Differences in Gut Microbiota Profiles and Microbiota Steroid Hormone Biosynthesis in Men with and Without Prostate Cancer

Background

Although prostate cancer (PCa) is the most common cancer in men in Western countries, there is significant variability in geographical incidence. This might result from genetic factors, discrepancies in screening policies, or differences in lifestyle. Gut microbiota has recently been associated with cancer progression, but its role in PCa is unclear.

Objective

Characterization of the gut microbiota and its functions associated with PCa.

Design setting and participants

In a prospective multicenter clinical trial (NCT02241122), the gut microbiota profiles of 181 men with a clinical suspicion of PCa were assessed utilizing 16S rRNA sequencing.

Outcome measurements and statistical analysis

Sequences were assigned to operational taxonomic units, differential abundance analysis, and α- and β-diversities, and predictive functional analyses were performed. Plasma steroid hormone levels corresponding to the predicted microbiota steroid hormone biosynthesis profiles were investigated.

Results and limitations

Of 364 patients, 181 were analyzed, 60% of whom were diagnosed with PCa. Microbiota composition and diversity were significantly different in PCa, partially affected by Prevotella 9, the most abundant genus of the cohort, and significantly higher in PCa patients. Predictive functional analyses revealed higher 5-α-reductase, copper absorption, and retinol metabolism in the PCa-associated microbiome. Plasma testosterone was associated negatively with the predicted microbial 5-α-reductase level.

Conclusions

Gut microbiota of the PCa patients differed significantly compared with benign individuals. Microbial 5-α-reductase, copper absorption, and retinol metabolism are potential mechanisms of action. These findings support the observed association of lifestyle, geography, and PCa incidence.

Patient summary

In this report, we found that several microbes and potential functions of the gut microbiota are altered in prostate cancer compared with benign cases. These findings suggest that gut microbiota could be the link between environmental factors and prostate cancer.

Prostate cancer detection and segmentation on MRI using non-local mask R-CNN with histopathological ground truth

BACKGROUND

Automatic detection and segmentation of intraprostatic lesions (ILs) on preoperative multiparametric-magnetic resonance images (mp-MRI) can improve clinical workflow efficiency and enhance the diagnostic accuracy of prostate cancer and is an essential step in dominant intraprostatic lesion boost.

PURPOSE

The goal is to improve the detection and segmentation accuracy of 3D ILs in MRI by a proposed a deep learning (DL)-based algorithm with histopathological ground truth.

METHODS

This retrospective study included 262 patients with in vivo prostate biparametric MRI (bp-MRI) scans and were divided into three cohorts based on their data analysis and annotation. Histopathological ground truth was established by using histopathology images as delineation reference standard on cohort 1, which consisted of 64 patients and was randomly split into 20 training, 12 validation, and 32 testing patients. Cohort 2 consisted of 158 patients with bp-MRI based lesion delineation, and was randomly split into 104 training, 15 validation, and 39 testing patients. Cohort 3 consisted of 40 unannotated patients, used in semi-supervised learning. We proposed a non-local Mask R-CNN and boosted its performance by applying different training techniques. The performance of non-local Mask R-CNN was compared with baseline Mask R-CNN, 3D U-Net and an experienced radiologist's delineation and was evaluated by detection rate, dice similarity coefficient (DSC), sensitivity, and Hausdorff Distance (HD).

RESULTS

The independent testing set consists of 32 patients with histopathological ground truth. With the training technique maximizing detection rate, the non-local Mask R-CNN achieved 80.5% and 94.7% detection rate; 0.548 and 0.604 DSC; 5.72 and 6.36 95 HD (mm); 0.613 and 0.580 sensitivity for ILs of all Gleason Grade groups (GGGs) and clinically significant ILs (GGG > 2), which outperformed baseline Mask R-CNN and 3D U-Net. For clinically significant ILs, the model segmentation accuracy was significantly higher than that of the experienced radiologist involved in the study, who achieved 0.512 DSC (p = 0.04), 8.21 (p = 0.041) 95 HD (mm), and 0.398 (p = 0.001) sensitivity.

CONCLUSION

The proposed DL model achieved state-of-art performance and has the potential to help improve radiotherapy treatment planning and noninvasive prostate cancer diagnosis.

Diagnosis of prostate cancer with magnetic resonance imaging in men treated with 5-alpha-reductase inhibitors

PURPOSE

The primary aim of this study was to evaluate if exposure to 5-alpha-reductase inhibitors (5-ARIs) modifies the effect of MRI for the diagnosis of clinically significant Prostate Cancer (csPCa) (ISUP Gleason grade ≥ 2).

METHODS

This study is a multicenter cohort study including patients undergoing prostate biopsy and MRI at 24 institutions between 2013 and 2022. Multivariable analysis predicting csPCa with an interaction term between 5-ARIs and PIRADS score was performed. Sensitivity, specificity, and negative (NPV) and positive (PPV) predictive values of MRI were compared in treated and untreated patients.

RESULTS

705 patients (9%) were treated with 5-ARIs [median age 69 years, Interquartile range (IQR): 65, 73; median PSA 6.3 ng/ml, IQR 4.0, 9.0; median prostate volume 53 ml, IQR 40, 72] and 6913 were 5-ARIs naïve (age 66 years, IQR 60, 71; PSA 6.5 ng/ml, IQR 4.8, 9.0; prostate volume 50 ml, IQR 37, 65). MRI showed PIRADS 1-2, 3, 4, and 5 lesions in 141 (20%), 158 (22%), 258 (37%), and 148 (21%) patients treated with 5-ARIs, and 878 (13%), 1764 (25%), 2948 (43%), and 1323 (19%) of untreated patients (p < 0.0001). No difference was found in csPCa detection rates, but diagnosis of high-grade PCa (ISUP GG ≥ 3) was higher in treated patients (23% vs 19%, p = 0.013). We did not find any evidence of interaction between PIRADS score and 5-ARIs exposure in predicting csPCa. Sensitivity, specificity, PPV, and NPV of PIRADS ≥ 3 were 94%, 29%, 46%, and 88% in treated patients and 96%, 18%, 43%, and 88% in untreated patients, respectively.

CONCLUSIONS

Exposure to 5-ARIs does not affect the association of PIRADS score with csPCa. Higher rates of high-grade PCa were detected in treated patients, but most were clearly visible on MRI as PIRADS 4 and 5 lesions.

TRIAL REGISTRATION

The present study was registered at ClinicalTrials.gov number: NCT05078359.

Discrepancies between Radiology Specialists and Residents in Fracture Detection from Musculoskeletal Radiographs

(1) Background: The aim of this study was to compare the competence in appendicular trauma radiograph image interpretation between radiology specialists and residents. (2) Methods: In this multicenter retrospective cohort study, we collected radiology reports from radiology specialists (N = 506) and residents (N = 500) during 2018-2021. As a reference standard, we used the consensus of two subspecialty-level musculoskeletal (MSK) radiologists, who reviewed all original reports. (3) Results: A total of 1006 radiograph reports were reviewed by the two subspecialty-level MSK radiologists. Out of the 1006 radiographs, 41% were abnormal. In total, 67 radiographic findings were missed (6.7%) and 31 findings were overcalled (3.1%) in the original reports. Sensitivity, specificity, positive predictive value, and negative predictive value were 0.86, 0.92, 0.91 and 0.88 respectively. There were no statistically significant differences between radiology specialists' and residents' competence in interpretation (p = 0.44). However, radiology specialists reported more subtle cases than residents did (p = 0.04). There were no statistically significant differences between errors made in the morning, evening, or night shifts (p = 0.57). (4) Conclusions: This study found a lack of major discrepancies between radiology specialists and residents in radiograph interpretation, although there were differences between MSK regions and in subtle or obvious radiographic findings. In addition, missed findings found in this study often affected patient treatment. Finally, there are MSK regions where the sensitivity or specificity is below 90%, and these should raise concerns and highlight the need for double reading and should be taken into consideration in radiology education.

Resident education in radiology in Europe including entrustable professional activities: results of an ESR survey

Entrustable professional activity (EPA) is a tool for comprehensively evaluating the level of confidence in resident performances across various competencies in medicine. The application of and attitudes towards EPAs in radiology across the European Society of Radiology (ESR) national institutional member societies is still to be determined. An online survey was conducted among ESR national institutional member societies to assess the current use of EPAs and other resident assessment forms among different countries.Although the primary focus was on the use of EPAs, additional questions also addressed the adherence of training programs to the European Training Curriculum (ETC), other methods of continuous assessment, and examinations. A total of 65 responses were received from 38 countries (81% response rate among national institutional member societies). EPAs were being used in radiology in 21% of countries and planned to be used in 26%. Most responders considered EPAs suitable for radiology and, regarding the future, preferred European-level guidelines on EPAs over national or institutional levels. The majority (63%) of national training programs were reported to be similar to or following the content of the ETC, and the majority (95%) of countries rated the requirements of the European Training Curriculum (ETC) to be adequate. In conclusion, EPAs are beginning to be used in radiology resident training programs across Europe, and their use is expected to increase. There seems to be a positive attitude toward using EPAs in radiology and toward a common European framework.Critical relevance statement As a result of this survey, we found positive attitudes towards using entrustable professional activities (EPA) in radiology among the institutional member societies of the European Society of Radiology (ESR).Key points• Twenty-one percent of national member societies use entrustable professional activities (EPA) in radiology.• There is a positive attitude toward using EPAs in radiology.• Majority of respondents preferred a common European framework for EPAs.• Majority of radiology training curricula adhere to the European Training Curriculum (ETC).

