1
|
Eklund M. Artificial intelligence for scoring prostate MRI: ready for prospective evaluation. Lancet Oncol 2024:S1470-2045(24)00284-5. [PMID: 38876122 DOI: 10.1016/s1470-2045(24)00284-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Revised: 05/10/2024] [Accepted: 05/15/2024] [Indexed: 06/16/2024]
Affiliation(s)
- Martin Eklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 171 77, Sweden.
| |
Collapse
|
2
|
Buteau JP, Moon D, Fahey MT, Roberts MJ, Thompson J, Murphy DG, Papa N, Mitchell C, De Abreu Lourenco R, Dhillon HM, Kasivisvanathan V, Francis RJ, Stricker P, Agrawal S, O'Brien J, McVey A, Sharma G, Levy S, Ayati N, Nguyen A, Lee SF, Pattison DA, Sivaratnam D, Frydenberg M, Du Y, Titus J, Lee ST, Ischia J, Jack G, Hofman MS, Emmett L. Clinical Trial Protocol for PRIMARY2: A Multicentre, Phase 3, Randomised Controlled Trial Investigating the Additive Diagnostic Value of [ 68Ga]Ga-PSMA-11 Positron Emission Tomography/Computed Tomography in Men with Negative or Equivocal Multiparametric Magnetic Resonance Imaging for the Diagnosis of Clinically Significant Prostate Cancer. Eur Urol Oncol 2024; 7:544-552. [PMID: 38061976 DOI: 10.1016/j.euo.2023.11.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 10/06/2023] [Accepted: 11/02/2023] [Indexed: 05/19/2024]
Abstract
BACKGROUND Multiparametric magnetic resonance imaging (mpMRI) has an established role for the diagnosis of clinically significant prostate cancer (sPCa). The PRIMARY trial demonstrated that [68Ga]Ga-PSMA-11 positron emission tomography/computed tomography (PET/CT) was associated with a significant improvement in sensitivity and negative predictive value for sPCa detection. OBJECTIVE To demonstrate that addition of prostate-specific membrane antigen (PSMA) radioligand PET/CT will enable some men to avoid transperineal prostate biopsy without missing sPCa, and will facilitate biopsy targeting of PSMA-avid sites. DESIGN, SETTING, AND PARTICIPANTS This multicentre, two-arm, phase 3, randomised controlled trial will recruit 660 participants scheduled to undergo biopsy. Eligible participants will have clinical suspicion of sPCa with a Prostate Imaging-Reporting and Data System (PI-RADS) score of 2 and red flags, or a PI-RADS score of 3 on mpMRI (PI-RADS v2). Participants will be randomised at a 1:1 ratio in permuted blocks stratified by centre. The trial is registered on ClinicalTrials.gov as NCT05154162. INTERVENTION In the experimental arm, participants will undergo pelvic PSMA PET/CT. Local and central reviewers will interpret scans independently using the PRIMARY score. Participants with a positive result will undergo targeted transperineal prostate biopsies, whereas those with a negative result will undergo prostate-specific antigen monitoring alone. In the control arm, all participants undergo template transperineal prostate biopsies. Participants will be followed for subsequent clinical care for up to 2 yr after randomisation. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS sPCa is defined as Gleason score 3 + 4 (≥10%) = 7 disease (grade group 2) or higher on transperineal prostate biopsy. Avoidance of transperineal prostate biopsy will be measured at 6 mo from randomisation. The primary endpoints will be analysed on an intention-to-treat basis. CONCLUSIONS Patient enrolment began in March 2022, with recruitment expected to take 36 mo. PATIENT SUMMARY For patients with suspected prostate cancer who have nonsuspicious or unclear MRI (magnetic resonance imaging) scan findings, a different type of scan (called PSMA PET/CT; prostate-specific membrane antigen positron emission tomography/computed tomography) may identify men who could avoid an invasive prostate biopsy. This type of scan could also help urologists in better targeting of samples from suspicious lesions during prostate biopsies.
Collapse
Affiliation(s)
- James P Buteau
- Prostate Cancer Theranostics and Imaging Centre of Excellence, Peter MacCallum Cancer Centre, Melbourne, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia.
| | - Daniel Moon
- Division of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, Australia; Royal Melbourne Clinical School, University of Melbourne, Melbourne, Australia
| | - Michael T Fahey
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia; Centre for Biostatistics and Clinical Trials, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Matthew J Roberts
- Department of Urology, Royal Brisbane and Women's Hospital, Brisbane, Australia; UQ Centre for Clinical Research, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - James Thompson
- Department of Urology, St. George Hospital, Sydney, Australia
| | - Declan G Murphy
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia; Division of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Nathan Papa
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Catherine Mitchell
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia; Department of Pathology, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Richard De Abreu Lourenco
- Centre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney, Australia
| | - Haryana M Dhillon
- Psycho-Oncology Cooperative Research Group, Centre for Medical Psychology & Evidence-based Decision-making, University of Sydney, Camperdown, Australia
| | - Veeru Kasivisvanathan
- Division of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, Australia; Division of Surgery and Interventional Science, University College London, London, UK
| | - Roslyn J Francis
- Department of Nuclear Medicine, Sir Charles Gairdner Hospital, Perth, WA, Australia; Medical School, University of Western Australia, Perth, Australia
| | - Phillip Stricker
- St. Vincent's Prostate Cancer Research Centre, Garvan Institute, UNSW Sydney, Sydney, Australia; Department of Urology, St. Vincent's Hospital, Sydney, Australia
| | - Shihka Agrawal
- Department of Theranostics and Nuclear Medicine, St. Vincent's Hospital, Sydney, Australia; Faculty of Medicine, UNSW Sydney, Sydney, Australia
| | - Jonathan O'Brien
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia; Division of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Aoife McVey
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia; Division of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Gaurav Sharma
- Prostate Cancer Theranostics and Imaging Centre of Excellence, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Sidney Levy
- Prostate Cancer Theranostics and Imaging Centre of Excellence, Peter MacCallum Cancer Centre, Melbourne, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia; Department of Nuclear Medicine, Royal Melbourne Hospital, Melbourne, Australia; Department of Nuclear Medicine, Cabrini Health, Melbourne, Australia
| | - Narjess Ayati
- Department of Theranostics and Nuclear Medicine, St. Vincent's Hospital, Sydney, Australia; Faculty of Medicine, UNSW Sydney, Sydney, Australia
| | - Andrew Nguyen
- Department of Theranostics and Nuclear Medicine, St. Vincent's Hospital, Sydney, Australia; Faculty of Medicine, UNSW Sydney, Sydney, Australia
| | - Su-Faye Lee
- Prostate Cancer Theranostics and Imaging Centre of Excellence, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - David A Pattison
- Department of Nuclear Medicine and Specialised PET Services, Royal Brisbane and Women's Hospital, Brisbane, Australia; School of Medicine, University of Queensland, Brisbane, Australia
| | - Dinesh Sivaratnam
- Department of Nuclear Medicine, Royal Melbourne Hospital, Melbourne, Australia; Department of Nuclear Medicine, Cabrini Health, Melbourne, Australia
| | - Mark Frydenberg
- Department of Surgery, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia; Cabrini Research, Cabrini Health, Melbourne, Australia
| | - Yang Du
- Department of Nuclear Medicine, PET and Bone Densitometry, South Australia Medical Imaging, Royal Adelaide Hospital, Adelaide, Australia
| | - Jehan Titus
- Department of Urology, Royal Adelaide Hospital, Adelaide, Australia
| | - Sze-Ting Lee
- Department of Medicine, University of Melbourne, Melbourne, Australia; Department of Molecular Imaging and Therapy, Austin Health, Melbourne, Australia
| | - Joseph Ischia
- University of Melbourne Department of Surgery, Austin Health, Melbourne, Australia
| | - Greg Jack
- University of Melbourne Department of Surgery, Austin Health, Melbourne, Australia
| | - Michael S Hofman
- Prostate Cancer Theranostics and Imaging Centre of Excellence, Peter MacCallum Cancer Centre, Melbourne, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia
| | - Louise Emmett
- Department of Theranostics and Nuclear Medicine, St. Vincent's Hospital, Sydney, Australia; Faculty of Medicine, UNSW Sydney, Sydney, Australia
| |
Collapse
|
3
|
van den Kroonenberg DL, Stoter JD, Jager A, Veerman H, Hagens MJ, Schoots IG, Postema AW, Hoekstra RJ, Oprea-Lager DE, Nieuwenhuijzen JA, van Leeuwen PJ, Vis AN. The Impact of Omitting Contralateral Systematic Biopsy on the Surgical Planning of Patients with a Unilateral Suspicious Lesion on Magnetic Resonance Imaging Undergoing Robot-assisted Radical Prostatectomy for Prostate Cancer. EUR UROL SUPPL 2024; 63:13-18. [PMID: 38558763 PMCID: PMC10981034 DOI: 10.1016/j.euros.2024.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/10/2024] [Indexed: 04/04/2024] Open
Abstract
Background and objective A combined approach of magnetic resonance imaging (MRI)-targeted biopsy (TBx) and bilateral systematic biopsy (SBx) is advised in patients who have an increased risk of prostate cancer (PCa). The diagnostic gain of SBx in detecting PCa for treatment planning of patients undergoing robot-assisted radical prostatectomy (RARP) is unknown. This study aims to determine the impact of omitting contralateral SBx on the surgical planning of patients undergoing RARP in terms of nerve-sparing surgery (NSS) and extended pelvic lymph node dissection (ePLND). Methods Case files from 80 men with biopsy-proven PCa were studied. All men had a unilateral suspicious lesion on MRI, and underwent TBx and bilateral SBx. Case files were presented to five urologists for the surgical planning of RARP. Each case file was presented randomly using two different sets of information: (1) results of TBx + bilateral SBx, and (2) results of TBx + ipsilateral SBx. The urologists assessed whether they would perform NSS and/or ePLND. Key findings and limitations A change in the surgical plan concerning NSS on the contralateral side was observed in 9.0% (95% confidence interval [CI] 6.4-12.2) of cases. Additionally, the indication for ePLND changed in 5.3% (95% CI 3.3-7.9) of cases. Interobserver agreement based on Fleiss' kappa changed from 0.44 to 0.15 for the indication of NSS and from 0.84 to 0.83 for the indication of ePLND. Conclusions and clinical implications In our series, the diagnostic information obtained from contralateral SBx has limited impact on the surgical planning of patients with a unilateral suspicious lesion on MRI scheduled to undergo RARP. Patient summary In patients with one-sided prostate cancer on magnetic resonance imaging, omitting biopsies on the other side rarely changed the surgical plan with respect to nerve-sparing surgery and the indication to perform extended lymph node dissection.
