Correction to: Machine learning classifiers can predict Gleason pattern 4 prostate cancer with greater accuracy than experienced radiologists.

The original version of this article, published on 11 June 2019, unfortunately contained a mistake. The following correction has therefore been made in the original: In section "Multiparametric MRI review," the readers mentioned in the first sentence were partly incorrect.

Machine learning classifiers can predict Gleason pattern 4 prostate cancer with greater accuracy than experienced radiologists.

OBJECTIVE: The purpose of this study was: To test whether machine learning classifiers for transition zone (TZ) and peripheral zone (PZ) can correctly classify prostate tumors into those with/without a Gleason 4 component, and to compare the performance of the best performing classifiers against the opinion of three board-certified radiologists. METHODS: A retrospective analysis of prospectively acquired data was performed at a single center between 2012 and 2015. Inclusion criteria were (i) 3-T mp-MRI compliant with international guidelines, (ii) Likert ≥ 3/5 lesion, (iii) transperineal template ± targeted index lesion biopsy confirming cancer ≥ Gleason 3 + 3. Index lesions from 164 men were analyzed (119 PZ, 45 TZ). Quantitative MRI and clinical features were used and zone-specific machine learning classifiers were constructed. Models were validated using a fivefold cross-validation and a temporally separated patient cohort. Classifier performance was compared against the opinion of three board-certified radiologists. RESULTS: The best PZ classifier trained with prostate-specific antigen density, apparent diffusion coefficient (ADC), and maximum enhancement (ME) on DCE-MRI obtained a ROC area under the curve (AUC) of 0.83 following fivefold cross-validation. Diagnostic sensitivity at 50% threshold of specificity was higher for the best PZ model (0.93) when compared with the mean sensitivity of the three radiologists (0.72). The best TZ model used ADC and ME to obtain an AUC of 0.75 following fivefold cross-validation. This achieved higher diagnostic sensitivity at 50% threshold of specificity (0.88) than the mean sensitivity of the three radiologists (0.82). CONCLUSIONS: Machine learning classifiers predict Gleason pattern 4 in prostate tumors better than radiologists. KEY POINTS: • Predictive models developed from quantitative multiparametric magnetic resonance imaging regarding the characterization of prostate cancer grade should be zone-specific. • Classifiers trained differently for peripheral and transition zone can predict a Gleason 4 component with a higher performance than the subjective opinion of experienced radiologists. • Classifiers would be particularly useful in the context of active surveillance, whereby decisions regarding whether to biopsy are necessitated.

Diagnostic accuracy of whole-body MRI versus standard imaging pathways for metastatic disease in newly diagnosed colorectal cancer: the prospective Streamline C trial.

BACKGROUND: Whole-body MRI (WB-MRI) could be an alternative to multimodality staging of colorectal cancer, but its diagnostic accuracy, effect on staging times, number of tests needed, cost, and effect on treatment decisions are unknown. We aimed to prospectively compare the diagnostic accuracy and efficiency of WB-MRI-based staging pathways with standard pathways in colorectal cancer. METHODS: The Streamline C trial was a prospective, multicentre trial done in 16 hospitals in England. Eligible patients were 18 years or older, with newly diagnosed colorectal cancer. Exclusion criteria were severe systemic disease, pregnancy, contraindications to MRI, or polyp cancer. Patients underwent WB-MRI, the result of which was withheld until standard staging investigations were complete and the first treatment decision made. The multidisciplinary team recorded its treatment decision based on standard investigations, then on the WB-MRI staging pathway (WB-MRI plus additional tests generated), and finally on all tests. The primary outcome was difference in per-patient sensitivity for metastases between standard and WB-MRI staging pathways against a consensus reference standard at 12 months, in the per-protocol population. Secondary outcomes were difference in per-patient specificity for metastatic disease detection between standard and WB-MRI staging pathways, differences in treatment decisions, staging efficiency (time taken, test number, and costs), and per-organ sensitivity and specificity for metastases and per-patient agreement for local T and N stage. This trial is registered with the International Standard Randomised Controlled Trial registry, number ISRCTN43958015, and is complete. FINDINGS: Between March 26, 2013, and Aug 19, 2016, 1020 patients were screened for eligibility. 370 patients were recruited, 299 of whom completed the trial; 68 (23%) had metastasis at baseline. Pathway sensitivity was 67% (95% CI 56 to 78) for WB-MRI and 63% (51 to 74) for standard pathways, a difference in sensitivity of 4% (-5 to 13, p=0·51). No adverse events related to imaging were reported. Specificity did not differ between WB-MRI (95% [95% CI 92-97]) and standard pathways (93% [90-96], p=0·48). Agreement with the multidisciplinary team's final treatment decision was 96% for WB-MRI and 95% for the standard pathway. Time to complete staging was shorter for WB-MRI (median, 8 days [IQR 6-9]) than for the standard pathway (13 days [11-15]); a 5-day (3-7) difference. WB-MRI required fewer tests (median, one [95% CI 1 to 1]) than did standard pathways (two [2 to 2]), a difference of one (1 to 1). Mean per-patient staging costs were £216 (95% CI 211-221) for WB-MRI and £285 (260-310) for standard pathways. INTERPRETATION: WB-MRI staging pathways have similar accuracy to standard pathways and reduce the number of tests needed, staging time, and cost. FUNDING: UK National Institute for Health Research.