Predicting the Need for Biopsy to Detect Clinically Significant Prostate Cancer in Patients with a Magnetic Resonance Imaging-detected Prostate Imaging Reporting and Data System/Likert ≥3 Lesion: Development and Multinational External Validation of the Imperial Rapid Access to Prostate Imaging and Diagnosis Risk Score

BACKGROUND

Although multiparametric magnetic resonance imaging (MRI) has high sensitivity, its lower specificity leads to a high prevalence of false-positive lesions requiring biopsy.

OBJECTIVE

To develop and externally validate a scoring system for MRI-detected Prostate Imaging Reporting and Data System (PIRADS)/Likert ≥3 lesions containing clinically significant prostate cancer (csPCa).

DESIGN, SETTING, AND PARTICIPANTS

The multicentre Rapid Access to Prostate Imaging and Diagnosis (RAPID) pathway included 1189 patients referred to urology due to elevated age-specific prostate-specific antigen (PSA) and/or abnormal digital rectal examination (DRE); April 27, 2017 to October 25, 2019.

INTERVENTION

Visual-registration or image-fusion targeted and systematic transperineal biopsies for an MRI score of ≥4 or 3 + PSA density ≥0.12 ng/ml/ml.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Fourteen variables were used in multivariable logistic regression for Gleason ≥3 + 4 (primary) and Gleason ≥4 + 3, and PROMIS definition 1 (any ≥4 + 3 or ≥6 mm any grade; secondary). Nomograms were created and a decision curve analysis (DCA) was performed. Models with varying complexity were externally validated in 2374 patients from six international cohorts.

RESULTS AND LIMITATIONS

The five-item Imperial RAPID risk score used age, PSA density, prior negative biopsy, prostate volume, and highest MRI score (corrected c-index for Gleason ≥3 + 4 of 0.82 and 0.80-0.86 externally). Incorporating family history, DRE, and Black ethnicity within the eight-item Imperial RAPID risk score provided similar outcomes. The DCA showed similar superiority of all models, with net benefit differences increasing in higher threshold probabilities. At 20%, 30%, and 40% of predicted Gleason ≥3 + 4 prostate cancer, the RAPID risk score was able to reduce, respectively, 11%, 21%, and 31% of biopsies against 1.8%, 6.2%, and 14% of missed csPCa (or 9.6%, 17%, and 26% of foregone biopsies, respectively).

CONCLUSIONS

The Imperial RAPID risk score provides a standardised tool for the prediction of csPCa in patients with an MRI-detected PIRADS/Likert ≥3 lesion and can support the decision for prostate biopsy.

PATIENT SUMMARY

In this multinational study, we developed a scoring system incorporating clinical and magnetic resonance imaging characteristics to predict which patients have prostate cancer requiring treatment and which patients can safely forego an invasive prostate biopsy. This model was validated in several other countries.

Deep learning accurately classifies elbow joint effusion in adult and pediatric radiographs

Joint effusion due to elbow fractures are common among adults and children. Radiography is the most commonly used imaging procedure to diagnose elbow injuries. The purpose of the study was to investigate the diagnostic accuracy of deep convolutional neural network algorithms in joint effusion classification in pediatric and adult elbow radiographs. This retrospective study consisted of a total of 4423 radiographs in a 3-year period from 2017 to 2020. Data was randomly separated into training (n = 2672), validation (n = 892) and test set (n = 859). Two models using VGG16 as the base architecture were trained with either only lateral projection or with four projections (AP, LAT and Obliques). Three radiologists evaluated joint effusion separately on the test set. Accuracy, precision, recall, specificity, F1 measure, Cohen’s kappa, and two-sided 95% confidence intervals were calculated. Mean patient age was 34.4 years (1–98) and 47% were male patients. Trained deep learning framework showed an AUC of 0.951 (95% CI 0.946–0.955) and 0.906 (95% CI 0.89–0.91) for the lateral and four projection elbow joint images in the test set, respectively. Adult and pediatric patient groups separately showed an AUC of 0.966 and 0.924, respectively. Radiologists showed an average accuracy, sensitivity, specificity, precision, F1 score, and AUC of 92.8%, 91.7%, 93.6%, 91.07%, 91.4%, and 92.6%. There were no statistically significant differences between AUC's of the deep learning model and the radiologists (p value > 0.05). The model on the lateral dataset resulted in higher AUC compared to the model with four projection datasets. Using deep learning it is possible to achieve expert level diagnostic accuracy in elbow joint effusion classification in pediatric and adult radiographs. Deep learning used in this study can classify joint effusion in radiographs and can be used in image interpretation as an aid for radiologists.

How to read biparametric MRI in men with a clinical suspicious of prostate cancer: Pictorial review for beginners with public access to imaging, clinical and histopathological database

Prostate Magnetic Resonance Imaging (MRI) is increasingly being used in men with a clinical suspicion of prostate cancer (PCa). Performing prostate MRI without the use of an intravenous contrast (IV) agent in men with a clinical suspicion of PCa can lead to reduced MRI scan time. Enabling a large array of different medical providers (from mid-level to specialized radiologists) to evaluate and potentially report prostate MRI in men with a clinical suspicion of PCa with a high accuracy could be one way to enable wide adoption of prostate MRI in men with a clinical suspicion of PCa. The aim of this pictorial review is to provide an insight into acquisition, quality control and reporting of prostate MRI performed without IV contrast agent in men with a clinical suspicion of PCa, aimed specifically at radiologists starting reporting prostate MRI, urologists, urology/radiology residents and mid-level medical providers without experience in reporting prostate MRI. Free public access (http://petiv.utu.fi/improd/and http://petiv.utu.fi/multiimprod/) to complete datasets of 161 and 338 men is provided. The imaging datasets are accompanied by clinical, laboratory and histopathological findings. Several topics are simplified in order to provide a solid base for the development of skills needed for an unsupervised review and potential reporting of prostate MRI in men with a clinical suspicion of PCa. The current review represents the first step towards enabling a large array of different medical providers to review and report accurately prostate MRI performed without IV contrast agent in men with a clinical suspicion of PCa.

Prospective comparison of 18F-PSMA-1007 PET/CT, whole-body MRI and CT in primary nodal staging of unfavourable intermediate- and high-risk prostate cancer

PURPOSE

To prospectively compare 18F-prostate-specific membrane antigen (PSMA)-1007 positron emission tomography (PET)/CT, whole-body magnetic resonance imaging (WBMRI) including diffusion-weighted imaging (DWI) and standard computed tomography (CT), in primary nodal staging of prostate cancer (PCa).

METHODS

Men with newly diagnosed unfavourable intermediate- or high-risk PCa prospectively underwent 18F-PSMA-1007 PET/CT, WBMRI with DWI and contrast-enhanced CT within a median of 8 days. Six readers (two for each modality) independently reported pelvic lymph nodes as malignant, equivocal or benign while blinded to the other imaging modalities. Sensitivity, specificity and accuracy were reported according to optimistic (equivocal lesions interpreted as benign) and pessimistic (equivocal lesions interpreted as malignant) analyses. The reference standard diagnosis was based on multidisciplinary consensus meetings where available histopathology, clinical and follow-up data were used.

RESULTS

Seventy-nine patients completed all the imaging modalities, except for one case of interrupted WBMRI. Thirty-one (39%) patients had pelvic lymph node metastases, which were detected in 27/31 (87%), 14/31 (45%) and 8/31 (26%) patients by 18F-PSMA-1007 PET/CT, WBMRI with DWI and CT, respectively (optimistic analysis). In 8/31 (26%) patients, only 18F-PSMA-1007 PET/CT detected malignant lymph nodes, while the other two imaging modalities were reported as negative. At the patient level, sensitivity and specificity values for 18F-PSMA-1007 PET/CT, WBMRI with DWI and CT in optimistic analysis were 0.87 (95%CI 0.71-0.95) and 0.98 (95%CI 0.89-1.00), 0.37 (95%CI 0.22-0.55) and 0.98 (95%CI 0.89-1.00) and 0.26 (95%CI 0.14-0.43) and 1.00 (95%CI 0.93-1.00), respectively.

CONCLUSION

18F-PSMA-1007 PET/CT showed significantly greater sensitivity in nodal staging of primary PCa than did WBMRI with DWI or CT, while maintaining high specificity.

CLINICAL TRIAL REGISTRATION

Clinicaltrials.gov ID: NCT03537391.

Detection of Prostate Cancer Using Biparametric Prostate MRI, Radiomics, and Kallikreins: A Retrospective Multicenter Study of Men With a Clinical Suspicion of Prostate Cancer

BACKGROUND

Accurate detection of clinically significant prostate cancer (csPCa), Gleason Grade Group ≥ 2, remains a challenge. Prostate MRI radiomics and blood kallikreins have been proposed as tools to improve the performance of biparametric MRI (bpMRI).

PURPOSE

To develop and validate radiomics and kallikrein models for the detection of csPCa.

STUDY TYPE

Retrospective.

POPULATION

A total of 543 men with a clinical suspicion of csPCa, 411 (76%, 411/543) had kallikreins available and 360 (88%, 360/411) did not take 5-alpha-reductase inhibitors. Two data splits into training, validation (split 1: single center, n = 72; split 2: random 50% of pooled datasets from all four centers), and testing (split 1: 4 centers, n = 288; split 2: remaining 50%) were evaluated.

FIELD STRENGTH/SEQUENCE

A 3 T/1.5 T, TSE T2-weighted imaging, 3x SE DWI.