Collapse
Affiliation(s)
| | | | - Auke Jager
- Amsterdam UMC, location VUmc, Amsterdam, The Netherlands
- Prostate Cancer Network Netherlands, Amsterdam, The Netherlands
| | - Hans Veerman
- Amsterdam UMC, location VUmc, Amsterdam, The Netherlands
- Prostate Cancer Network Netherlands, Amsterdam, The Netherlands
| | - Marinus J. Hagens
- Amsterdam UMC, location VUmc, Amsterdam, The Netherlands
- Prostate Cancer Network Netherlands, Amsterdam, The Netherlands
- Department of Urology, Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Ivo G. Schoots
- Department of Radiology and Nuclear medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Radiology, Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Arnoud W. Postema
- Amsterdam UMC, location VUmc, Amsterdam, The Netherlands
- Prostate Cancer Network Netherlands, Amsterdam, The Netherlands
- Department of Urology, Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Robert J. Hoekstra
- Department of Urology, Catharina Hospital, Eindhoven, The Netherlands
- Prosper Prostate Clinic, Nijmegen, The Netherlands
| | | | - Jakko A. Nieuwenhuijzen
- Amsterdam UMC, location VUmc, Amsterdam, The Netherlands
- Prostate Cancer Network Netherlands, Amsterdam, The Netherlands
| | - Pim J. van Leeuwen
- Prostate Cancer Network Netherlands, Amsterdam, The Netherlands
- Department of Urology, Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - André N. Vis
- Amsterdam UMC, location VUmc, Amsterdam, The Netherlands
- Prostate Cancer Network Netherlands, Amsterdam, The Netherlands
| |
Collapse
|
4
|
Mac Curtain BM, Temperley HC, Kelly JAO, Ryan J, Qian W, O'Sullivan N, Breen KJ, Mc Carthy CJ, Brennan I, Davis NF. The role of urology and radiology in prostate biopsy: current trends and future perspectives. World J Urol 2024; 42:249. [PMID: 38649544 DOI: 10.1007/s00345-024-04967-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 03/25/2024] [Indexed: 04/25/2024] Open
Abstract
PURPOSE Prostate biopsy is central to the accurate histological diagnosis of prostate cancer. In current practice, the biopsy procedure can be performed using a transrectal or transperineal route with different technologies available for targeting of lesions within the prostate. Historically, the biopsy procedure was performed solely by urologists, but with the advent of image-guided techniques, the involvement of radiologists in prostate biopsy has become more common. Herein, we discuss the pros, cons and future considerations regarding their ongoing role. METHODS A narrative review regarding the current evidence was completed. PubMed and Cochrane central register of controlled trials were search until January 2024. All study types were of consideration if published after 2000 and an English language translation was available. RESULTS There are no published studies that directly compare outcomes of prostate biopsy when performed by a urologist or radiologist. In all published studies regarding the learning curve for prostate biopsy, the procedure was performed by urologists. These studies suggest that the learning curve for prostate biopsy is between 10 and 50 cases to reach proficiency in terms of prostate cancer detection and complications. It is recognised that many urologists are poorly able to accurately interpret multi parametric (mp)-MRI of the prostate. Collaboration between the specialities is of importance with urology offering the advantage of being involved in prior and future care of the patient while radiology has the advantage of being able to expertly interpret preprocedure MRI. CONCLUSION There is no evidence to suggest that prostate biopsy should be solely performed by a specific specialty. The most important factor remains knowledge of the relevant anatomy and sufficient volume of cases to develop and maintain skills.
Collapse
Affiliation(s)
| | | | - John A O Kelly
- Department of Urology, St Vincent's University Hospital, Dublin, Ireland
| | - James Ryan
- Department of Radiology, St Vincent's University Hospital, Dublin, Ireland
| | - Wanyang Qian
- Dept of Surgery, St John of God Midland Hospital, Midland, WA, USA
| | | | - Kieran J Breen
- Department of Urology, St Vincent's University Hospital, Dublin, Ireland
| | - Colin J Mc Carthy
- Department of Radiology, Beth Israel Deaconess Medical Centre, Boston, MA, USA
| | - Ian Brennan
- Department of Radiology, St James Hospital, Dublin, Ireland
| | - Niall F Davis
- Department of Urology, Beaumont Hospital, Dublin, Ireland
| |
Collapse
|
5
|
Mayer R, Turkbey B, Choyke PL, Simone CB. Relationship between Eccentricity and Volume Determined by Spectral Algorithms Applied to Spatially Registered Bi-Parametric MRI and Prostate Tumor Aggressiveness: A Pilot Study. Diagnostics (Basel) 2023; 13:3238. [PMID: 37892059 PMCID: PMC10605733 DOI: 10.3390/diagnostics13203238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 10/09/2023] [Accepted: 10/10/2023] [Indexed: 10/29/2023] Open
Abstract
(1) Background: Non-invasive prostate cancer assessments using multi-parametric MRI are essential to the reliable detection of lesions and proper management of patients. While current guidelines call for the administration of Gadolinium-containing intravenous contrast injections, eliminating such injections would simplify scanning and reduce patient risk and costs. However, augmented image analysis is necessary to extract important diagnostic information from MRIs. Purpose: This study aims to extend previous work on the signal to clutter ratio and test whether prostate tumor eccentricity and volume are indicators of tumor aggressiveness using bi-parametric (BP)-MRI. (2) Methods: This study retrospectively processed 42 consecutive prostate cancer patients from the PI-CAI data collection. BP-MRIs (apparent diffusion coefficient, high b-value, and T2 images) were resized, translated, cropped, and stitched to form spatially registered BP-MRIs. The International Society of Urological Pathology (ISUP) grade was used to judge cases of prostate cancer as either clinically significant prostate cancer (CsPCa) (ISUP ≥ 2) or clinically insignificant prostate cancer (CiPCa) (ISUP < 2). The Adaptive Cosine Estimator (ACE) algorithm was applied to the BP-MRIs, followed by thresholding, and then eccentricity and volume computations, from the labeled and blobbed detection maps. Then, univariate and multivariate linear regression fittings of eccentricity and volume were applied to the ISUP grade. The fits were quantitatively evaluated by computing correlation coefficients (R) and p-values. Area under the curve (AUC) and receiver operator characteristic (ROC) curve scores were used to assess the logistic fitting to CsPCa/CiPCa. (3) Results: Modest correlation coefficients (R) (>0.35) and AUC scores (0.70) for the linear and/or logistic fits from the processed prostate tumor eccentricity and volume computations for the spatially registered BP-MRIs exceeded fits using the parameters of prostate serum antigen, prostate volume, and patient age (R~0.17). (4) Conclusions: This is the first study that applied spectral approaches to BP-MRIs to generate tumor eccentricity and volume metrics to assess tumor aggressiveness. This study found significant values of R and AUC (albeit below those from multi-parametric MRI) to fit and relate the metrics to the ISUP grade and CsPCA/CiPCA, respectively.