Diagnostic accuracy of whole-body MRI versus standard imaging pathways for metastatic disease in newly diagnosed non-small-cell lung cancer: the prospective Streamline L trial.

BACKGROUND: Whole-body magnetic resonance imaging (WB-MRI) could be an alternative to multi-modality staging of non-small-cell lung cancer (NSCLC), but its diagnostic accuracy, effect on staging times, number of tests needed, cost, and effect on treatment decisions are unknown. We aimed to prospectively compare the diagnostic accuracy and efficiency of WB-MRI-based staging pathways with standard pathways in NSCLC. METHODS: The Streamline L trial was a prospective, multicentre trial done in 16 hospitals in England. Eligible patients were 18 years or older, with newly diagnosed NSCLC that was potentially radically treatable on diagnostic chest CT (defined as stage IIIb or less). Exclusion criteria were severe systemic disease, pregnancy, contraindications to MRI, or histologies other than NSCLC. Patients underwent WB-MRI, the result of which was withheld until standard staging investigations were complete and the first treatment decision made. The multidisciplinary team recorded its treatment decision based on standard investigations, then on the WB-MRI staging pathway (WB-MRI plus additional tests generated), and finally on all tests. The primary outcome was difference in per-patient sensitivity for metastases between standard and WB-MRI staging pathways against a consensus reference standard at 12 months, in the per-protocol population. Secondary outcomes were difference in per-patient specificity for metastatic disease detection between standard and WB-MRI staging pathways, differences in treatment decisions, staging efficiency (time taken, test number, and costs) and per-organ sensitivity and specificity for metastases and per-patient agreement for local T and N stage. This trial is registered with the International Standard Randomised Controlled Trial registry, number ISRCTN50436483, and is complete. FINDINGS: Between Feb 26, 2013, and Sept 5, 2016, 976 patients were screened for eligibility. 353 patients were recruited, 187 of whom completed the trial; 52 (28%) had metastasis at baseline. Pathway sensitivity was 50% (95% CI 37-63) for WB-MRI and 54% (41-67) for standard pathways, a difference of 4% (-7 to 15, p=0·73). No adverse events related to imaging were reported. Specificity did not differ between WB-MRI (93% [88-96]) and standard pathways (95% [91-98], p=0·45). Agreement with the multidisciplinary team's final treatment decision was 98% for WB-MRI and 99% for the standard pathway. Time to complete staging was shorter for WB-MRI (13 days [12-14]) than for the standard pathway (19 days [17-21]); a 6-day (4-8) difference. The number of tests required was similar WB-MRI (one [1-1]) and standard pathways (one [1-2]). Mean per-patient costs were £317 (273-361) for WBI-MRI and £620 (574-666) for standard pathways. INTERPRETATION: WB-MRI staging pathways have similar accuracy to standard pathways, and reduce the staging time and costs. FUNDING: UK National Institute for Health Research.

VERDICT MRI for Prostate Cancer: Intracellular Volume Fraction versus Apparent Diffusion Coefficient.