ASSESSMENT

In total, 20,363 radiomic features calculated from manually delineated whole gland (WG) and bpMRI suspicion lesion masks were evaluated in addition to clinical parameters, prostate-specific antigen, four kallikreins, MRI-based qualitative (PI-RADSv2.1/IMPROD bpMRI Likert) scores.

STATISTICAL TESTS

For the detection of csPCa, area under receiver operating curve (AUC) was calculated using the DeLong's method. A multivariate analysis was conducted to determine the predictive power of combining variables. The values of P-value < 0.05 were considered significant.

RESULTS

The highest prediction performance was achieved by IMPROD bpMRI Likert and PI-RADSv2.1 score with AUC = 0.85 and 0.85 in split 1, 0.85 and 0.83 in split 2, respectively. bpMRI WG and/or kallikreins demonstrated AUCs ranging from 0.62 to 0.73 in split 1 and from 0.68 to 0.76 in split 2. AUC of bpMRI lesion-derived radiomics model was not statistically different to IMPROD bpMRI Likert score (split 1: AUC = 0.83, P-value = 0.306; split 2: AUC = 0.83, P-value = 0.488).

DATA CONCLUSION

The use of radiomics and kallikreins failed to outperform PI-RADSv2.1/IMPROD bpMRI Likert and their combination did not lead to further performance gains.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 2.

Statistical Evaluation of Different Mathematical Models for Diffusion Weighted Imaging of Prostate Cancer Xenografts in Mice

Purpose

To evaluate fitting quality and repeatability of four mathematical models for diffusion weighted imaging (DWI) during tumor progression in mouse xenograft model of prostate cancer.

Methods

Human prostate cancer cells (PC-3) were implanted subcutaneously in right hind limbs of 11 immunodeficient mice. Tumor growth was followed by weekly DWI examinations using a 7T MR scanner. Additional DWI examination was performed after repositioning following the fourth DWI examination to evaluate short term repeatability. DWI was performed using 15 and 12 b-values in the ranges of 0-500 and 0-2000 s/mm², respectively. Corrected Akaike information criteria and F-ratio were used to evaluate fitting quality of each model (mono-exponential, stretched exponential, kurtosis, and bi-exponential).

Results

Significant changes were observed in DWI data during the tumor growth, indicated by ADC_m, ADC_s, and ADC_k. Similar results were obtained using low as well as high b-values. No marked changes in model preference were present between the weeks 1−4. The parameters of the mono-exponential, stretched exponential, and kurtosis models had smaller confidence interval and coefficient of repeatability values than the parameters of the bi-exponential model.

Conclusion

Stretched exponential and kurtosis models showed better fit to DWI data than the mono-exponential model and presented with good repeatability.

Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study

Existing tools for post-radical prostatectomy (RP) prostate cancer biochemical recurrence (BCR) prognosis rely on human pathologist-derived parameters such as tumor grade, with the resulting inter-reviewer variability. Genomic companion diagnostic tests such as Decipher tend to be tissue destructive, expensive, and not routinely available in most centers. We present a tissue non-destructive method for automated BCR prognosis, termed "Histotyping", that employs computational image analysis of morphologic patterns of prostate tissue from a single, routinely acquired hematoxylin and eosin slide. Patients from two institutions (n = 214) were used to train Histotyping for identifying high-risk patients based on six features of glandular morphology extracted from RP specimens. Histotyping was validated for post-RP BCR prognosis on a separate set of n = 675 patients from five institutions and compared against Decipher on n = 167 patients. Histotyping was prognostic of BCR in the validation set (p < 0.001, univariable hazard ratio [HR] = 2.83, 95% confidence interval [CI]: 2.03-3.93, concordance index [c-index] = 0.68, median years-to-BCR: 1.7). Histotyping was also prognostic in clinically stratified subsets, such as patients with Gleason grade group 3 (HR = 4.09) and negative surgical margins (HR = 3.26). Histotyping was prognostic independent of grade group, margin status, pathological stage, and preoperative prostate-specific antigen (PSA) (multivariable p < 0.001, HR = 2.09, 95% CI: 1.40-3.10, n = 648). The combination of Histotyping, grade group, and preoperative PSA outperformed Decipher (c-index = 0.75 vs. 0.70, n = 167). These results suggest that a prognostic classifier for prostate cancer based on digital images could serve as an alternative or complement to molecular-based companion diagnostic tests.

Whole Brain Adiabatic T1rho and Relaxation Along a Fictitious Field Imaging in Healthy Volunteers and Patients With Multiple Sclerosis: Initial Findings

BACKGROUND

In preclinical models of multiple sclerosis (MS), both adiabatic T_1rho (T_1ρadiab ) and relaxation along a fictitious field (RAFF) imaging have demonstrated potential to noninvasively characterize MS.

PURPOSE

To evaluate the feasibility of whole brain T_1ρadiab and RAFF imaging in healthy volunteers and patients with MS.

STUDY TYPE

Single institutional clinical trial.

SUBJECTS

38 healthy volunteers (24-69 years) and 21 patients (26-59 years) with MS. Five healthy volunteers underwent a second MR examination performed within 8 days. Clinical disease severity (The Expanded Disability Status Scale [EDSS] and The Multiple Sclerosis Severity Score [MSSS]) was evaluated at baseline and 1-year follow-up (FU).

FIELD STRENGTH/SEQUENCE

RAFF in second rotating frame of reference (RAFF2) was performed at 3 T using 3D-fast-field echo with magnetization preparation, RF amplitude of 11.74 μT while the corresponding value for T_1ρadiab was 13.50 μT. T₁ -, T₂ -, and FLAIR-weighted images were acquired with reconstruction voxel size 1.0 × 1.0 × 1.0 mm³ .

ASSESSMENT

The parametric maps of T_1ρadiab and RAFF2 (T_RAFF2 ) were calculated using a monoexponential model. Semi-automatic segmentation of MS lesions, white matter (WM), and gray matter (GM), and WM tracks was performed using T₁ -, T₂ -, and FLAIR-weighted images.

STATISTICAL TESTS

Regression analysis was used to evaluate correlation of T_1ρadiab and T_RAFF2 with age and disease severity while a Friedman test followed by Wilcoxon Signed Rank test for differences between tissue types. Short-term repeatability was evaluated on voxel level.

RESULTS

Both T_1ρadiab and T_RAFF2 demonstrated good short-term repeatability with relative differences on voxel level in the range of 6.1%-11.9%. Differences in T_1ρadiab and T_RAFF2 between the tissue types in MS patients were significant (P < 0.05). T_1ρadiab and T_RAFF2 correlated (P < 0.001) with baseline EDSS/MSSM and disease progression at FU (P < 0.001).

DATA CONCLUSION

Whole brain T_1ρadiab and T_RAFF2 at 3 T was feasible with significant differences in T_1ρadiab and T_RAFF2 values between tissues types and correlation with disease severity.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 1.

Combined Use of Prostate-specific Antigen Density and Magnetic Resonance Imaging for Prostate Biopsy Decision Planning: A Retrospective Multi-institutional Study Using the Prostate Magnetic Resonance Imaging Outcome Database (PROMOD)

BACKGROUND

Previous studies suggested that prostate-specific antigen (PSA) density (PSAd) combined with magnetic resonance imaging (MRI) may help avoid unnecessary prostate biopsy (PB) with a limited risk of missing clinically significant prostate cancer (csPCa; Gleason grade group [GGG] >1).

OBJECTIVE

To define optimal diagnostic strategies based on the combined use of PSAd and MRI in patients at risk of prostate cancer (PCa).

DESIGN, SETTING, AND PARTICIPANTS

A retrospective analysis of the international multicenter Prostate MRI Outcome Database (PROMOD), including 2512 men having undergone PSAd and prostate MRI before PB between 2013 and 2019, was performed.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Rates of avoided PB, missed GGG 1, and csPCa according to 10 strategies based on PSAd values and MRI reporting scores (Prostate Imaging Reporting and Data System [PI-RADS]/Likert/IMPROD biparametric prostate MRI Likert). Decision curve analysis (DCA) was used to statistically compare the net benefit of each strategy. Combined systematic and targeted biopsies were used for reference.

RESULTS AND LIMITATIONS

According to DCA, the best strategy in biopsy-naive patients was #7 (PI-RADS/Likert 4-5 or PI-RADS/Likert 3 if PSAd >0.2), which avoided 41.2% PBs while missed 44% of GGG 1 and 10.9% of csPCa cases. From a clinical standpoint, however, strategies with a lower risk of missing csPCa included #10 (PI-RADS/Likert 4-5 or PI-RADS 3 if PSAd >0.10 or PSAd >0.2), which avoided 27% PBs while missing 24.4% GGG 1 and 4% csPCa cases, or #5 (PI-RADS/Likert 3-5 or PSAd>0.15), which avoided 14.7% PBs while missing 9.3% GGG 1 and 1.7% csPCa cases. Similar results were found in patients with a previous negative biopsy. This study is limited by its retrospective nature, and no central review of MRI and histopathological findings.

CONCLUSIONS

Combined PSAd and MRI findings allows individualization of the decision to perform PB on the basis of the risk of missing PCa that both patients and clinicians are ready to accept to avoid this procedure.

PATIENT SUMMARY

We compared several biopsy strategies based on a combination of prostate magnetic resonance imaging findings and prostate-specific antigen density, providing a readily available tool for each center and practicing urologist to counsel patients about their individual risk of significant prostate cancer.

Test-retest repeatability of a deep learning architecture in detecting and segmenting clinically significant prostate cancer on apparent diffusion coefficient (ADC) maps

OBJECTIVES

To evaluate short-term test-retest repeatability of a deep learning architecture (U-Net) in slice- and lesion-level detection and segmentation of clinically significant prostate cancer (csPCa: Gleason grade group > 1) using diffusion-weighted imaging fitted with monoexponential function, ADC_m.