Collapse
Affiliation(s)
- Rulon Mayer
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Oncoscore, Garrett Park, MD 20896, USA
| | - Baris Turkbey
- National Institutes of Health, Bethesda, MD 20892, USA; (B.T.); (P.L.C.)
| | - Peter L. Choyke
- National Institutes of Health, Bethesda, MD 20892, USA; (B.T.); (P.L.C.)
| | | |
Collapse
|
6
|
Duenweg SR, Bobholz SA, Barrett MJ, Lowman AK, Winiarz A, Nath B, Stebbins M, Bukowy J, Iczkowski KA, Jacobsohn KM, Vincent-Sheldon S, LaViolette PS. T2-Weighted MRI Radiomic Features Predict Prostate Cancer Presence and Eventual Biochemical Recurrence. Cancers (Basel) 2023; 15:4437. [PMID: 37760407 PMCID: PMC10526331 DOI: 10.3390/cancers15184437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 08/23/2023] [Accepted: 08/31/2023] [Indexed: 09/29/2023] Open
Abstract
Prostate cancer (PCa) is the most diagnosed non-cutaneous cancer in men. Despite therapies such as radical prostatectomy, which is considered curative, distant metastases may form, resulting in biochemical recurrence (BCR). This study used radiomic features calculated from multi-parametric magnetic resonance imaging (MP-MRI) to evaluate their ability to predict BCR and PCa presence. Data from a total of 279 patients, of which 46 experienced BCR, undergoing MP-MRI prior to surgery were assessed for this study. After surgery, the prostate was sectioned using patient-specific 3D-printed slicing jigs modeled using the T2-weighted imaging (T2WI). Sectioned tissue was stained, digitized, and annotated by a GU-fellowship trained pathologist for cancer presence. Digitized slides and annotations were co-registered to the T2WI and radiomic features were calculated across the whole prostate and cancerous lesions. A tree regression model was fitted to assess the ability of radiomic features to predict BCR, and a tree classification model was fitted with the same radiomic features to classify regions of cancer. We found that 10 radiomic features predicted eventual BCR with an AUC of 0.97 and classified cancer at an accuracy of 89.9%. This study showcases the application of a radiomic feature-based tool to screen for the presence of prostate cancer and assess patient prognosis, as determined by biochemical recurrence.
Collapse
Affiliation(s)
- Savannah R. Duenweg
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA; (S.R.D.); (M.S.)
| | - Samuel A. Bobholz
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
| | - Michael J. Barrett
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
| | - Allison K. Lowman
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
| | - Aleksandra Winiarz
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA; (S.R.D.); (M.S.)
| | - Biprojit Nath
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA; (S.R.D.); (M.S.)
| | - Margaret Stebbins
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA; (S.R.D.); (M.S.)
| | - John Bukowy
- Department of Electrical Engineering and Computer Science, Milwaukee School of Engineering, 1025 N Broadway, Milwaukee, WI 53202, USA
| | - Kenneth A. Iczkowski
- Department of Pathology, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA;
| | - Kenneth M. Jacobsohn
- Department of Urology, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
| | - Stephanie Vincent-Sheldon
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
| | - Peter S. LaViolette
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA; (S.R.D.); (M.S.)
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
- Department of Biomedical Engineering, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
| |
Collapse
|
7
|
Kalchev E. Evaluating the Utility of Prostate-Specific Antigen Density in Risk Stratification of PI-RADS 3 Peripheral Zone Lesions on Non-Contrast-Enhanced Prostate MRI: An Exploratory Single-Institution Study. Cureus 2023; 15:e41369. [PMID: 37546087 PMCID: PMC10399968 DOI: 10.7759/cureus.41369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/04/2023] [Indexed: 08/08/2023] Open
Abstract
Objective This study aimed to explore the potential of prostate-specific antigen density (PSAD) as a supplementary tool for defining high-risk Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions in the peripheral zone on non-contrast-enhanced MRI. This additional stratification tool could supplement the decision-making process for biopsy, potentially helping in identifying higher-risk patients more accurately, minimizing unnecessary procedures in lower-risk patients, and limiting the need for dynamic contrast-enhanced (DCE) scans. Materials and methods Between January 2019 and April 2023, 30 patients with PI-RADS 3 lesions underwent MRI-ultrasound fusion biopsies at our institution. Age and PSAD values were investigated using logistic regression and chi-square automatic interaction detection (CHAID) analysis to discern their predictive value for malignancy. Results The mean patient age was 64.7 years, and the mean PSAD was 0.13 ng/mL2. Logistic regression demonstrated PSAD to be a significant predictor of cancer (p=0.012), but not age (p=0.855). CHAID analysis further identified a PSAD cut-off value of 0.12, below which the cancer detection rate was 23.1% and above which the rate increased to 76.5%. Conclusions This exploratory study suggests that PSAD might be utilized to enhance the stratification of high-risk PI-RADS 3 lesions in the peripheral zone on non-contrast-enhanced MRI, aiding in decision-making for biopsy. While biopsy remains the gold standard for definitive diagnosis, a high PSAD value may suggest a greater need for biopsy in this specific group. Although further validation in larger cohorts is required, our findings contribute to the ongoing discourse on optimizing PI-RADS 3 lesion management. Limitations include a small sample size, the retrospective nature of the study, and the single-center setting, which may impact the generalizability of our results.
Collapse
Affiliation(s)
- Emilian Kalchev
- Diagnostic Imaging, St Marina University Hospital, Varna, BGR
| |
Collapse
|
8
|
Lophatananon A, Light A, Burns-Cox N, Maccormick A, John J, Otti V, McGrath J, Archer P, Anning J, McCracken S, Page T, Muir K, Gnanapragasam VJ. Re-evaluating the diagnostic efficacy of PSA as a referral test to detect clinically significant prostate cancer in contemporary MRI-based image-guided biopsy pathways. JOURNAL OF CLINICAL UROLOGY 2023; 16:264-273. [PMID: 37614642 PMCID: PMC7614972 DOI: 10.1177/20514158211059057] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Abstract
Introduction Modern image-guided biopsy pathways at diagnostic centres have greatly refined the investigations of men referred with suspected prostate cancer. However, the referral criteria from primary care are still based on historical prostate-specific antigen (PSA) cut-offs and age-referenced thresholds. Here, we tested whether better contemporary pathways and biopsy methods had improved the predictive utility value of PSA referral thresholds. Methods PSA referral thresholds, age-referenced ranges and PSA density (PSAd) were assessed for positive predictive value (PPV) in detection of clinically significant prostate cancer (csPCa - histological ⩾ Grade Group 2). Data were analysed from men referred to three diagnostics centres who used multi-parametric magnetic resonance imaging (mpMRI)-guided prostate biopsies for disease characterisation. Findings were validated in a separate multicentre cohort. Results: Data from 2767 men were included in this study. The median age, PSA and PSAd were 66.4 years, 7.3 ng/mL and 0.1 ng/mL2, respectively. Biopsy detected csPCa was found in 38.7%. The overall area under the curve (AUC) for PSA was 0.68 which is similar to historical performance. A PSA threshold of ⩾ 3 ng/mL had a PPV of 40.3%, but this was age dependent (PPV: 24.8%, 32.7% and 56.8% in men 50-59 years, 60-69 years and ⩾ 70 years, respectively). Different PSA cut-offs and age-reference ranges failed to demonstrate better performance. PSAd demonstrated improved AUC (0.78 vs 0.68, p < 0.0001) and improved PPV compared to PSA. A PSAd of ⩾ 0.10 had a PPV of 48.2% and similar negative predictive value (NPV) to PSA ⩾ 3 ng/mL and out-performed PSA age-reference ranges. This improved performance was recapitulated in a separate multi-centre cohort (n = 541). Conclusion The introduction of MRI-based image-guided biopsy pathways does not appear to have altered PSA diagnostic test characteristics to positively detect csPCa. We find no added value to PSA age-referenced ranges, while PSAd offers better PPV and the potential for a single clinically useful threshold (⩾0.10) for all age groups. Level of evidence IV.
