesity following bariatric surgery. TRIAL REGISTRATION: EFIBAR randomized controlled trial was prospectively registered at Clinicaltrials.gov (NCT03497546) on April 13, 2018.

Usefulness of ultrasound in sub-Saharan patients with a serological diagnosis of schistosomiasis.

OBJECTIVE: To evaluate the usefulness of ultrasound examination in patients with just a serological diagnosis of schistosomiasis but no other evidence of active infection. METHODS: 346 sub-Saharan patients with possible schistosomiasis that presented at a Tropical Medicine Unit between 2008 and 2019 were retrospectively selected. Possible schistosomiasis was considered in those patients with a positive serology for schistosomasis in the absence of direct microbiological isolates, hematuria and/or eosinophilia. Data from ultrasound examinations before and after treatment with praziquantel were collected and categorized following the World Health Organization-Niamey score to standardize the use of ultrasonography for the assessment of schistosomiasis-related morbidity. RESULTS: Ultrasound examinations were abnormal in only ten patients (2.89%). Main findings were focal thickening of the bladder wall (n = 6), ureteral dilatation (n = 3) and grade I hydronephrosis (n = 1). No malignant lesions, hepatic lesions nor hepatobiliary related disorders were found. After treatment, the S. haematobium global score (5 vs 3.4, p = 0.06) and the urinary bladder score (2 vs 1, p = 0.059) showed a trend towards improvement after treatment. In three patients the score after treatment dropped to 0, and in another three it remained the same although with signs of improvement. No worsening of the score was observed in any case. CONCLUSION: For those patients with a diagnosis of schistosomiasis based solely in a positive serology, the ultrasound examination could safely be spared due to the low prevalence of pathological findings and its response to treatment anyway.

A multiobserver study investigating the effectiveness of prostatic multiparametric magnetic resonance imaging to dose escalate corresponding histologic lesions using high-dose-rate brachytherapy.

PURPOSE: Using multiparametric MRI data and the pathologic data from radical prostatectomy specimens, we simulated the treatment planning of dose-escalated high-dose-rate brachytherapy (HDR-BT) to the Multiparametric MRI dominant intraprostatic lesion (mpMRI-DIL) to compare the dose potentially delivered to the pathologically confirmed locations of the high-grade component of the cancer. METHODS AND MATERIALS: Pathologist-annotated prostatectomy midgland histology sections from 12 patients were registered to preprostatectomy mpMRI scans that were interpreted by four radiologists. To simulate realistic HDR-BT, we registered each observer's mpMRI-DILs and corresponding histology to two transrectal ultrasound images of other HDR-BT patients with a 15-Gy whole-gland prescription. We used clinical inverse planning to escalate the mpMRI-DILs to 20.25 Gy. We compared the dose that the histopathology would have received if treated with standard treatment plans to the dose mpMRI-targeting would have achieved. The histopathology was grouped as high-grade cancer (any Gleason Grade 4 or 5) and low-grade cancer (only Gleason Grade 3). RESULTS: 212 mpMRI-targeted HDR-BT plans were analyzed. For high-grade histology, the mpMRI-targeted plans achieved significantly higher median [IQR] D98 and D90 values of 18.2 [16.7-19.5] Gy and 19.4 [17.8-20.9] Gy, respectively, in comparison with the standard plans (p = 0.01 and p = 0.003). For low-grade histology, the targeted treatment plans would have resulted in a significantly higher median D90 of 17.0 [16.1-18.4] Gy in comparison with standard plans (p = 0.015); the median D98 was not significantly higher (p = 0.2). CONCLUSIONS: In this retrospective pilot study of 12 patients, mpMRI-based dose escalation led to increased dose to high-grade, but not low-grade, cancer. In our data set, different observers and mpMRI sequences had no substantial effect on dose to histologic cancer.

Stochastic Sequential Modeling: Toward Improved Prostate Cancer Diagnosis Through Temporal-Ultrasound.