METHODS

One hundred twelve patients with prostate cancer (PCa) underwent 2 prostate MRI examinations on the same day. PCa areas were annotated using whole mount prostatectomy sections. Two U-Net-based convolutional neural networks were trained on three different ADC_m b value settings for (a) slice- and (b) lesion-level detection and (c) segmentation of csPCa. Short-term test-retest repeatability was estimated using intra-class correlation coefficient (ICC(3,1)), proportionate agreement, and dice similarity coefficient (DSC). A 3-fold cross-validation was performed on training set (N = 78 patients) and evaluated for performance and repeatability on testing data (N = 34 patients).

RESULTS

For the three ADC_m b value settings, repeatability of mean ADC_m of csPCa lesions was ICC(3,1) = 0.86-0.98. Two CNNs with U-Net-based architecture demonstrated ICC(3,1) in the range of 0.80-0.83, agreement of 66-72%, and DSC of 0.68-0.72 for slice- and lesion-level detection and segmentation of csPCa. Bland-Altman plots suggest that there is no systematic bias in agreement between inter-scan ground truth segmentation repeatability and segmentation repeatability of the networks.

CONCLUSIONS

For the three ADC_m b value settings, two CNNs with U-Net-based architecture were repeatable for the problem of detection of csPCa at the slice-level. The network repeatability in segmenting csPCa lesions is affected by inter-scan variability and ground truth segmentation repeatability and may thus improve with better inter-scan reproducibility.

KEY POINTS

• For the three ADC_m b value settings, two CNNs with U-Net-based architecture were repeatable for the problem of detection of csPCa at the slice-level. • The network repeatability in segmenting csPCa lesions is affected by inter-scan variability and ground truth segmentation repeatability and may thus improve with better inter-scan reproducibility.

A Prospective Comparison of 18F-prostate-specific Membrane Antigen-1007 Positron Emission Tomography Computed Tomography, Whole-body 1.5 T Magnetic Resonance Imaging with Diffusion-weighted Imaging, and Single-photon Emission Computed Tomography/Computed Tomography with Traditional Imaging in Primary Distant Metastasis Staging of Prostate Cancer (PROSTAGE)

BACKGROUND

Computed tomography (CT) and bone scintigraphy (BS) are the imaging modalities currently used for distant metastasis staging of prostate cancer (PCa).

OBJECTIVE

To compare standard staging modalities with newer and potentially more accurate imaging modalities.

DESIGN, SETTING, AND PARTICIPANTS

This prospective, single-centre trial (NCT03537391) enrolled 80 patients with newly diagnosed high-risk PCa (International Society of Urological Pathology grade group ≥3 and/or prostate-specific antigen [PSA] ≥20 and/or cT ≥ T3; March 2018-June 2019) to undergo primary metastasis staging with two standard and three advanced imaging modalities.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The participants underwent the following five imaging examinations within 2 wk of enrolment and without a prespecified sequence: BS, CT, ^99mTc-hydroxymethylene diphosphonate (^99mTc-HMDP) single-photon emission computed tomography (SPECT)-CT, 1.5 T whole-body magnetic resonance imaging (WBMRI) using diffusion-weighted imaging, and ¹⁸F-prostate-specific membrane antigen-1007 (¹⁸F-PSMA-1007) positron emission tomography(PET)-CT. Each modality was reviewed by two independent experts blinded to the results of the prior studies, who classified lesions as benign, equivocal, or malignant. Pessimistic and optimistic analyses were performed to resolve each equivocal diagnosis. The reference standard diagnosis was defined using all available information accrued during at least 12 mo of clinical follow-up. Patients with equivocal reference standard diagnoses underwent MRI and/or CT to search for the development of anatomical correspondence. PSMA PET-avid lesions without histopathological verification were rated to be malignant only if there was a corresponding anatomical finding suspicious for malignancy at the primary or follow-up imaging.

RESULTS AND LIMITATIONS

Seventy-nine men underwent all imaging modalities except for one case of interrupted MRI. The median interval per patient between the first and the last imaging study was 8 d (interquartile range [IQR]: 6-9). The mean age was 70 yr (standard deviation: 7) and median PSA 12 ng/mL (IQR:7-23). The median follow-up was 435 d (IQR: 378-557). Metastatic disease was detected in 20 (25%) patients. The imaging modality ¹⁸F-PSMA-1007 PET-CT had superior sensitivity and highest inter-reader agreement. The area under the receiver-operating characteristic curve (AUC) values for bone metastasis detection with PSMA PET-CT were 0.90 (95% confidence interval [CI]: 0.85-0.95) and 0.91 (95% CI: 0.87-0.96) for readers 1 and 2, respectively, while the AUC values for BS, CT, SPECT-CT, and WBMRI were 0.71 (95% CI: 0.58-0.84) and 0.8 (95% CI: 0.67-0.92), 0.53 (95% CI: 0.39-0.67) and 0.66 (95% CI: 0.54-0.77), 0.77 (95% CI: 0.65-0.89) and 0.75 (95% CI: 0.62-0.88), and 0.85 (95% CI: 0.74-0.96) and 0.67 (95% CI: 0.54-0.80), respectively, for the other four pairs of readers. The imaging method ¹⁸F-PSMA-1007 PET-CT detected metastatic disease in 11/20 patients in whom standard imaging was negative and influenced clinical decision making in 14/79 (18%) patients. In 12/79 cases, false positive bone disease was reported only by PSMA PET-CT. Limitations included a nonrandomised study setting and few histopathologically validated suspicious lesions.

CONCLUSIONS

Despite the risk of false positive bone lesions, ¹⁸F-PSMA-1007 PET-CT outperformed all other imaging methods studied for the detection of primary distant metastasis in high-risk PCa.

PATIENT SUMMARY

In this report, we compared the diagnostic performance of conventional and advanced imaging. It was found that ¹⁸F-prostate-specific membrane antigen-1007 positron emission tomography/computed tomography (¹⁸F-PSMA-1007 PET-CT) was superior to the other imaging modalities studied for the detection of distant metastasis at the time of initial diagnosis of high-risk prostate cancer. PSMA PET-CT also appears to detect some nonmetastatic bone lesions.

Negative Predictive Value of Biparametric Prostate Magnetic Resonance Imaging in Excluding Significant Prostate Cancer: A Pooled Data Analysis Based on Clinical Data from Four Prospective, Registered Studies

BACKGROUND

Multiparametric prostate magnetic resonance imaging (mpMRI) can be considered the gold standard in prostate magnetic resonance imaging (MRI). Biparametric prostate MRI (bpMRI) is faster and could be a feasible alternative to mpMRI.

OBJECTIVE

To determine the negative predictive value (NPV) of Improved Prostate Cancer Diagnosis (IMPROD) bpMRI as a whole and in clinical subgroups in primary diagnostics of clinically significant prostate cancer (CSPCa).

DESIGN, SETTING, AND PARTICIPANTS

This is a pooled data analysis of four prospective, registered clinical trials investigating prebiopsy IMPROD bpMRI. Men with a clinical suspicion of prostate cancer (PCa) were included.

INTERVENTION

Prebiopsy IMPROD bpMRI was performed, and an IMPROD bpMRI Likert scoring system was used. If suspicious lesions (IMPROD bpMRI Likert score 3-5) were visible, targeted biopsies in addition to systematic biopsies were taken.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Performance measures of IMPROD bpMRI in CSPCa diagnostics were evaluated. NPV was also evaluated in clinical subgroups. Gleason grade ≥3 + 4 in any biopsy core taken was defined as CSPCa.

RESULTS AND LIMITATIONS

A total of 639 men were included in the analysis. The mean age was 64 yr, mean prostate-specific antigen level was 8.9 ng/ml, and CSPCa prevalence was 48%. NPVs of IMPROD bpMRI Likert scores 3-5 and 4-5 for CSPCa were 0.932 and 0.909, respectively, and the corresponding positive predictive values were 0.589 and 0.720. Only nine of 132 (7%) men with IMPROD bpMRI Likert score 1-2 had CSPCa and none with Gleason score >7. Thus, 132 of 639 (21%) study patients could have avoided biopsies without missing a single Gleason >7 cancer in the study biopsies. In the subgroup analysis, no clear outlier was present. The limitation is uncertainty of the true CSPCa prevalence.

CONCLUSIONS

IMPROD bpMRI demonstrated a high NPV to rule out CSPCa. IMPROD bpMRI Likert score 1-2 excludes Gleason >7 PCa in the study biopsies.

PATIENT SUMMARY

We investigated the feasibility of prostate magnetic resonance imaging (MRI) with the Improved Prostate Cancer Diagnosis (IMPROD) biparametric MRI (bpMRI) protocol in excluding significant prostate cancer. In this study, highly aggressive prostate cancer was excluded using the publicly available IMPROD bpMRI protocol (http://petiv.utu.fi/multiimprod/).