Collapse
Affiliation(s)
- Artitaya Lophatananon
- Division of Population Health, Health Services Research & Primary Care Centre, University of Manchester, UK
| | - Alexander Light
- Division of Urology, Department of Surgery, University of Cambridge, UK
- Department of Urology, Cambridge University Hospitals NHS Foundation Trust, UK
| | | | | | - Joseph John
- Department of Urology, Royal Devon and Exeter NHS Foundation Trust and University of Exeter, UK
| | - Vanessa Otti
- Department of Urology, Royal Devon and Exeter NHS Foundation Trust and University of Exeter, UK
| | - John McGrath
- Department of Urology, Royal Devon and Exeter NHS Foundation Trust and University of Exeter, UK
| | - Pete Archer
- Department of Urology, Southend Hospital, UK
| | | | - Stuart McCracken
- Department of Urology, South Tyneside and Sunderland NHS Trust, UK
| | - Toby Page
- Department of Urology, Newcastle Hospitals NHS Trust, UK
| | - Ken Muir
- Division of Population Health, Health Services Research & Primary Care Centre, University of Manchester, UK
| | - Vincent J Gnanapragasam
- Division of Urology, Department of Surgery, University of Cambridge, UK
- Department of Urology, Cambridge University Hospitals NHS Foundation Trust, UK
- Cambridge Urology Translational Research and Clinical Trials Office, Addenbrooke’s Hospital, UK
| |
Collapse
|
9
|
Eldred-Evans D, Connor MJ, Bertoncelli Tanaka M, Bass E, Reddy D, Walters U, Stroman L, Espinosa E, Das R, Khosla N, Tam H, Pegers E, Qazi H, Gordon S, Winkler M, Ahmed HU. The rapid assessment for prostate imaging and diagnosis (RAPID) prostate cancer diagnostic pathway. BJU Int 2023; 131:461-470. [PMID: 36134435 DOI: 10.1111/bju.15899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To report outcomes within the Rapid Assessment for Prostate Imaging and Diagnosis (RAPID) diagnostic pathway, introduced to reduce patient and healthcare burdens and standardize delivery of pre-biopsy multiparametric magnetic resonance imaging (MRI) and transperineal biopsy. PATIENTS AND METHODS A total of 2130 patients from three centres who completed the RAPID pathway (3 April 2017 to 31 March 2020) were consecutively entered as a prospective registry. These patients were also compared to a pre-RAPID cohort of 2435 patients. Patients on the RAPID pathway with an MRI score 4 or 5 and those with PSA density ≥0.12 and an MRI score 3 were advised to undergo a biopsy. Primary outcomes were rates of biopsy and cancer detection. Secondary outcomes included comparison of transperineal biopsy techniques, patient acceptability and changes in time to diagnosis before and after the introduction of RAPID. RESULTS The median patient age and PSA level were 66 years and 6.6 ng/mL, respectively. Biopsy could be omitted in 43% of patients (920/2130). A further 7.9% of patients (168/2130) declined a recommendation for biopsy. The percentage of biopsies avoided among sites varied (45% vs 36% vs 51%; P < 0.001). In all, 30% (221/742) had a local anaesthetic (grid and stepper) transperineal biopsy. Clinically significant cancer detection (any Gleason score ≥3 + 4) was 26% (560/2130) and detection of Gleason score 3 + 3 alone constituted 5.8% (124/2130); detection of Gleason score 3 + 3 did not significantly vary among sites (P = 0.7). Among participants who received a transperineal targeted biopsy, there was no difference in cancer detection rates among local anaesthetic, sedation and general anaesthetic groups. In the 2435 patients from the pre-RAPID cohor, time to diagnosis was 32.1 days (95% confidence interval [CI] 29.3-34.9) compared to 15.9 days (95% CI 12.9-34.9) in the RAPID group. A total of 141 consecutive patient satisfaction surveys indicated a high satisfaction rate with the pathway; 50% indicated a preference for having all tests on a single day. CONCLUSIONS The RAPID prostate cancer diagnostic pathway allows 43% of men to avoid a biopsy while preserving good detection of clinically significant cancers and low detection of insignificant cancers, although there were some centre-level variations.
Collapse
Affiliation(s)
- David Eldred-Evans
- Imperial Prostate, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK
- Imperial Urology, Imperial College Healthcare NHS Trust, London, UK
| | - Martin J Connor
- Imperial Prostate, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK
- Imperial Urology, Imperial College Healthcare NHS Trust, London, UK
| | - Mariana Bertoncelli Tanaka
- Imperial Prostate, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK
- Imperial Urology, Imperial College Healthcare NHS Trust, London, UK
| | - Edward Bass
- Imperial Prostate, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK
- Imperial Urology, Imperial College Healthcare NHS Trust, London, UK
| | - Deepika Reddy
- Imperial Prostate, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK
- Imperial Urology, Imperial College Healthcare NHS Trust, London, UK
| | - Uma Walters
- Imperial Prostate, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK
- Imperial Urology, Imperial College Healthcare NHS Trust, London, UK
| | - Luke Stroman
- St George's University Hospitals NHS Foundation Trust, London, UK
| | | | - Raj Das
- St George's University Hospitals NHS Foundation Trust, London, UK
| | - Nalin Khosla
- Epsom and St Helier University Hospitals, London, UK
| | - Henry Tam
- Imperial Urology, Imperial College Healthcare NHS Trust, London, UK
| | | | - Hasan Qazi
- St George's University Hospitals NHS Foundation Trust, London, UK
| | | | - Mathias Winkler
- Imperial Prostate, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK
- Imperial Urology, Imperial College Healthcare NHS Trust, London, UK
| | - Hashim U Ahmed
- Imperial Prostate, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK
- Imperial Urology, Imperial College Healthcare NHS Trust, London, UK
| |
Collapse
|
10
|
Fiard G, Seigneurin A, Roumiguié M, Albisinni S, Anract J, Assenmacher G, Barry Delongchamps N, Dariane C, Feyaerts A, Fourcade A, Fournier G, Gontero P, Mastroianni R, Oderda M, Peltier A, Roumeguère T, Saussez T, Simone G, Van Damme J, Descotes JL, Ploussard G, Diamand R. Prognostic significance of PI-RADS 5 lesions in patients treated by radical prostatectomy. World J Urol 2023; 41:1285-1291. [PMID: 36971827 DOI: 10.1007/s00345-023-04371-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 03/04/2023] [Indexed: 03/29/2023] Open
Abstract
PURPOSE To analyse the pathological features and survival of patients with a PI-RADS 5 lesion on pre-biopsy MRI. METHODS We extracted from a European multicentre prospectively gathered database the data of patients with a PI-RADS 5 lesion on pre-biopsy MRI, diagnosed using both systematic and targeted biopsies and subsequently treated by radical prostatectomy. The Kaplan-Meier model was used to assess the biochemical-free survival of the whole cohort and univariable and multivariable Cox models were set up to study factors associated with survival. RESULTS Between 2013 and 2019, 539 consecutive patients with a PI-RADS 5 lesion on pre-biopsy MRI were treated by radical prostatectomy and included in the analysis. Follow-up data were available for 448 patients. Radical prostatectomy and lymph node dissection specimens showed non-organ confined disease in 297/539 (55%), (including 2 patients with a locally staged pT2 lesion and lymph node involvement (LNI)). With a median follow-up of 25 months (12-39), the median biochemical recurrence-free survival was 54% at 2 years (95% CI 45-61) and 28% at 5 years (95% CI 18-39). Among the factors studied, MRI T stage [T3a vs T2 HR 3.57 (95%CI 1.78-7.16); T3b vs T2 HR 6.17 (95% CI 2.99-12.72)] and PSA density (HR 4.47 95% CI 1.55-12.89) were significantly associated with a higher risk of biochemical recurrence in multivariable analysis. CONCLUSION Patients with a PI-RADS 5 lesion on pre-biopsy MRI have a high risk of early biochemical recurrence after radical prostatectomy. MRI T stage and PSA density can be used to improve patient selection and counselling.