Prostate cancer (PCa) is a common, serious form of cancer in men that is still prevalent despite ongoing developments in diagnostic oncology. Current detection methods lead to high rates of inaccurate diagnosis. We present a method to directly model and exploit temporal aspects of temporal enhanced ultrasound (TeUS) for tissue characterization, which improves malignancy prediction. We employ a probabilistic-temporal framework, namely, hidden Markov models (HMMs), for modeling TeUS data obtained from PCa patients. We distinguish malignant from benign tissue by comparing the respective log-likelihood estimates generated by the HMMs. We analyze 1100 TeUS signals acquired from 12 patients. Our results show improved malignancy identification compared to previous results, demonstrating over 85% accuracy and AUC of 0.95. Incorporating temporal information directly into the models leads to improved tissue differentiation in PCa. We expect our method to generalize and be applied to other types of cancer in which temporal-ultrasound can be recorded.

Emerging roles of Sox6 in the renal and cardiovascular system.

The function of Sex-determining Region Y (SRY)-related high-mobility-group box (Sox) family of transcription factors in cell fate decisions during embryonic development are well-established. Accumulating evidence indicates that the Sox family of transcription factors are fundamental in adult tissue homeostasis, regeneration, and physiology. The SoxD subfamily of genes are expressed in various cell types of different organs during embryogenesis and adulthood and have been involved in cell-fate determination, cellular proliferation and survival, differentiation, and terminal maturation in a number of cell lineages. The dysregulation in the function of SoxD proteins (i.e. Sox5, Sox6, Sox13, and Sox23) have been implicated in different disease conditions such as chondrodysplasia, cancer, diabetes, hypertension, autoimmune diseases, osteoarthritis among others. In this minireview, we present recent developments related to the transcription factor Sox6, which is involved in a number of diseases such as diabetic nephropathy, adipogenesis, cardiomyopathy, inflammatory bowel disease, and cancer. Sox6 has been implicated in the regulation of renin expression and JG cell recruitment in mice during sodium depletion and dehydration. We provide a current perspective of Sox6 research developments in last five years, and the implications of Sox6 functions in cardiovascular physiology and disease conditions.

A Modified Two Kidney One Clip Mouse Model of Renin Regulation in Renal Artery Stenosis.

Renal artery stenosis is a common condition in patients with coronary or peripheral vascular disease where the renin angiotensin aldosterone system (RAAS) is overactivated. In this context, there is a narrowing of the renal arteries that stimulate an increase in the expression and release of renin, the rate-limiting protease in RAAS. The resulting rise in renin expression is a known driver of renovascular hypertension, frequently associated with kidney injury and end organ damage. Thus, there is a great interest in developing novel treatments for this condition. The molecular and cellular mechanism of renin control in renal artery stenosis is not fully understood and warrants further investigation. To induce renal artery stenosis in mice, a modified 2 kidney 1 clip (2K1C) Goldblatt mouse model was developed. The right kidney was stenosed in wild type mice and sham operated mice were used as control. After renal artery stenosis, we determined renin expression and kidney injury. Kidneys were harvested, and fresh cortices were used to determine protein and mRNA expression of renin. This animal model is reproducible and can be used to study pathophysiological responses, molecular and cellular pathways involved in renovascular hypertension and kidney injury.

Correction to: Stochastic Sequential Modeling: Toward Improved Prostate Cancer Diagnosis Through Temporal-Ultrasound.

The authors have noted an omission in the original acknowledgements. The correct acknowledgements are as follows: Acknowledgements: This work was partially supported by Grants from NSERC Discovery to Hagit Shatkay and Parvin Mousavi, NSERC and CIHR CHRP to Parvin Mousavi and NIH R01 LM012527, NIH U54 GM104941, NSF IIS EAGER #1650851 & NSF HDR #1940080 to Hagit Shatkay.

Histologic validation of auto-contoured dominant intraprostatic lesions on [18F] DCFPyL PSMA-PET imaging.