Impact of biparametric prebiopsy prostate magnetic resonance imaging on the diagnostics of clinically significant prostate cancer in biopsy naïve men

Background: The objective of this study was to compare the prevalence of clinically significant prostate cancer (CSPCa) in men with biparametric prebiopsy prostate magnetic resonance imaging (MRI) and lesion-targeted biopsies (TBs) to the group of men without prebiopsy MRI in an initial biopsy session.Methods: The MRI group consists of men enrolled into four prospective clinical trials investigating a biparametric MRI (bpMRI) and TB while the non-MRI group was a retrospective cohort of men collected from an era prior to a clinical use of a prostate MRI. All men had standard biopsies (SBs). In the MRI group, men had additional TBs from potential cancer-suspicious lesions. CSPCa was defined as Gleason score ≥3 + 4 in any biopsy core taken. All the patients were prostate biopsy naïve.Results: The MRI group consists of 507 while the non-MRI group 379 men. Mean age and prostate specific antigen (PSA) level differed significantly (p < 0.05) between the groups: In the MRI group, 64 years and 7.6 ng/ml, respectively, and in the non-MRI group 68 years and 8.2 ng/ml, respectively. Significantly (p < 0.05) more CSPCa was diagnosed with initial biopsies in the MRI group (48%) compared to non-MRI group (34%). In men with no CSPCa diagnosed during the initial biopsies, significantly fewer (p < 0.05) men had upgrading re-biopsies in the MRI group (5%) than in the non-MRI group (19%) during the follow up.Conclusions: Prebiopsy bpMRI with TBs combined with SBs could lead to earlier diagnoses of CSPCa compared with men without prebiopsy prostate MRI used in initial PCa diagnostics.

Repeatability of radiomics and machine learning for DWI: Short-term repeatability study of 112 patients with prostate cancer

PURPOSE

To evaluate repeatability of prostate DWI-derived radiomics and machine learning methods for prostate cancer (PCa) characterization.

METHODS

A total of 112 patients with diagnosed PCa underwent 2 prostate MRI examinations (Scan1 and Scan2) performed on the same day. DWI was performed using 12 b-values (0-2000 s/mm² ), post-processed using kurtosis function, and PCa areas were annotated using whole mount prostatectomy sections. A total of 1694 radiomic features including Sobel, Kirch, Gradient, Zernike Moments, Gabor, Haralick, CoLIAGe, Haar wavelet coefficients, 3D analogue to Laws features, 2D contours, and corner detectors were calculated. Radiomics and 4 feature pruning methods (area under the receiver operator characteristic curve, maximum relevance minimum redundancy, Spearman's ρ, Wilcoxon rank-sum) were evaluated in terms of Scan1-Scan2 repeatability using intraclass correlation coefficient (ICC)(3,1). Classification performance for clinically significant and insignificant PCa with Gleason grade groups 1 versus >1 was evaluated by area under the receiver operator characteristic curve in unseen random 30% data split.

RESULTS

The ICC(3,1) values for conventional radiomics and feature pruning methods were in the range of 0.28-0.90. The machine learning classifications varied between Scan1 and Scan2 with % of same class labels between Scan1 and Scan2 in the range of 61-81%. Surface-to-volume ratio and corner detector-based features were among the most represented features with high repeatability, ICC(3,1) >0.75, consistently high ranking using all 4 feature pruning methods, and classification performance with area under the receiver operator characteristic curve >0.70.

CONCLUSION

Surface-to-volume ratio and corner detectors for prostate DWI led to good classification of unseen data and performed similarly in Scan1 and Scan2 in contrast to multiple conventional radiomic features.

Prostate Cancer Risk Stratification in Men With a Clinical Suspicion of Prostate Cancer Using a Unique Biparametric MRI and Expression of 11 Genes in Apparently Benign Tissue: Evaluation Using Machine-Learning Techniques

BACKGROUND

Accurate risk stratification of men with a clinical suspicion of prostate cancer (cSPCa) remains challenging despite the increasing use of MRI.

PURPOSE

To evaluate the diagnostic accuracy of a unique biparametric MRI protocol (IMPROD bpMRI) combined with clinical and molecular markers in men with cSPCa.

STUDY TYPE

Prospective single-institutional clinical trial (NCT01864135).

SUBJECTS

Eighty men with cSPCa.

FIELD STRENGTH/SEQUENCE

3T, surface array coils. Two T₂ -weighted and three diffusion-weighted imaging (DWI) acquisitions: 1) b-values 0, 100, 200, 300, 500 s/mm² ; 2) b-values 0,1500 s/mm² ; 3) b-values 0, 2000 s/mm² .

ASSESSMENT

IMPROD bpMRI examinations were qualitatively (IMPROD bpMRI Likert score) and quantitatively (DWI-based Gleason grade score) prospectively reported. Men with IMPROD bpMRI Likert 3-5 had two targeted biopsies followed by 12-core systematic biopsies (SB); those with IMPROD bpMRI Likert 1-2 had only SB. Additionally, 2-core from normal-appearing prostate areas were obtained for the mRNA expression of ACSM1, AMACR, CACNA1D, DLX1, PCA3, PLA2G7, RHOU, SPINK1, SPON2, TMPRSS2-ERG, and TDRD1 measured by quantitative reverse-transcription polymerase chain reaction.

STATISTICAL TESTS

Univariate and multivariate analysis using regularized least-squares, feature selection and tournament leave-pair-out cross-validation (TLPOCV), as well as 10 random splits of the data in training-testing sets, were used to evaluate the mRNA, clinical and IMPROD bpMRI parameters in detecting clinically significant prostate cancer (SPCa) defined as Gleason score ≥ 3 + 4. The evaluation metric was the area under the curve (AUC).

RESULTS

IMPROD bpMRI Likert demonstrated the highest TLPOCV AUC of 0.92. The tested clinical variables had AUC 0.56-0.73, while the mRNA and additional IMPROD bpMRI parameters had AUC 0.50-0.67 and 0.65-0.89 respectively. The combination of clinical and mRNA biomarkers produced TLPOCV AUC of 0.87, the highest TLPOCV performance without including IMPROD bpMRI Likert.

DATA CONCLUSION

The qualitative IMPROD bpMRI Likert score demonstrated the highest accuracy for SPCa detection compared with the tested clinical variables and mRNA biomarkers.

LEVEL OF EVIDENCE

1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1540-1553.

Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization

Purpose

To develop and validate a classifier system for prediction of prostate cancer (PCa) Gleason score (GS) using radiomics and texture features of T₂-weighted imaging (T₂w), diffusion weighted imaging (DWI) acquired using high b values, and T₂-mapping (T₂).

Methods

T₂w, DWI (12 b values, 0–2000 s/mm²), and T₂ data sets of 62 patients with histologically confirmed PCa were acquired at 3T using surface array coils. The DWI data sets were post-processed using monoexponential and kurtosis models, while T₂w was standardized to a common scale. Local statistics and 8 different radiomics/texture descriptors were utilized at different configurations to extract a total of 7105 unique per-tumor features. Regularized logistic regression with implicit feature selection and leave pair out cross validation was used to discriminate tumors with 3+3 vs >3+3 GS.

Results

In total, 100 PCa lesions were analysed, of those 20 and 80 had GS of 3+3 and >3+3, respectively. The best model performance was obtained by selecting the top 1% features of T₂w, ADC_m and K with ROC AUC of 0.88 (95% CI of 0.82–0.95). Features from T₂ mapping provided little added value. The most useful texture features were based on the gray-level co-occurrence matrix, Gabor transform, and Zernike moments.

Conclusion

Texture feature analysis of DWI, post-processed using monoexponential and kurtosis models, and T₂w demonstrated good classification performance for GS of PCa. In multisequence setting, the optimal radiomics based texture extraction methods and parameters differed between different image types.

Validation of IMPROD biparametric MRI in men with clinically suspected prostate cancer: A prospective multi-institutional trial

BACKGROUND

Magnetic resonance imaging (MRI) combined with targeted biopsy (TB) is increasingly used in men with clinically suspected prostate cancer (PCa), but the long acquisition times, high costs, and inter-center/reader variability of routine multiparametric prostate MRI limit its wider adoption.

METHODS AND FINDINGS

The aim was to validate a previously developed unique MRI acquisition and reporting protocol, IMPROD biparametric MRI (bpMRI) (NCT01864135), in men with a clinical suspicion of PCa in a multi-institutional trial (NCT02241122). IMPROD bpMRI has average acquisition time of 15 minutes (no endorectal coil, no intravenous contrast use) and consists of T2-weighted imaging and 3 separate diffusion-weighed imaging acquisitions. Between February 1, 2015, and March 31, 2017, 364 men with a clinical suspicion of PCa were enrolled at 4 institutions in Finland. Men with an equivocal to high suspicion (IMPROD bpMRI Likert score 3-5) of PCa had 2 TBs of up to 2 lesions followed by a systematic biopsy (SB). Men with a low to very low suspicion (IMPROD bpMRI Likert score 1-2) had only SB. All data and protocols are freely available. The primary outcome of the trial was diagnostic accuracy-including overall accuracy, sensitivity, specificity, negative predictive value (NPV), and positive predictive value-of IMPROD bpMRI for clinically significant PCa (SPCa), which was defined as a Gleason score ≥ 3 + 4 (Gleason grade group 2 or higher). In total, 338 (338/364, 93%) prospectively enrolled men completed the trial. The accuracy and NPV of IMPROD bpMRI for SPCa were 70% (113/161) and 95% (71/75) (95% CI 87%-98%), respectively. Restricting the biopsy to men with equivocal to highly suspicious IMPROD bpMRI findings would have resulted in a 22% (75/338) reduction in the number of men undergoing biopsy while missing 4 (3%, 4/146) men with SPCa. The main limitation is uncertainty about the true PCa prevalence in the study cohort, since some of the men may have PCa despite having negative biopsy findings.

CONCLUSIONS

IMPROD bpMRI demonstrated a high NPV for SPCa in men with a clinical suspicion of PCa in this prospective multi-institutional clinical trial.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02241122.