Background Biologic specificity of diffusion MRI in relation to prostate cancer aggressiveness may improve by examining separate components of the diffusion MRI signal. The Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumors (VERDICT) model estimates three distinct signal components and associates them to (a) intracellular water, (b) water in the extracellular extravascular space, and (c) water in the microvasculature. Purpose To evaluate the repeatability, image quality, and diagnostic utility of intracellular volume fraction (FIC) maps obtained with VERDICT prostate MRI and to compare those maps with apparent diffusion coefficient (ADC) maps for Gleason grade differentiation. Materials and Methods Seventy men (median age, 62.2 years; range, 49.5-82.0 years) suspected of having prostate cancer or undergoing active surveillance were recruited to a prospective study between April 2016 and October 2017. All men underwent multiparametric prostate and VERDICT MRI. Forty-two of the 70 men (median age, 67.7 years; range, 50.0-82.0 years) underwent two VERDICT MRI acquisitions to assess repeatability of FIC measurements obtained with VERDICT MRI. Repeatability was measured with use of intraclass correlation coefficients (ICCs). The image quality of FIC and ADC maps was independently evaluated by two board-certified radiologists. Forty-two men (median age, 64.8 years; range, 49.5-79.6 years) underwent targeted biopsy, which enabled comparison of FIC and ADC metrics in the differentiation between Gleason grades. Results VERDICT MRI FIC demonstrated ICCs of 0.87-0.95. There was no significant difference between image quality of ADC and FIC maps (score, 3.1 vs 3.3, respectively; P = .90). FIC was higher in lesions with a Gleason grade of at least 3+4 compared with benign and/or Gleason grade 3+3 lesions (mean, 0.49 ± 0.17 vs 0.31 ± 0.12, respectively; P = .002). The difference in ADC between these groups did not reach statistical significance (mean, 1.42 vs 1.16 × 10-3 mm2/sec; P = .26). Conclusion Fractional intracellular volume demonstrates high repeatability and image quality and enables better differentiation of a Gleason 4 component cancer from benign and/or Gleason 3+3 histology than apparent diffusion coefficient. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Sigmund and Rosenkrantz in this issue.

Multi-parametric MRI zone-specific diagnostic model performance compared with experienced radiologists for detection of prostate cancer.

OBJECTIVES: Compare the performance of zone-specific multi-parametric-MRI (mp-MRI) diagnostic models in prostate cancer detection with experienced radiologists. METHODS: A single-centre, IRB approved, prospective STARD compliant 3 T MRI test dataset of 203 patients was generated to test validity and generalisability of previously reported 1.5 T mp-MRI diagnostic models. All patients included within the test dataset underwent 3 T mp-MRI, comprising T2, diffusion-weighted and dynamic contrast-enhanced imaging followed by transperineal template ± targeted index lesion biopsy. Separate diagnostic models (transition zone (TZ) and peripheral zone (PZ)) were applied to respective zones. Sensitivity/specificity and the area under the receiver operating characteristic curve (ROC-AUC) were calculated for the two zone-specific models. Two radiologists (A and B) independently Likert scored test 3 T mp-MRI dataset, allowing ROC analysis for each radiologist for each prostate zone. RESULTS: Diagnostic models applied to the test dataset demonstrated a ROC-AUC = 0.74 (95% CI 0.67-0.81) in the PZ and 0.68 (95% CI 0.61-0.75) in the TZ. Radiologist A/B had a ROC-AUC = 0.78/0.74 in the PZ and 0.69/0.69 in the TZ. Radiologists A and B each scored 51 patients in the PZ and 41 and 45 patients respectively in the TZ as Likert 3. The PZ model demonstrated a ROC-AUC = 0.65/0.67 for the patients Likert scored as indeterminate by radiologist A/B respectively, whereas the TZ model demonstrated a ROC-AUC = 0.74/0.69. CONCLUSION: Zone-specific mp-MRI diagnostic models demonstrate generalisability between 1.5 and 3 T mp-MRI protocols and show similar classification performance to experienced radiologists for prostate cancer detection. Results also indicate the ability of diagnostic models to classify cases with an indeterminate radiologist score. KEY POINTS: • MRI diagnostic models had similar performance to experienced radiologists for classification of prostate cancer. • MRI diagnostic models may help radiologists classify tumour in patients with indeterminate Likert 3 scores.

The SmartTarget Biopsy Trial: A Prospective, Within-person Randomised, Blinded Trial Comparing the Accuracy of Visual-registration and Magnetic Resonance Imaging/Ultrasound Image-fusion Targeted Biopsies for Prostate Cancer Risk Stratification.