BACKGROUND: PSMA-PET1 has shown good concordance with histology, but there is a need to investigate the ability of PSMA-PET to delineate DIL2 boundaries for guided biopsy and focal therapy planning. OBJECTIVE: To determine threshold and margin combinations that satisfy the following criteria: ≥95% sensitivity with max specificity and ≥95% specificity with max sensitivity. DESIGN, SETTING AND PARTICIPANTS: We registered pathologist-annotated whole-mount mid-gland prostatectomy histology sections cut in 4.4 mm intervals from 12 patients to pre-surgical PSMA-PET/MRI by mapping histology to ex-vivo imaging to in-vivo imaging. We generated PET-derived tumor volumes using boundaries defined by thresholded PET volumes from 1-100% of SUV3max in 1% intervals. At each interval, we applied margins of 0-30 voxels in one voxel increments, giving 3000 volumes/patient. OUTCOME MEASUREMENTS: Mean and standard deviation of sensitivity and specificity for cancer detection within the 2D oblique histologic planes that intersected with the 3D PET volume for each patient. RESULTS AND LIMITATIONS: A threshold of 67% SUV max with an 8.4 mm margin achieved a (mean ± std.) sensitivity of 95.0 ± 7.8% and specificity of 76.4 ± 14.7%. A threshold of 81% SUV max with a 5.1 mm margin achieved sensitivity of 65.1 ± 28.4% and specificity of 95.1 ± 5.2%. CONCLUSIONS: Preliminary evidence of thresholding and margin expansion of PSMA-PET images targeted at DILs validated with histopathology demonstrated excellent mean sensitivity and specificity in the setting of focal therapy/boosting and guided biopsy. These parameters can be used in a larger validation study supporting clinical translation.

Automatic cancer detection on digital histopathology images of mid-gland radical prostatectomy specimens.

Purpose: Automatic cancer detection on radical prostatectomy (RP) sections facilitates graphical and quantitative surgical pathology reporting, which can potentially benefit postsurgery follow-up care and treatment planning. It can also support imaging validation studies using a histologic reference standard and pathology research studies. This problem is challenging due to the large sizes of digital histopathology whole-mount whole-slide images (WSIs) of RP sections and staining variability across different WSIs. Approach: We proposed a calibration-free adaptive thresholding algorithm, which compensates for staining variability and yields consistent tissue component maps (TCMs) of the nuclei, lumina, and other tissues. We used and compared three machine learning methods for classifying each cancer versus noncancer region of interest (ROI) throughout each WSI: (1) conventional machine learning methods and 14 texture features extracted from TCMs, (2) transfer learning with pretrained AlexNet fine-tuned by TCM ROIs, and (3) transfer learning with pretrained AlexNet fine-tuned with raw image ROIs. Results: The three methods yielded areas under the receiver operating characteristic curve of 0.96, 0.98, and 0.98, respectively, in leave-one-patient-out cross validation using 1.3 million ROIs from 286 mid-gland whole-mount WSIs from 68 patients. Conclusion: Transfer learning with the use of TCMs demonstrated state-of-the-art overall performance and is more stable with respect to sample size across different tissue types. For the tissue types involving Gleason 5 (most aggressive) cancer, it achieved the best performance compared to the other tested methods. This tool can be translated to clinical workflow to assist graphical and quantitative pathology reporting for surgical specimens upon further multicenter validation.

Histologic tissue components provide major cues for machine learning-based prostate cancer detection and grading on prostatectomy specimens.

Automatically detecting and grading cancerous regions on radical prostatectomy (RP) sections facilitates graphical and quantitative pathology reporting, potentially benefitting post-surgery prognosis, recurrence prediction, and treatment planning after RP. Promising results for detecting and grading prostate cancer on digital histopathology images have been reported using machine learning techniques. However, the importance and applicability of those methods have not been fully investigated. We computed three-class tissue component maps (TCMs) from the images, where each pixel was labeled as nuclei, lumina, or other. We applied seven different machine learning approaches: three non-deep learning classifiers with features extracted from TCMs, and four deep learning, using transfer learning with the 1) TCMs, 2) nuclei maps, 3) lumina maps, and 4) raw images for cancer detection and grading on whole-mount RP tissue sections. We performed leave-one-patient-out cross-validation against expert annotations using 286 whole-slide images from 68 patients. For both cancer detection and grading, transfer learning using TCMs performed best. Transfer learning using nuclei maps yielded slightly inferior overall performance, but the best performance for classifying higher-grade cancer. This suggests that 3-class TCMs provide the major cues for cancer detection and grading primarily using nucleus features, which are the most important information for identifying higher-grade cancer.