Prospective evaluation of 18F-FACBC PET/CT and PET/MRI versus multiparametric MRI in intermediate- to high-risk prostate cancer patients (FLUCIPRO trial)

PURPOSE

The purpose of this study was to evaluate ¹⁸F-FACBC PET/CT, PET/MRI, and multiparametric MRI (mpMRI) in detection of primary prostate cancer (PCa).

METHODS

Twenty-six men with histologically confirmed PCa underwent PET/CT immediately after injection of 369 ± 10 MBq ¹⁸F-FACBC (fluciclovine) followed by PET/MRI started 55 ± 7 min from injection. Maximum standardized uptake values (SUV_max) were measured for both hybrid PET acquisitions. A separate mpMRI was acquired within a week of the PET scans. Logan plots were used to calculate volume of distribution (V_T). The presence of PCa was estimated in 12 regions with radical prostatectomy findings as ground truth. For each imaging modality, area under the curve (AUC) for detection of PCa was determined to predict diagnostic performance. The clinical trial registration number is NCT02002455.

RESULTS

In the visual analysis, 164/312 (53%) regions contained PCa, and 41 tumor foci were identified. PET/CT demonstrated the highest sensitivity at 87% while its specificity was low at 56%. The AUC of both PET/MRI and mpMRI significantly (p < 0.01) outperformed that of PET/CT while no differences were detected between PET/MRI and mpMRI. SUV_max and V_T of Gleason score (GS) >3 + 4 tumors were significantly (p < 0.05) higher than those for GS 3 + 3 and benign hyperplasia. A total of 442 lymph nodes were evaluable for staging, and PET/CT and PET/MRI demonstrated true-positive findings in only 1/7 patients with metastatic lymph nodes.

CONCLUSIONS

Quantitative ¹⁸F-FACBC imaging significantly correlated with GS but failed to outperform MRI in lesion detection. ¹⁸F-FACBC may assist in targeted biopsies in the setting of hybrid imaging with MRI.

Radiomic features for prostate cancer detection on MRI differ between the transition and peripheral zones: Preliminary findings from a multi-institutional study

PURPOSE

To evaluate in a multi-institutional study whether radiomic features useful for prostate cancer (PCa) detection from 3 Tesla (T) multi-parametric MRI (mpMRI) in the transition zone (TZ) differ from those in the peripheral zone (PZ).

MATERIALS AND METHODS

3T mpMRI, including T2-weighted (T2w), apparent diffusion coefficient (ADC) maps, and dynamic contrast-enhanced MRI (DCE-MRI), were retrospectively obtained from 80 patients at three institutions. This study was approved by the institutional review board of each participating institution. First-order statistical, co-occurrence, and wavelet features were extracted from T2w MRI and ADC maps, and contrast kinetic features were extracted from DCE-MRI. Feature selection was performed to identify 10 features for PCa detection in the TZ and PZ, respectively. Two logistic regression classifiers used these features to detect PCa and were evaluated by area under the receiver-operating characteristic curve (AUC). Classifier performance was compared with a zone-ignorant classifier.

RESULTS

Radiomic features that were identified as useful for PCa detection differed between TZ and PZ. When classification was performed on a per-voxel basis, a PZ-specific classifier detected PZ tumors on an independent test set with significantly higher accuracy (AUC = 0.61-0.71) than a zone-ignorant classifier trained to detect cancer throughout the entire prostate (P < 0.05). When classifiers were evaluated on MRI data from multiple institutions, statistically similar AUC values (P > 0.14) were obtained for all institutions.

CONCLUSION

A zone-aware classifier significantly improves the accuracy of cancer detection in the PZ.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:184-193.

Cerebral hemodynamics in a healthy population measured by dynamic susceptibility contrast MR imaging

Purpose: To establish reference data and to study age-dependency for cerebral perfusion in various regions of the brain in a healthy population.

Material and Methods: Eighty healthy subjects of both genders from 22 to 85 years of age were studied with spin echo echo-planar dynamic susceptibility contrast MR imaging (DSC MRI) at 1.5 T. Cerebral blood volume (CBV), cerebral blood flow (CBF), and contrast agent mean transit time (MTT) were calculated bilaterally for 20 distinct neuroanatomic structures.

Results: In gray matter, the following values were found (mean ± SD): CBV (4.6 ± 1.0 ml/100 g), CBF (94.2 ± 23.0 ml/100 g/min), and MTT (3.0 ± 0.6 s), and in white matter: CBV (1.3 ± 0.4 ml/100 g), CBF (19.6 ± 5.8 ml/100 g/min), and MTT (4.3 ± 0.7 s). The perfusion parameters did not change with age, except for a tendency to an increase in gray matter MTT and CBV. Males exhibited higher MTT and CBV than females. No hemispheric difference was found in either gender.

Conclusion: Cerebral hemodynamics can be assessed with DSC MRI. Age itself seems to have only a marginal effect on cerebral perfusion in healthy population.

Patient-specific pharmacokinetic parameter estimation on dynamic contrast-enhanced MRI of prostate: Preliminary evaluation of a novel AIF-free estimation method

PURPOSE

To develop and evaluate a prostate-based method (PBM) for estimating pharmacokinetic parameters on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) by leveraging inherent differences in pharmacokinetic characteristics between the peripheral zone (PZ) and transition zone (TZ).

MATERIALS AND METHODS

This retrospective study, approved by the Institutional Review Board, included 40 patients who underwent a multiparametric 3T MRI examination and subsequent radical prostatectomy. A two-step PBM for estimating pharmacokinetic parameters exploited the inherent differences in pharmacokinetic characteristics associated with the TZ and PZ. First, the reference region model was implemented to estimate ratios of K^trans between normal TZ and PZ. Subsequently, the reference region model was leveraged again to estimate values for K^trans and v_e for every prostate voxel. The parameters of PBM were compared with those estimated using an arterial input function (AIF) derived from the femoral arteries. The ability of the parameters to differentiate prostate cancer (PCa) from benign tissue was evaluated on a voxel and lesion level. Additionally, the effect of temporal downsampling of the DCE MRI data was assessed.

RESULTS

Significant differences (P < 0.05) in PBM K^trans between PCa lesions and benign tissue were found in 26/27 patients with TZ lesions and in 33/38 patients with PZ lesions; significant differences in AIF-based K^trans occurred in 26/27 and 30/38 patients, respectively. The 75^th and 100^th percentiles of K^trans and v_e estimated using PBM positively correlated with lesion size (P < 0.05).

CONCLUSION

Pharmacokinetic parameters estimated via PBM outperformed AIF-based parameters in PCa detection. J. Magn. Reson. Imaging 2016;44:1405-1414.

Fitting methods for intravoxel incoherent motion imaging of prostate cancer on region of interest level: Repeatability and gleason score prediction

PURPOSE

To evaluate different fitting methods for intravoxel incoherent motion (IVIM) imaging of prostate cancer in the terms of repeatability and Gleason score prediction.

METHODS

Eighty-one patients with histologically confirmed prostate cancer underwent two repeated 3 Tesla diffusion-weighted imaging (DWI) examinations performed using 14 b-values in the range of 0-500 s/mm² and diffusion time of 19.004 ms. Mean signal intensities of regions-of-interest were fitted using five different fitting methods for IVIM as well as monoexponential, kurtosis, and stretched exponential models. The fitting methods and models were evaluated in the terms of fitting quality [Akaike information criteria (AIC)], repeatability, and Gleason score prediction. Tumors were classified into three groups (3 + 3, 3 + 4, > 3 + 4). Machine learning algorithms were used to evaluate the performance of the combined use of the parameters. Simulation studies were performed to evaluate robustness of the fitting methods against noise.

RESULTS

Monoexponential model was preferred over IVIM based on AIC. The "pseudodiffusion" parameters demonstrated low repeatability and clinical value. Median "pseudodiffusion" fraction values were below 8.00%. Combined use of the parameters did not outperform the monoexponential model.

CONCLUSION

Monoexponential model demonstrated the highest repeatability and clinical values in the regions-of-interest based analysis of prostate cancer DWI, b-values in the range of 0-500 s/mm² . Magn Reson Med 77:1249-1264, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Diffusion-weighted imaging of prostate cancer: effect of b-value distribution on repeatability and cancer characterization

PURPOSE

To evaluate the effect of b-value distribution on the repeatability and Gleason score (GS) prediction of prostate cancer (PCa).

METHODS

Fifty PCa patients underwent two repeated 3T diffusion-weighted imaging (DWI) examinations using 12 b values in the range from 0 to 2000s/mm(2) and diffusion time of 20.3ms. Mean signal intensities of regions of interest, placed in PCa using whole mount prostatectomy sections as the reference, were fitted using monoexponential, kurtosis, stretched exponential, and biexponential models. In total, 4083 different b-value combinations consisting of 2 to 12 b values were evaluated. Repeatability was assessed by intraclass correlation coefficient, ICC(3,1), and coefficient of repeatability (CoR). Areas under receiver operating characteristic curve (AUCs) for PCa characterization were estimated while the correlation of the fitted values with GS groups (3+3, 3+4, >3+4) was evaluated by using the Spearman correlation coefficient (ρ).

RESULTS

The parameters of monoexponential, kurtosis, and stretched exponential models estimated using only 4-5, 5-7, 5-7 b values, respectively, had similar ICC(3,1), CoR, AUC, and ρ values as the parameters estimated using all 12 b values. Optimized b-value distributions demonstrated improved ICC(3,1) and CoR values but failed to improve AUC and ρ values. The parameters of biexponential model demonstrated the worst repeatability and diagnostic performance.

CONCLUSION

B-value distribution influences mainly the repeatability of DWI-derived parameters rather than the diagnostic performance.