Collapse
|
11
|
Clinical Trial Protocol: Developing an Image Classification Algorithm for Prostate Cancer Diagnosis on Three-dimensional Multiparametric Transrectal Ultrasound. EUR UROL SUPPL 2023; 49:32-43. [PMID: 36874606 PMCID: PMC9975006 DOI: 10.1016/j.euros.2022.12.018] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/22/2022] [Indexed: 01/27/2023] Open
Abstract
Introduction and hypothesis The tendency toward population-based screening programs for prostate cancer (PCa) is expected to increase demand for prebiopsy imaging. This study hypothesizes that a machine learning image classification algorithm for three-dimensional multiparametric transrectal prostate ultrasound (3D mpUS) can detect PCa accurately. Design This is a phase 2 prospective multicenter diagnostic accuracy study. A total of 715 patients will be included in a period of approximately 2 yr. Patients are eligible in case of suspected PCa for which prostate biopsy is indicated or in case of biopsy-proven PCa for which radical prostatectomy (RP) will be performed. Exclusion criteria are prior treatment for PCa or contraindications for ultrasound contrast agents (UCAs). Protocol overview Study participants will undergo 3D mpUS, consisting of 3D grayscale, 4D contrast-enhanced ultrasound, and 3D shear wave elastography (SWE). Whole-mount RP histopathology will provide the ground truth to train the image classification algorithm. Patients included prior to prostate biopsy will be used for subsequent preliminary validation. There is a small, anticipated risk for participants associated with the administration of a UCA. Informed consent has to be given prior to study participation, and (serious) adverse events will be reported. Statistical analysis The primary outcome will be the diagnostic performance of the algorithm for detecting clinically significant PCa (csPCa) on a per-voxel and a per-microregion level. Diagnostic performance will be reported as the area under the receiver operating characteristic curve. Clinically significant PCa is defined as the International Society of Urological grade group ≥2. Full-mount RP histopathology will be used as the reference standard. Secondary outcomes will be sensitivity, specificity, negative predictive value, and positive predictive value for csPCa on a per-patient level, evaluated in patients included prior to prostate biopsy, using biopsy results as the reference standard. A further analysis will be performed on the ability of the algorithm to differentiate between low-, intermediate-, and high-risk tumors. Discussion and summary This study aims to develop an ultrasound-based imaging modality for PCa detection. Subsequent head-to-head validation trials with magnetic resonance imaging have to be performed in order to determine its role in clinical practice for risk stratification in patients suspected for PCa.
Collapse
|
12
|
Song J, Zhao C, Zhang F, Yuan Y, Wang LM, Sah V, Zhang J, Weng W, Yang Z, Wang Z, Wang L. The diagnostic performance in clinically significant prostate cancer with PI-RADS version 2.1: simplified bpMRI versus standard mpMRI. Abdom Radiol (NY) 2023; 48:704-712. [PMID: 36464756 DOI: 10.1007/s00261-022-03750-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 11/13/2022] [Accepted: 11/14/2022] [Indexed: 12/07/2022]
Abstract
OBJECTIVES To compare the diagnostic performance for the detection of clinically significant prostate cancer (csPCa) between bpMRI with only axial T2WI (simplified bpMRI) and standard-multiparametric MRI (mpMRI). METHODS A total of 569 patients who underwent mpMRI followed by biopsy or prostatectomy were enrolled in this retrospective study. According to PI-RADS v2.1, three radiologists (A, B, C) from three centers blinded to clinical variables were assigned scores on lesions with simplified bpMRI and then with mpMRI 2 weeks later. Diagnostic performance of simplified bpMRI was compared with mpMRI using histopathology as reference standard. RESULTS For all the three radiologists, the diagnostic sensitivity was significantly higher with mpMRI than with simplified bpMRI (P < 0.001 to P = 0.035); and although specificity was also higher with mpMRI than with simplified bpMRI for radiologist B and radiologist C, it was statistically significant only for radiologist B (P = 0.011, P = 0.359, respectively). On the contrary, for radiologist A, specificity was higher with simplified bpMRI than with mpMRI (P = 0.001). The area under the receiver operating characteristic curve (AUC) was significantly higher for mpMRI than for simplified bpMRI except for radiologist A (radiologist A: 0.903 vs 0.913, P = 0.1542; radiologist B: 0.861 vs 0.834 P = 0.0013; and radiologist C: 0.884 vs 0.848, P = 0.0003). Interobserver reliability of PI-RADS v2.1 showed good agreement for both simplified bpMRI (kappa = 0.665) and mpMRI (kappa = 0.739). CONCLUSION Although the detection of csPCa with simplified bpMRI was comparatively lower than that with mpMRI, the diagnostic performance was still high in simplified bpMRI. Our data justify using mpMRI outperforms simplified bpMRI for prostate cancer screening and imply simplified bpMRI as a potential screening tool.
Collapse
Affiliation(s)
- Jihui Song
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
- Department of Radiology, Dalian University Affiliated Xinhua Hospital, No.156 Wansui Street, Shahekou District, Dalian, 116021, Liaoning, China
| | - Chenglin Zhao
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Fei Zhang
- Department of Radiology, QUFU City People Hospital, No.111 Chunqiu West Road, Qufu, 273100, Shandong, China
| | - Yingdi Yuan
- Department of Radiology, Ganzhou District People's Hospital, No.705 Beihuan Road, Ganzhou District, Zhangye, 734000, Gansu, China
| | - Lee M Wang
- Carnegie Mellon University, Pittsburgh, USA
| | - Vivek Sah
- ADK Hospital, Sosun Magu, Male, 20070, Maldives
| | - Jun Zhang
- Department of Radiology, The First Hospital of Qinhuangdao, No.258 Wenhua Road, Haigang District, Qinhuangdao, 066000, Hebei, China
| | - Wencai Weng
- Department of Radiology, Dalian University Affiliated Xinhua Hospital, No.156 Wansui Street, Shahekou District, Dalian, 116021, Liaoning, China
| | - Zhenghan Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zhenchang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Liang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
| |
Collapse
|
13
|
Are Urologists Ready for Interpretation of Multiparametric MRI Findings? A Prospective Multicentric Evaluation. Diagnostics (Basel) 2022; 12:diagnostics12112656. [PMID: 36359499 PMCID: PMC9689928 DOI: 10.3390/diagnostics12112656] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 10/26/2022] [Accepted: 10/27/2022] [Indexed: 11/06/2022] Open
Abstract
Aim: To assess urologists’ proficiency in the interpretation of multiparametric magnetic resonance imaging (mpMRI). Materials and Methods: Twelve mpMRIs were shown to 73 urologists from seven Italian institutions. Responders were asked to identify the site of the suspicious nodule (SN) but not to assign a PIRADS score. We set an a priori cut-off of 75% correct identification of SN as a threshold for proficiency in mpMRI reading. Data were analyzed according to urologists’ hierarchy (UH; resident vs. consultant) and previous experience in fusion prostate biopsies (E-fPB, defined as <125 vs. ≥125). Additionally, we tested for differences between non-proficient vs. proficient mpMRI readers. Multivariable logistic regression analyses (MVLRA) tested potential predictors of proficiency in mpMRI reading. Results: The median (IQR) number of correct identifications was 8 (6−8). Anterior nodules (number 3, 4 and 6) represented the most likely prone to misinterpretation. Overall, 34 (47%) participants achieved the 75% cut-off. When comparing consultants vs. residents, we found no differences in terms of E-fPB (p = 0.9) or in correct identification rates (p = 0.6). We recorded higher identification rates in urologists with E-fBP vs. their no E-fBP counterparts (75% vs. 67%, p = 0.004). At MVLRA, only E- fPB reached the status of independent predictor of proficiency in mpMRI reading (OR: 3.4, 95% CI 1.2−9.9, p = 0.02) after adjusting for UH and type of institution. Conclusions: Despite urologists becoming more familiar with interpretation of mpMRI, their results are still far from proficient. E-fPB enhances the proficiency in mpMRI interpretation.
Collapse
|
14
|
Alfano R, Bauman GS, Gomez JA, Gaed M, Moussa M, Chin J, Pautler S, Ward AD. Prostate cancer classification using radiomics and machine learning on mp-MRI validated using co-registered histology. Eur J Radiol 2022; 156:110494. [PMID: 36095953 DOI: 10.1016/j.ejrad.2022.110494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 07/04/2022] [Accepted: 08/16/2022] [Indexed: 11/21/2022]
Abstract
BACKGROUND Multi-parametric magnetic resonance imaging (mp-MRI) is emerging as a useful tool for prostate cancer (PCa) detection but currently has unaddressed limitations. Computer aided diagnosis (CAD) systems have been developed to address these needs, but many approaches used to generate and validate the models have inherent biases. METHOD All clinically significant PCa on histology was mapped to mp-MRI using a previously validated registration algorithm. Shape and size matched non-PCa regions were selected using a proposed sampling algorithm to eliminate biases towards shape and size. Further analysis was performed to assess biases regarding inter-zonal variability. RESULTS A 5-feature Naïve-Bayes classifier produced an area under the receiver operating characteristic curve (AUC) of 0.80 validated using leave-one-patient-out cross-validation. As mean inter-class area mismatch increased, median AUC trended towards positively biasing classifiers to producing higher AUCs. Classifiers were invariant to differences in shape between PCa and non-PCa lesions (AUC: 0.82 vs 0.82). Performance for models trained and tested only in the peripheral zone was found to be lower than in the central gland (AUC: 0.75 vs 0.95). CONCLUSION We developed a radiomics based machine learning system to classify PCa vs non-PCa tissue on mp-MRI validated on accurately co-registered mid-gland histology with a measured target registration error. Potential biases involved in model development were interrogated to provide considerations for future work in this area.