BACKGROUND: Multiparametric magnetic resonance imaging (mpMRI)-targeted prostate biopsies can improve detection of clinically significant prostate cancer and decrease the overdetection of insignificant cancers. It is unknown whether visual-registration targeting is sufficient or augmentation with image-fusion software is needed. OBJECTIVE: To assess concordance between the two methods. DESIGN, SETTING, AND PARTICIPANTS: We conducted a blinded, within-person randomised, paired validating clinical trial. From 2014 to 2016, 141 men who had undergone a prior (positive or negative) transrectal ultrasound biopsy and had a discrete lesion on mpMRI (score 3-5) requiring targeted transperineal biopsy were enrolled at a UK academic hospital; 129 underwent both biopsy strategies and completed the study. INTERVENTION: The order of performing biopsies using visual registration and a computer-assisted MRI/ultrasound image-fusion system (SmartTarget) on each patient was randomised. The equipment was reset between biopsy strategies to mitigate incorporation bias. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The proportion of clinically significant prostate cancer (primary outcome: Gleason pattern ≥3+4=7, maximum cancer core length ≥4mm; secondary outcome: Gleason pattern ≥4+3=7, maximum cancer core length ≥6mm) detected by each method was compared using McNemar's test of paired proportions. RESULTS AND LIMITATIONS: The two strategies combined detected 93 clinically significant prostate cancers (72% of the cohort). Each strategy detected 80/93 (86%) of these cancers; each strategy identified 13 cases missed by the other. Three patients experienced adverse events related to biopsy (urinary retention, urinary tract infection, nausea, and vomiting). No difference in urinary symptoms, erectile function, or quality of life between baseline and follow-up (median 10.5 wk) was observed. The key limitations were lack of parallel-group randomisation and a limit on the number of targeted cores. CONCLUSIONS: Visual-registration and image-fusion targeting strategies combined had the highest detection rate for clinically significant cancers. Targeted prostate biopsy should be performed using both strategies together. PATIENT SUMMARY: We compared two prostate cancer biopsy strategies: visual registration and image fusion. A combination of the two strategies found the most clinically important cancers and should be used together whenever targeted biopsy is being performed.

Simplified Luminal Water Imaging for the Detection of Prostate Cancer From Multiecho T2 MR Images.

BACKGROUND: Luminal water imaging (LWI) suffers less from imaging artifacts than the diffusion-weighted imaging used in multiparametric MRI of the prostate. LWI obtains multicompartment tissue information from a multiecho T2 dataset. PURPOSE: To compare a simplified LWI technique with apparent diffusion coefficient (ADC) in classifying lesions based on groupings of PI-RADS v2 scores. Secondary aims were to investigate whether LWI differentiates between histologically confirmed tumor and normal tissue as effectively as ADC, and whether LWI is correlated with the multicompartment parameters of the vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT) diffusion model. STUDY TYPE: A subset of a larger prospective study. POPULATION: In all, 65 male patients aged 49-79 were scanned. FIELD STRENGTH/SEQUENCE: A 32-echo T2 and a six b-value diffusion sequence (0, 90, 500, 1500, 2000, 3000 s/mm2 ) at 3T. ASSESSMENT: Regions of interest were placed by a board-certified radiologist in areas of lesion and benign tissue and given PI-RADS v2 scores. STATISTICAL TESTS: Receiver operating characteristic and logistic regression analyses were performed. RESULTS: LWI classifies tissue as PI-RADS 1,2 or PI-RADS 3,4,5 with an area under curve (AUC) value of 0.779, compared with 0.764 for ADC. LWI differentiated histologically confirmed malignant from nonmalignant tissue with AUC, sensitivity, and specificity values of 0.81, 75%, and 87%, compared with 0.75, 83%, and 67% for ADC. The microstructural basis of the LWI technique is further suggested by the correspondence with the VERDICT diffusion-based microstructural imaging technique, with α, A1 , A2 , and LWF showing significant correlations. DATA CONCLUSION: LWI alone can predict PI-RADS v2 score groupings and detect histologically confirmed tumors with an ability similar to ADC alone without the limitations of diffusion-weighted MRI. This is important, given that ADC has an advantage in these tests as it already informs PI-RADS v2 scoring. LWI also provides multicompartment information that has an explicit biophysical interpretation, unlike ADC. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:910-917.

Characterizing indeterminate (Likert-score 3/5) peripheral zone prostate lesions with PSA density, PI-RADS scoring and qualitative descriptors on multiparametric MRI.