Relaxation along fictitious field, diffusion-weighted imaging, and T2 mapping of prostate cancer: Prediction of cancer aggressiveness

PURPOSE

To evaluate the performance of relaxation along a fictitious field (RAFF) relaxation time (TRAFF ), diffusion-weighted imaging (DWI)-derived parameters, and T2 relaxation time values for prostate cancer (PCa) detection and characterization.

METHODS

Fifty patients underwent 3T MR examination using surface array coils before prostatectomy. DWI was performed using 14 and 12 b values in the ranges of 0-500 s/mm(2) and 0-2000 s/mm(2) , respectively. Repeated MR examination was performed in 16 patients. TRAFF , DWI-derived parameters (monoexponential, kurtosis, biexponential models), and T2 values were measured and averaged over regions of interest placed in PCa and normal tissue. Repeatability of TRAFF and DWI-derived parameters were assessed by coefficient of repeatability and intraclass correlation coefficient ICC(3,1). Areas under the receiver operating characteristic curve (AUCs) for PCa detection and Gleason score classification were estimated. The parameters were correlated with Gleason score groups using Spearman correlation coefficient (ρ).

RESULTS

ICC(3,1) values for TRAFF were in the range of 0.82-0.92. TRAFF values had higher AUC values for Gleason score classification compared with DWI-derived parameters and T2 . The RAFF method demonstrated the highest ρ value (-0.65).

CONCLUSION

In a quantitative region of interest-based analysis, RAFF outperformed DWI ("low" and "high" b values) and T2 mapping in the characterization of PCa.

Prospective evaluation of planar bone scintigraphy, SPECT, SPECT/CT, 18F-NaF PET/CT and whole body 1.5T MRI, including DWI, for the detection of bone metastases in high risk breast and prostate cancer patients: SKELETA clinical trial

PURPOSE

Detection of bone metastases in breast and prostate cancer patients remains a major clinical challenge. The aim of the current trial was to compare the diagnostic accuracy of (99m)Tc-hydroxymethane diphosphonate ((99m)Tc-HDP) planar bone scintigraphy (BS), (99m)Tc-HDP SPECT, (99m)Tc-HDP SPECT/CT, (18)F-NaF PET/CT and whole body 1.5 Tesla magnetic resonance imaging (MRI), including diffusion weighted imaging, (wbMRI+DWI) for the detection of bone metastases in high risk breast and prostate cancer patients.

MATERIAL AND METHODS

Twenty-six breast and 27 prostate cancer patients at high risk of bone metastases underwent (99m)Tc-HDP BS, (99m)Tc-HDP SPECT, (99m)Tc-HDP SPECT/CT, (18)F-NaF PET/CT and wbMRI+DWI. Five independent reviewers interpreted each individual modality without the knowledge of other imaging findings. The final metastatic status was based on the consensus reading, clinical and imaging follow-up (minimal and maximal follow-up time was 6, and 32 months, respectively). The bone findings were compared on patient-, region-, and lesion-level.

RESULTS

(99m)Tc-HDP BS was false negative in four patients. In the region-based analysis, sensitivity values for (99m)Tc-HDP BS, (99m)Tc-HDP SPECT, (99m)Tc-HDP SPECT/CT, (18)F-NaF PET/CT, and wbMRI+DWI were 62%, 74%, 85%, 93%, and 91%, respectively. The number of equivocal findings for (99m)Tc-HDP BS, (99m)Tc-HDP SPECT, (99m)Tc-HDP SPECT/CT, (18)F-NaF PET/CT and wbMRI+DWI was 50, 44, 5, 6, and 4, respectively.

CONCLUSION

wbMRI+DWI showed similar diagnostic accuracy to (18)F-NaF PET/CT and outperformed (99m)Tc-HDP SPECT/CT, and (99m)Tc-HDP BS.

Rotating frame relaxation imaging of prostate cancer: Repeatability, cancer detection, and Gleason score prediction

PURPOSE

To investigate relaxation along a fictitious field (RAFF) and continuous wave (cw) T1ρ imaging of prostate cancer (PCa) in the terms of repeatability, PCa detection, and characterization.

METHODS

Thirty-six patients (PSA 11.6 ± 7.6 ng/mL, mean ± standard deviation) with histologically confirmed PCa underwent two repeated 3T MR examinations using surface array coils before prostatectomy. Relaxation along fictitious field, cw T1ρ, and T2 relaxation times (TRAFF, T1ρcw, T2) were measured and averaged over regions of interest placed in PCa, normal peripheral zone (PZ), and normal central gland (CG) positioned using whole-mount prostatectomy sections and anatomical T2-weighted images. Receiver operating characteristic curve analysis with area under the curve (AUC) was calculated to distinguish PCa from PZ/CG and PCa with Gleason score (GS) of 3+3 from GS of 3+4/≥ 3+4.

RESULTS

TRAFF and T1ρcw relaxation times were repeatable with coefficients of repeatability as a percentage of median value in the range of 7.8-23.2%. AUC (mean, 95% confidence interval) in the differentiation of PCa with GS of 3+3 from PCa with CS of ≥ 3+4 were 0.88 (0.72-0.99), 0.69 (0.46-0.90), and 0.68 (0.45-0.88), for TRAFF, T1ρcw, and T2, respectively.

CONCLUSION

In quantitative region of interest based analysis, TRAFF outperformed T1ρcw and T2 in PCa detection and characterization.

Evaluation of different mathematical models for diffusion-weighted imaging of normal prostate and prostate cancer using high b-values: a repeatability study

PURPOSE

To evaluate monoexponential, stretched exponential, kurtosis, and biexponential models for diffusion-weighted imaging (DWI) of normal prostate and prostate cancer (PCa), using b-values up to 2000 s/mm(2) , in terms of fitting quality and repeatability.

METHODS

Eight healthy volunteers and 16 PCa patients underwent a total of four repeated 3T DWI examinations using 16 and 12 b-values, respectively. The highest b-value was 2000 s/mm(2) . The normalized mean signal intensities of regions of interest, placed in normal tissue and PCa using anatomical images and prostatectomy sections, were fitted using the four models. The fitting quality was evaluated using Akaike information criteria and F-ratio. Repeatability of the fitted parameters was evaluated using intraclass correlation coefficient ICC(3,1).

RESULTS

The biexponential model provided the best fit to normal prostate and PCa DWI data. The parameters of the monoexponential, kurtosis, and stretched exponential (with the exception of the α parameter) models had higher ICC(3,1) values compared with the biexponential model. The kurtosis model provided a better fit to DWI data of normal prostate and PCa than the monoexponential model, whereas these models had comparable reliability and repeatability based on ICC(3,1) values.

CONCLUSION

Considering the model fit and repeatability, the kurtosis model seems to be the preferred model for characterization of normal prostate and PCa DWI using b-values up to 2000 s/mm(2) .

Prebiopsy multiparametric 3T prostate MRI in patients with elevated PSA, normal digital rectal examination, and no previous biopsy

PURPOSE

To find the diagnostic accuracy of 3T multiparametric magnetic resonance imaging (mpMRI) and mpMRI targeted transrectal ultrasound (TRUS)-guided biopsy using visual coregistration (TB) in patients with elevated prostate-specific antigen (PSA), normal digital rectal examination, and no previous biopsy.

MATERIALS AND METHODS

Fifty-five patients at two institutions underwent mpMRI, consisting of anatomical T2 -weighted imaging (T2 W), diffusion-weighted imaging (DWI), proton magnetic resonance spectroscopy ((1) H-MRS), and dynamic contrast-enhanced MRI (DCE-MRI), followed by TB in addition to 12 core systematic TRUS-guided biopsy (SB). Histopathological scorings of biopsy (n = 38) and prostatectomy (n = 17) specimens were used as the reference standard for calculation of diagnostic accuracy values. Clinically significant prostate cancer (SPCa) was defined as 3 mm core length of Gleason score 3+3 or any Gleason grade 4.

RESULTS

The sensitivity, specificity, accuracy, and area under the curve (AUC) values for the detection of SPCa on the sextant level for T2 W+DWI+(1) H-MRS+DCE-MRI were 72%, 89%, 85%, and 0.81, respectively. The corresponding values for T2 wi+DWI were 61%, 96%, 87%, and 0.79, respectively. The overall PCa detection rate per core in 53 patients was 21% (138 of 648 cores) for SB and 43% (33 of 77 cores) for TB (P < 0.001).

CONCLUSION

Prebiopsy mpMRI is an accurate tool for PCa detection and biopsy targeting in patients with elevated PSA.

Cavum septum pellucidum and psychopathy

The presence of cavum septum pellucidum (CSP) has been reported to be a neurodevelopmental marker of psychopathy. We scanned 26 violent offenders and 25 controls; 2 offenders and 2 controls had CSP (8% in both groups). Thus, the presence of CSP is not a common or a unique feature of antisocial personality disorder or psychopathy.

Atypical nucleus accumbens morphology in psychopathy: another limbic piece in the puzzle

Psychopathy has been associated with increased putamen and striatum volumes. The nucleus accumbens - a key structure in reversal learning, less effective in psychopathy - has not yet received specific attention. Moreover, basal ganglia morphology has never been explored. We examined the morphology of the caudate, putamen and accumbens, manually segmented from magnetic resonance images of 26 offenders (age: 32.5 ± 8.4) with medium-high psychopathy (mean PCL-R=30 ± 5) and 25 healthy controls (age: 34.6 ± 10.8). Local differences were statistically modeled using a surface-based radial distance mapping method (p<0.05; multiple comparisons correction through permutation tests). In psychopathy, the caudate and putamen had normal global volume, but different morphology, significant after correction for multiple comparisons, for the right dorsal putamen (permutation test: p=0.02). The volume of the nucleus accumbens was 13% smaller in psychopathy (p corrected for multiple comparisons <0.006). The atypical morphology consisted of predominant anterior hypotrophy bilaterally (10-30%). Caudate and putamen local morphology displayed negative correlation with the lifestyle factor of the PCL-R (permutation test: p=0.05 and 0.03). From these data, psychopathy appears to be associated with an atypical striatal morphology, with highly significant global and local differences of the accumbens. This is consistent with the clinical syndrome and with theories of limbic involvement.