Collapse
Affiliation(s)
- Ryan Alfano
- Baines Imaging Research Laboratory, 790 Commissioners Rd E, London, ON N6A 5W9, Canada; Lawson Health Research Institute, 750 Base Line Rd E, London, ON N6C 2R5, Canada; Western University, Department of Medical Biophysics, 1151 Richmond St., London, ON N6A 3K7, Canada.
| | - Glenn S Bauman
- Western University, Department of Medical Biophysics, 1151 Richmond St., London, ON N6A 3K7, Canada; Western University, Department of Oncology, 1151 Richmond St., London, ON N6A 3K7, Canada.
| | - Jose A Gomez
- Western University, Department of Pathology and Laboratory Medicine, 1151 Richmond St., London, ON N6A 3K7, Canada.
| | - Mena Gaed
- Western University, Department of Pathology and Laboratory Medicine, 1151 Richmond St., London, ON N6A 3K7, Canada.
| | - Madeleine Moussa
- Western University, Department of Pathology and Laboratory Medicine, 1151 Richmond St., London, ON N6A 3K7, Canada.
| | - Joseph Chin
- Western University, Department of Surgery, 1151 Richmond St., London, ON N6A 3K7, Canada; Western University, Department of Oncology, 1151 Richmond St., London, ON N6A 3K7, Canada.
| | - Stephen Pautler
- Western University, Department of Surgery, 1151 Richmond St., London, ON N6A 3K7, Canada; Western University, Department of Oncology, 1151 Richmond St., London, ON N6A 3K7, Canada.
| | - Aaron D Ward
- Baines Imaging Research Laboratory, 790 Commissioners Rd E, London, ON N6A 5W9, Canada; Lawson Health Research Institute, 750 Base Line Rd E, London, ON N6C 2R5, Canada; Western University, Department of Medical Biophysics, 1151 Richmond St., London, ON N6A 3K7, Canada; Western University, Department of Oncology, 1151 Richmond St., London, ON N6A 3K7, Canada.
| |
Collapse
|
15
|
Grivas N, Lardas M, Espinós EL, Lam TB, Rouviere O, Mottet N, van den Bergh RCN. Prostate Cancer Detection Percentages of Repeat Biopsy in Patients with Positive Multiparametric Magnetic Resonance Imaging (Prostate Imaging Reporting and Data System/Likert 3-5) and Negative Initial Biopsy. A Mini Systematic Review. Eur Urol 2022; 82:452-457. [PMID: 35985901 DOI: 10.1016/j.eururo.2022.07.025] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 06/11/2022] [Accepted: 07/26/2022] [Indexed: 11/04/2022]
Abstract
Multiparametric magnetic resonance imaging (mpMRI) has high sensitivity but low specificity for prostate cancer (PCa) diagnosis. The aim of our systematic review was to investigate the proportion of PCa found at a repeat biopsy in patients with a negative initial prostate biopsy, despite initial positive mpMRI. Included patients had a Prostate Imaging Reporting and Data System (PI-RADS)/Likert 3-5 lesion on mpMRI prior to the initial mpMRI-targeted prostate biopsy, which was negative for PCa on histology. The main outcomes were the overall and clinically significant PCa (csPCa; International Society of Urological Pathology >1 or any provided definition) percentages at a repeat biopsy. Out of 1179 articles identified, nine studies were included (a total of 485 patients). For patients with PI-RADS 3 lesions, overall and csPCa detection percentages ranged from 0% to 80% and from 0% to 20%, respectively, while for patients with PI-RADS ≥4 lesions, the corresponding percentages were 15.4-86% and 7.7-57%. An overall cancer detection percentage of 87.5% was reported in patients with Likert 5 lesions. Limitation of our review is the small number of studies and the protocol revision that allowed studies with <50 patients. In patients with a positive MRI result and a negative initial MRI-targeted biopsy, we suggest MRI re-reading and follow-up with repeat mpMRI or the standard repeat biopsy in cases at the highest risk. PATIENT SUMMARY: Literature has shown that in men with an abnormal prostate magnetic resonance imaging (MRI) scan but a normal biopsy, a significant prostate cancer can be present. MRI scans should be double checked, followed by standard checkups or repeat prostate biopsy, especially in highly suspicious cases.
Collapse
Affiliation(s)
- Nikolaos Grivas
- Department of Urology, The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands; Department of Urology, Lefkos Stavros Hospital, Athens, Greece.
| | - Michael Lardas
- Department of Urology, Metropolitan General Hospital, Athens, Greece
| | | | - Thomas B Lam
- Department of Urology, Aberdeen Royal Infirmary, Aberdeen, UK
| | - Olivier Rouviere
- Hospices Civils de Lyon, Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Lyon, France
| | - Nicolas Mottet
- Department of Urology, University Hospital, St. Etienne, France
| | | | | |
Collapse
|
16
|
van Riel LA, Jager A, Meijer D, Postema AW, Smit RS, Vis AN, de Reijke TM, Beerlage HP, Oddens JR. Predictors of clinically significant prostate cancer in biopsy-naïve and prior negative biopsy men with a negative prostate MRI: improving MRI-based screening with a novel risk calculator. Ther Adv Urol 2022; 14:17562872221088536. [PMID: 35356754 PMCID: PMC8958520 DOI: 10.1177/17562872221088536] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 03/03/2022] [Indexed: 12/23/2022] Open
Abstract
Purpose: A pre-biopsy decision aid is needed to counsel men with a clinical suspicion for clinically significant prostate cancer (csPCa), despite normal prostate magnetic resonance imaging (MRI). Methods: A risk calculator (RC) for csPCa (International Society of Urological Pathology grade group (ISUP) ⩾ 2) presence in men with a negative-MRI (Prostate Imaging–Reporting and Data System (PI-RADS) ⩽ 2) was developed, and its performance was compared with RCs of the European Randomized Study of Screening for Prostate Cancer (ERSPC), Prostate Biopsy Collaborative Group (PBCG), and Prospective Loyola University mpMRI (PLUM). All biopsy-naïve and prior negative biopsy men with a negative-MRI followed by systematic prostate biopsy were included from October 2015 to September 2021. The RC was developed using multivariable logistic regression with the following parameters: age (years), family history of PCa (first- or second-degree family member), ancestry (African Caribbean/other), digital rectal exam (benign/malignant), MRI field strength (1.5/3.0 Tesla), prior negative biopsy status, and prostate-specific antigen (PSA) density (ng/ml/cc). Performance of RCs was compared using receiver operating characteristic (ROC) curve analysis. Results: A total of 232 men were included for analysis, of which 18.1% had csPCa. Parameters associated with csPCa were family history of PCa (p < 0.0001), African Caribbean ancestry (p = 0.005), PSA density (p = 0.002), prior negative biopsy (p = 0.06), and age at biopsy (p = 0.157). The area under the curve (AUC) of the developed RC was 0.76 (95% CI 0.68–0.85). This was significantly better than the RCs of the ERSPC (AUC: 0.59; p = 0.001) and PBCG (AUC: 0.60; p = 0.002), yet similar to PLUM (AUC: 0.69; p = 0.09). Conclusion: The developed RC (Prostate Biopsy Cohort Amsterdam (‘PROBA’ RC), integrated predictors for csPCa at prostate biopsy in negative-MRI men and outperformed other widely used RCs. These findings require external validation before introduction in daily practice.