OBJECTIVE: To determine whether indeterminate (Likert-score 3/5) peripheral zone (PZ) multiparametric MRI (mpMRI) studies are classifiable by prostate-specific antigen (PSA), PSA density (PSAD), Prostate Imaging Reporting And Data System version 2 (PI-RADS_v2) rescoring and morphological MRI features. METHODS: Men with maximum Likert-score 3/5 within their PZ were retrospectively selected from 330 patients who prospectively underwent prostate mpMRI (3 T) without an endorectal coil, followed by 20-zone transperineal template prostate mapping biopsies ＋/- focal lesion-targeted biopsy. PSAD was calculated using pre-biopsy PSA and MRI-derived volume. Two readers A and B independently assessed included men with both Likert-assessment and PI-RADS_v2. Both readers then classified mpMRI morphological features in consensus. Men were divided into two groups: significant cancer (≥ Gleason 3 ＋ 4) or insignificant cancer (≤ Gleason 3 ＋ 3)/no cancer. Comparisons between groups were made separately for PSA & PSAD using Mann-Whitney test and morphological descriptors with Fisher's exact test. PI-RADS_v2 and Likert-assessment were descriptively compared and percentage inter-reader agreement calculated. RESULTS: 76 males were eligible for PSA & PSAD analyses, 71 for PI-RADS scoring, and 67 for morphological assessment (excluding significant image artefacts). Unlike PSA (p = 0.915), PSAD was statistically different (p = 0.004) between the significant [median: 0.19 ng ml-2 (interquartile range: 0.13-0.29)] and non-significant/no cancer [median: 0.13 ng ml-2 (interquartile range: 0.10-0.17)] groups. Presence of mpMRI morphological features was not significantly different between groups. Subjective Likert-assessment discriminated patients with significant cancer better than PI-RADS_v2. Inter-reader percentage agreement was 83% for subjective Likert-assessment and 56% for PI-RADS_v2. CONCLUSION: PSAD may categorize presence of significant cancer in patients with Likert-scored 3/5 PZ mpMRI findings. Advances in knowledge: PSAD may be used in indeterminate PZ mpMRI to guide decisions between biopsy vs monitoring.

"Textural analysis of multiparametric MRI detects transition zone prostate cancer".

OBJECTIVES: To evaluate multiparametric-MRI (mpMRI) derived histogram textural-analysis parameters for detection of transition zone (TZ) prostatic tumour. METHODS: Sixty-seven consecutive men with suspected prostate cancer underwent 1.5T mpMRI prior to template-mapping-biopsy (TPM). Twenty-six men had 'significant' TZ tumour. Two radiologists in consensus matched TPM to the single axial slice best depicting tumour, or largest TZ diameter for those with benign histology, to define single-slice whole TZ-regions-of-interest (ROIs). Textural-parameter differences between single-slice whole TZ-ROI containing significant tumour versus benign/insignificant tumour were analysed using Mann Whitney U test. Diagnostic accuracy was assessed by receiver operating characteristic area under curve (ROC-AUC) analysis cross-validated with leave-one-out (LOO) analysis. RESULTS: ADC kurtosis was significantly lower (p < 0.001) in TZ containing significant tumour with ROC-AUC 0.80 (LOO-AUC 0.78); the difference became non-significant following exclusion of significant tumour from single-slice whole TZ-ROI (p = 0.23). T1-entropy was significantly lower (p = 0.004) in TZ containing significant tumour with ROC-AUC 0.70 (LOO-AUC 0.66) and was unaffected by excluding significant tumour from TZ-ROI (p = 0.004). Combining these parameters yielded ROC-AUC 0.86 (LOO-AUC 0.83). CONCLUSION: Textural features of the whole prostate TZ can discriminate significant prostatic cancer through reduced kurtosis of the ADC-histogram where significant tumour is included in TZ-ROI and reduced T1 entropy independent of tumour inclusion. KEY POINTS: • MR textural features of prostate transition zone may discriminate significant prostatic cancer. • Transition zone (TZ) containing significant tumour demonstrates a less peaked ADC histogram. • TZ containing significant tumour reveals higher post-contrast T1-weighted homogeneity. • The utility of MR texture analysis in prostate cancer merits further investigation.

Imaging features of therapeutic drug-induced musculoskeletal abnormalities.

Increasing use of a wide variety of therapeutic drugs with known musculoskeletal side-effect profiles necessitates a rigorous understanding and approach when evaluating imaging features suggestive of drug-induced musculoskeletal abnormalities. The etiology of such abnormalities is diverse, and the clinical and imaging manifestations may be nonspecific. The recognition of adverse effects depends, first, on the physician's vigilant review of clinical information for relevant drug history and indicative signs, and second, on the radiologist's ability to detect musculoskeletal changes consistent with known potential effects of specific drugs. Musculoskeletal abnormalities induced by therapeutic drugs may be broadly categorized as embryopathic, juvenile, or postmaturation. Embryopathic skeletal abnormalities result from the teratogenic effects of drugs administered to pregnant women (eg, thalidomide, anticonvulsants). Other therapeutic agents characteristically lead to abnormalities during postnatal skeletal maturation (eg, high-dose vitamins or prostaglandin) either because they are used exclusively in children or because they have idiosyncratic effects on immature musculoskeletal structures. Many drugs (eg, statins) may have musculoskeletal side effects that, although independent of the stage of skeletal maturation, are most often seen in adults or elderly people because they are commonly prescribed for people in these age groups. Drug-induced musculoskeletal abnormalities may be further characterized according to the predominant skeletal manifestations as osteomalacic, proliferative, or osteoporotic and according to the involvement of soft tissues as musculotendinous or chondral.