Improved detection of localized prostate cancer using co-registered MRI and 11C-acetate PET/CT

OBJECTIVES

We aimed to study the ability of contrast enhanced MRI at 1.5 T and 11C-acetate PET/CT, both individually and using fused data, to detect localized prostate cancer.

METHODS

Thirty-six men with untreated prostate cancer and negative for metastatic disease on pelvic CT and bone scan were prospectively enrolled. A pelvic 11C-acetate PET/CT scan was performed in all patients, and a contrast enhanced MRI scan in 33 patients (6 examinations using both endorectal coil and surface coils, and 27 examinations using surface coils only). After the imaging studies 10 patients underwent prostatectomy and 26 were treated by image guided external beam radiation treatment. Image fusion of co-registered PET and MRI data was performed based on anatomical landmarks visible on CT and MRI using an advanced in-house developed software package. PET/CT, MRI and fused PET/MRI data were evaluated visually and compared with biopsy findings on a lobar level, while a sextant approach was used for patients undergoing prostatectomy.

RESULTS

When using biopsy samples as method of reference, the sensitivity, specificity and accuracy for visual detection of prostate cancer on a lobar level by contrast enhanced MRI was 85%, 37%, 73% and that of 11C-acetate PET/CT 88%, 41%, 74%, respectively. Fusion of PET with MRI data increased sensitivity, specificity and accuracy to 90%, 72% and 85%, respectively.

CONCLUSIONS

Fusion of sequentially obtained PET/CT and MRI data for the localization of prostate cancer is feasible and superior to the performance of each individual modality alone.

Cortex and amygdala morphology in psychopathy

Psychopathy is characterized by abnormal emotional processes, but only recent neuroimaging studies have investigated its cerebral correlates. The study aim was to map local differences of cortical and amygdalar morphology. Cortical pattern matching and radial distance mapping techniques were used to analyze the magnetic resonance images of 26 violent male offenders (age: 32±8) with psychopathy diagnosed using the Psychopathy Checklist-Revised (PCL-R) and no schizophrenia spectrum disorders, and in matched controls (age: 35± sp="0.12"/>11). The cortex displayed up to 20% reduction in the orbitofrontal and midline structures (corrected p<0.001 bilaterally). Up to 30% tissue reduction in the basolateral nucleus, and 10-30% enlargement effects in the central and lateral nuclei indicated abnormal structure of the amygdala (corrected p=0.05 on the right; and symmetrical pattern on the left). Psychopathy features specific morphology of the main cerebral structures involved in cognitive and emotional processing, consistent with clinical and functional data, and with a hypothesis of an alternative evolutionary brain development.

Frontal lobe white matter hyperintensities and neurofibrillary pathology in the oldest old

BACKGROUND

Current studies suggest an interaction between vascular mechanisms and neurodegenerative processes that leads to late-onset Alzheimer disease (AD). We tested whether AD pathology was associated with white matter hyperintensities (WMH) or cerebral infarcts in the oldest old individuals.

METHODS

Brains from 132 subjects over 85 years old, who came to autopsy from the Vantaa 85+ population-based cohort, were scanned by postmortem MRI and examined for neuropathologic changes. Coronal images were analyzed to determine the degree of frontal and parietal periventricular WMH (PVWMH) and deep WMH (DWMH) and cerebral infarcts. Neuropathologic variables included Consortium to Establish a Registry for Alzheimer's Disease scores for neuritic plaques and Braak staging among subjects in 5 groups: normal aging (NA), borderline with insufficient AD pathology, AD, AD plus other pathology, and other primary degenerative diseases.

RESULTS

Frontal DWMH were detected in >50% of the sample. Both frontal PVWMH and DWMH were significantly more extensive in the AD group compared to the NA group or the NA and borderline groups combined. Frontal PVWMH and DWMH were also associated with increased Braak staging (p = 0.03) and the neuritic plaque load (p = 0.01). Further analysis revealed there were a greater number of cerebral infarcts associated with frontal DWMH (p = 0.03) but not with frontal PVWMH.

CONCLUSIONS

Our study showed an association between neurofibrillary pathology and frontal PVWMH and DWMH (rather than parietal), as a surrogate of small vessel disease, particularly in very old community-dwelling individuals.

Functional imaging of localized prostate cancer aggressiveness using 11C-acetate PET/CT and 1H-MR spectroscopy

We assessed the ability of (11)C-acetate PET/CT, MRI, and proton MR spectroscopy ((1)H-MRS) to image localized prostate cancer and detect its aggressiveness, using qualitative and quantitative approaches.

METHODS

Twenty-one patients with untreated localized prostate cancer, diagnosed using transrectal ultrasound-guided biopsy, were prospectively enrolled. Cancer laterality was based on the percentage of cancer and the highest Gleason score determined from biopsies. In addition to PET/CT, 3-dimensional (1)H-MRS of the entire prostate volume using a quantitative approach was performed. The imaging and histologic findings of 8 patients undergoing subsequent prostatectomy were compared on a sextant level. For each lobe and sextant, standardized uptake values (SUVs) and (choline + creatine + polyamines)-to-citrate (CCP/C) ratios were obtained from (11)C-acetate PET/CT and (1)H-MRS, respectively. The visual and quantitative findings on PET/CT and MRI data were compared with cancer laterality and aggressiveness based on the Gleason score and with prostate-specific antigen (PSA) velocity and international risk group classification.

RESULTS

The sensitivity, specificity, and accuracy, on a lobar level using visual analysis, of (11)C-acetate PET/CT were 80%, 29%, 71%, respectively, and 89%, 29%, 79%, respectively, using contrast-enhanced MRI. The sensitivity and accuracy of (11)C-acetate PET/CT decreased to 64% and 63% and specificity increased to 62% when sextant analysis was performed. The agreement between prostate cancer laterality based on biopsy findings and visual interpretation of (11)C-acetate PET/CT and contrast-enhanced MRI was similar at 71%. The mean SUV maximum and CCP/C maximum for the dominant tumor lesion were 5.5 and 1.48, respectively, and did not differ significantly from values in the nondominant lobe. The dominant-lesion SUVs or CCP/C values were not associated with histologically determined prostate cancer aggressiveness, nor did PSA velocity correlate with the SUV or CCP/C values from the entire gland.

CONCLUSION

(11)C-acetate PET/CT, MRI, and (1)H-MRS enable detection of localized prostate cancer with comparable and limited accuracy but fail to provide information on cancer aggressiveness.

Abnormal hippocampal shape in offenders with psychopathy

Posterior hippocampal volumes correlate negatively with the severity of psychopathy, but local morphological features are unknown. The aim of this study was to investigate hippocampal morphology in habitually violent offenders having psychopathy. Manual tracings of hippocampi from magnetic resonance images of 26 offenders (age: 32.5 +/- 8.4), with different degrees of psychopathy (12 high, 14 medium psychopathy based on the Psychopathy Checklist Revised), and 25 healthy controls (age: 34.6 +/- 10.8) were used for statistical modelling of local changes with a surface-based radial distance mapping method. Both offenders and controls had similar hippocampal volume and asymmetry ratios. Local analysis showed that the high psychopathy group had a significant depression along the longitudinal hippocampal axis, on both the dorsal and ventral aspects, when compared with the healthy controls and the medium psychopathy group. The opposite comparison revealed abnormal enlargement of the lateral borders in both the right and left hippocampi of both high and medium psychopathy groups versus controls, throughout CA1, CA2-3 and the subicular regions. These enlargement and reduction effects survived statistical correction for multiple comparisons in the main contrast (26 offenders vs. 25 controls) and in most subgroup comparisons. A statistical check excluded a possible confounding effect from amphetamine and polysubstance abuse. These results indicate that habitually violent offenders exhibit a specific abnormal hippocampal morphology, in the absence of total gray matter volume changes, that may relate to different autonomic modulation and abnormal fear-conditioning.

Brain anatomy of persistent violent offenders: more rather than less

Most violent crimes in Western societies are committed by a small group of men who display antisocial behavior from an early age that remains stable across the life-span. It is not known if these men display abnormal brain structure. We compared regional brain volumes of 26 persistently violent offenders with antisocial personality disorder and substance dependence and 25 healthy men using magnetic resonance imaging volumetry and voxel-based morphometry (VBM). The violent offenders, as compared with the healthy men, had markedly larger white matter volumes, bilaterally, in the occipital and parietal lobes, and in the left cerebellum, and larger grey matter volume in right cerebellum (effect sizes up to 1.24, P<0.001). Among the offenders, volumes of these areas were not associated with psychopathy scores, substance abuse, psychotropic medication, or global IQ scores. By contrast, VBM analyses of grey matter revealed focal, symmetrical, bilateral areas of atrophy in the postcentral gyri, frontopolar cortex, and orbitofrontal cortex among the offenders as compared with the healthy men (z-scores as high as 5.06). Offenders with psychopathy showed the smallest volumes in these areas. The larger volumes in posterior brain areas may reflect atypical neurodevelopmental processes that underlie early-onset persistent antisocial and aggressive behavior.