Collapse
Affiliation(s)
- Luigi A.M.J.G. van Riel
- Department of Urology, Prostate Cancer Network in the Netherlands, Amsterdam University Medical Centers, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Auke Jager
- Department of Urology, Prostate Cancer Network in the Netherlands, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Dennie Meijer
- Department of Urology, Prostate Cancer Network in the Netherlands, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Arnoud W. Postema
- Department of Urology, Prostate Cancer Network in the Netherlands, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Ruth S. Smit
- Department of Radiology, Amsterdam University Medical Centers, VU University, Amsterdam, The Netherlands
| | - André N. Vis
- Department of Urology, Prostate Cancer Network in the Netherlands, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Theo M. de Reijke
- Department of Urology, Prostate Cancer Network in the Netherlands, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Harrie P. Beerlage
- Department of Urology, Prostate Cancer Network in the Netherlands, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Jorg R. Oddens
- Department of Urology, Prostate Cancer Network in the Netherlands, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| |
Collapse
|
17
|
Würnschimmel C, Chandrasekar T, Hahn L, Esen T, Shariat SF, Tilki D. MRI as a screening tool for prostate cancer: current evidence and future challenges. World J Urol 2022; 41:921-928. [PMID: 35226140 PMCID: PMC10160206 DOI: 10.1007/s00345-022-03947-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 01/19/2022] [Indexed: 10/19/2022] Open
Abstract
Abstract
Purpose
Prostate cancer (PCa) screening, which relies on prostate-specific antigen (PSA) testing, is a contentious topic that received negative attention due to the low sensitivity and specificity of PSA to detect clinically significant PCa. In this context, due to the higher sensitivity and specificity of magnetic resonance imaging (MRI), several trials investigate the feasibility of “MRI-only” screening approaches, and question if PSA testing may be replaced within prostate cancer screening programs.
Methods
This narrative review discusses the current literature and the outlook on the potential of MRI-based PCa screening.
Results
Several prospective randomized population-based trials are ongoing. Preliminary study results appear to favor the “MRI-only” approach. However, MRI-based PCa screening programs face a variety of obstacles that have yet to be fully addressed. These include the increased cost of MRI, lack of broad availability, differences in MRI acquisition and interpretation protocols, and lack of long-term impact on cancer-specific mortality. Partly, these issues are being addressed by shorter and simpler MRI approaches (5–20 min bi-parametric MRI), novel quality indicators (PI-QUAL) and the implementation of radiomics (deep learning, machine learning).
Conclusion
Although promising preliminary results were reported, MRI-based PCa screening still lack long-term data on crucial endpoints such as the impact of MRI screening on mortality. Furthermore, the issues of availability, cost-effectiveness, and differences in MRI acquisition and interpretation still need to be addressed.
Collapse
|
18
|
Deep learning for fully automatic detection, segmentation, and Gleason grade estimation of prostate cancer in multiparametric magnetic resonance images. Sci Rep 2022; 12:2975. [PMID: 35194056 PMCID: PMC8864013 DOI: 10.1038/s41598-022-06730-6] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 02/03/2022] [Indexed: 02/07/2023] Open
Abstract
Although the emergence of multi-parametric magnetic resonance imaging (mpMRI) has had a profound impact on the diagnosis of prostate cancers (PCa), analyzing these images remains still complex even for experts. This paper proposes a fully automatic system based on Deep Learning that performs localization, segmentation and Gleason grade group (GGG) estimation of PCa lesions from prostate mpMRIs. It uses 490 mpMRIs for training/validation and 75 for testing from two different datasets: ProstateX and Valencian Oncology Institute Foundation. In the test set, it achieves an excellent lesion-level AUC/sensitivity/specificity for the GGG\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$\ge$$\end{document}≥2 significance criterion of 0.96/1.00/0.79 for the ProstateX dataset, and 0.95/1.00/0.80 for the IVO dataset. At a patient level, the results are 0.87/1.00/0.375 in ProstateX, and 0.91/1.00/0.762 in IVO. Furthermore, on the online ProstateX grand challenge, the model obtained an AUC of 0.85 (0.87 when trained only on the ProstateX data, tying up with the original winner of the challenge). For expert comparison, IVO radiologist’s PI-RADS 4 sensitivity/specificity were 0.88/0.56 at a lesion level, and 0.85/0.58 at a patient level. The full code for the ProstateX-trained model is openly available at https://github.com/OscarPellicer/prostate_lesion_detection. We hope that this will represent a landmark for future research to use, compare and improve upon.
Collapse
|
19
|
Ferro M, de Cobelli O, Musi G, del Giudice F, Carrieri G, Busetto GM, Falagario UG, Sciarra A, Maggi M, Crocetto F, Barone B, Caputo VF, Marchioni M, Lucarelli G, Imbimbo C, Mistretta FA, Luzzago S, Vartolomei MD, Cormio L, Autorino R, Tătaru OS. Radiomics in prostate cancer: an up-to-date review. Ther Adv Urol 2022; 14:17562872221109020. [PMID: 35814914 PMCID: PMC9260602 DOI: 10.1177/17562872221109020] [Citation(s) in RCA: 53] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Accepted: 05/30/2022] [Indexed: 12/24/2022] Open
Abstract
Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male population. The diagnosis, the identification of aggressive disease, and the post-treatment follow-up needs a more comprehensive and holistic approach. Radiomics is the extraction and interpretation of images phenotypes in a quantitative manner. Radiomics may give an advantage through advancements in imaging modalities and through the potential power of artificial intelligence techniques by translating those features into clinical outcome prediction. This article gives an overview on the current evidence of methodology and reviews the available literature on radiomics in PCa patients, highlighting its potential for personalized treatment and future applications.
Collapse
Affiliation(s)
- Matteo Ferro
- Department of Urology, European Institute of Oncology, IRCCS, Milan, Italy, via Ripamonti 435 Milano, Italy
| | - Ottavio de Cobelli
- Department of Urology, European Institute of Oncology, IRCCS, Milan, Italy; Department of Oncology and Hematology-Oncology, Università degli Studi di Milano, Milan, Italy
| | - Gennaro Musi
- Department of Urology, European Institute of Oncology, IRCCS, Milan, Italy; Department of Oncology and Hematology-Oncology, Università degli Studi di Milano, Milan, Italy
| | - Francesco del Giudice
- Department of Urology, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Giuseppe Carrieri
- Department of Urology and Organ Transplantation, University of Foggia, Foggia, Italy
| | - Gian Maria Busetto
- Department of Urology and Organ Transplantation, University of Foggia, Foggia, Italy
| | | | - Alessandro Sciarra
- Department of Urology, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Martina Maggi
- Department of Urology, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Felice Crocetto
- Department of Neurosciences, Reproductive Sciences and Odontostomatology, University of Naples ‘Federico II’, Naples, Italy
| | - Biagio Barone
- Department of Neurosciences, Reproductive Sciences and Odontostomatology, University of Naples ‘Federico II’, Naples, Italy
| | - Vincenzo Francesco Caputo
- Department of Neurosciences, Reproductive Sciences and Odontostomatology, University of Naples ‘Federico II’, Naples, Italy
| | - Michele Marchioni
- Department of Medical, Oral and Biotechnological Sciences, G. d’Annunzio, University of Chieti, Chieti, Italy; Urology Unit, ‘SS. Annunziata’ Hospital, Chieti, Italy
- Department of Urology, ASL Abruzzo 2, Chieti, Italy
| | - Giuseppe Lucarelli
- Department of Emergency and Organ Transplantation, Urology, Andrology and Kidney Transplantation Unit, University of Bari, Bari, Italy
| | - Ciro Imbimbo
- Department of Neurosciences, Reproductive Sciences and Odontostomatology, University of Naples ‘Federico II’, Naples, Italy
| | - Francesco Alessandro Mistretta
- Department of Urology, European Institute of Oncology, IRCCS, Milan, Italy
- Università degli Studi di Milano, Milan, Italy
| | - Stefano Luzzago
- Department of Urology, European Institute of Oncology, IRCCS, Milan, Italy
- Università degli Studi di Milano, Milan, Italy
| | - Mihai Dorin Vartolomei
- Department of Cell and Molecular Biology, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mures, Târgu Mures, Romania
- Department of Urology, Medical University of Vienna, Vienna, Austria
| | - Luigi Cormio
- Urology and Renal Transplantation Unit, Department of Medical and Surgical Sciences, University of Foggia, Foggia, Italy
- Urology Unit, Bonomo Teaching Hospital, Foggia, Italy
| | | | - Octavian Sabin Tătaru
- Institution Organizing University Doctoral Studies, I.O.S.U.D., George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mures, Târgu Mures, Romania
| |
Collapse
|
20
|
Diagnostic accuracy and inter-observer reliability of the O-RADS scoring system among staff radiologists in a North American academic clinical setting. Abdom Radiol (NY) 2021; 46:4967-4973. [PMID: 34185128 DOI: 10.1007/s00261-021-03193-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 06/19/2021] [Accepted: 06/21/2021] [Indexed: 12/12/2022]
Abstract
PURPOSE The objective of this study is to evaluate the diagnostic accuracy, interobserver variability, and common lexicon pitfalls of the ACR O-RADS scoring system among staff radiologists without prior experience to O-RADS. MATERIALS AND METHODS After independent review of the ACR O-RADS publications and 30 training cases, three fellowship-trained, board-certified staff radiologists scored 50 pelvic ultrasound exams using the O-RADS system. The diagnostic accuracy and area under receiver operating characteristic were analyzed for each reader. Overall agreement and pair-wise agreement between readers were also analyzed. RESULTS Excellent specificities (92 to 100%), NPVs (92 to 100%), and variable sensitivities (72 to 100%), PPVs (66 to 100%) were observed. Considering O-RADS 4 and O-RADS 5 as predictors of malignancy, individual reader AUC values range from 0.94 to 0.98 (p < 0.001). Overall inter-reader agreement for all 3 readers was "very good," k = 0.82 (0.73 to 0.90, 95% CI, p < 0.001). Pair-wise agreement between readers were also "very good," k = 0.86-0.92. 14 out of 150 lesions were misclassified, with the most common error being down-scoring of a solid lesion with irregular outer contours. CONCLUSION Even without specific training, experienced ultrasound readers can achieve excellent diagnostic performance and high inter-reader reliability with self-directed review of guidelines and cases. The study highlights the effectiveness of ACR O-RADS as a stratification tool for radiologists and supports its continued use in practice.
Collapse
|
21
|
Prostate magnetic resonance imaging and the value of experience: An intrareader variability study. Asian J Urol 2021. [DOI: 10.1016/j.ajur.2021.08.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
|
22
|
Value of an online PI-RADS v2.1 score calculator for assessment of prostate MRI. Eur J Radiol Open 2021; 8:100332. [PMID: 33681427 PMCID: PMC7930347 DOI: 10.1016/j.ejro.2021.100332] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 02/04/2021] [Accepted: 02/14/2021] [Indexed: 11/23/2022] Open
Abstract
Purpose To evaluate the value of a browser-based PI-RADS Score Calculator (PCalc) compared to MRI reporting using the official PI-RADS v2.1 document (PDoc) for non-specialized radiologists in terms of reporting efficiency, interrater agreement and diagnostic accuracy for detection of clinically significant prostate cancer (PCa). Methods Between 09/2013 and 04/2015, 100 patients (median age, 64.8; range 47.5-78.2) who underwent prostate-MRI at a 3 T scanner and who received transperineal prostate mapping biopsy within <6 months were included in this retrospective study. Two non-specialized radiology residents (R1, R2) attributed a PI-RADS version 2.1 score for the most suspect (i. e. index) lesion (i) using the original PI-RADS v2.1 document only and after a 6-week interval (ii) using a browser-based PCalc. Reading time was measured. Reading time differences were assessed using Wilcoxon signed rank test. Intraclass-correlation Coefficient (ICC) was used to assess interrater agreement (IRA). Parameters of diagnostic accuracy and ROC curves were used for assessment of lesion-based diagnostic accuracy. Results Cumulative reading time was 32:55 (mm:ss) faster when using the PCalc, the difference being statistically significant for both readers (p < 0.05). The difference in IRA between the image sets (ICC 0.55 [0.40, 0.68]) and 0.75 [0.65, 0.82] for the image set with PDoc and PCalc, respectively) was not statistically significant. There was no statistically significant difference in lesion-based diagnostic accuracy (AUC 0.83 [0.74, 0.92] and 0.82 [95 %CI: 0.74, 0.91]) for images assessed with PDoc as compared to PCalc (AUC 0.82 [0.74, 0.91] and 0.74 [95 %CI: 0.64, 0.83]) for R1 and R2, respectively. Conclusion Non-specialized radiologists may increase reading speed in prostate MRI with the help of a browser-based PI-RADS Score Calculator compared to reporting using the official PI-RADS v2.1 document without impairing interreader agreement or lesion-based diagnostic accuracy for detection of clinically significant PCa.
Collapse
|
23
|
Magnetic Resonance Imaging Based Radiomic Models of Prostate Cancer: A Narrative Review. Cancers (Basel) 2021; 13:cancers13030552. [PMID: 33535569 PMCID: PMC7867056 DOI: 10.3390/cancers13030552] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2020] [Revised: 01/18/2021] [Accepted: 01/27/2021] [Indexed: 12/11/2022] Open
Abstract
Simple Summary The increasing interest in implementing artificial intelligence in radiomic models has occurred alongside advancement in the tools used for computer-aided diagnosis. Such tools typically apply both statistical and machine learning methodologies to assess the various modalities used in medical image analysis. Specific to prostate cancer, the radiomics pipeline has multiple facets that are amenable to improvement. This review discusses the steps of a magnetic resonance imaging based radiomics pipeline. Present successes, existing opportunities for refinement, and the most pertinent pending steps leading to clinical validation are highlighted. Abstract The management of prostate cancer (PCa) is dependent on biomarkers of biological aggression. This includes an invasive biopsy to facilitate a histopathological assessment of the tumor’s grade. This review explores the technical processes of applying magnetic resonance imaging based radiomic models to the evaluation of PCa. By exploring how a deep radiomics approach further optimizes the prediction of a PCa’s grade group, it will be clear how this integration of artificial intelligence mitigates existing major technological challenges faced by a traditional radiomic model: image acquisition, small data sets, image processing, labeling/segmentation, informative features, predicting molecular features and incorporating predictive models. Other potential impacts of artificial intelligence on the personalized treatment of PCa will also be discussed. The role of deep radiomics analysis-a deep texture analysis, which extracts features from convolutional neural networks layers, will be highlighted. Existing clinical work and upcoming clinical trials will be reviewed, directing investigators to pertinent future directions in the field. For future progress to result in clinical translation, the field will likely require multi-institutional collaboration in producing prospectively populated and expertly labeled imaging libraries.
Collapse
|
24
|
Ahmed HM, Ebeed AE, Hamdy A, El-Ghar MA, Razek AAKA. Interobserver agreement of Prostate Imaging–Reporting and Data System (PI-RADS–v2). THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2021. [DOI: 10.1186/s43055-020-00378-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Abstract
Background
A retrospective study was conducted on 71 consecutive patients with suspected prostate cancer (PCa) with a mean age of 56 years and underwent mp-MRI of the prostate at 3 Tesla MRI. Two readers recognized all prostatic lesions, and each lesion had a score according to Prostate Imaging–Reporting and Data System version 2 (PI-RADS-v2).
Purpose of the study
To evaluate the interobserver agreement of PI-RADS-v2 in characterization of prostatic lesions using multiparametric MRI (mp-MRI) at 3 Tesla MRI.
Results
The overall interobserver agreement of PI-RADS-v2 for both zones was excellent (k = 0.81, percent agreement = 94.9%). In the peripheral zone (PZ) lesions are the interobserver agreement for PI-RADS II (k = 0.78, percent agreement = 83.9%), PI-RADS III (k = 0.66, percent agreement = 91.3 %), PI-RADS IV (k = 0.69, percent agreement = 93.5%), and PI-RADS V (k = 0.91, percent agreement = 95.7 %). In the transitional zone (TZ) lesions are the interobserver agreement for PI-RADS I (k = 0.98, percent of agreement = 96%), PI-RADS II (k = 0.65, percent agreement = 96%), PI-RADS III (k = 0.65, percent agreement = 88%), PI-RADS IV (k = 0.83, percent agreement = 96%), and PI-RADS V (k = 0.82, percent agreement = 92%).
Conclusion
We concluded that PI-RADS-v2 is a reliable and a reproducible imaging modality for the characterization of prostatic lesions and detection of PCa.
Collapse
|
25
|
Walker SM, Türkbey B. PI-RADSv2.1: Current status. Turk J Urol 2020; 47:S45-S48. [PMID: 33052842 DOI: 10.5152/tud.2020.20403] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Accepted: 09/03/2020] [Indexed: 12/24/2022]
Abstract
Multiparametric magnetic resonance imaging (mpMRI) has played an increasing role in the detection and local staging of prostate cancer over the last 15 years. Prostate mpMRI, due to various factors, is prone to high inter-reader variability necessitating standardized reporting guidelines that provide accurate and actionable information to the ordering clinician. The Prostate Imaging-Reporting and Data System version 2.1 (PI-RADSv2.1) was released in March 2019 as an update to PI-RADSv2.0 with the hope of further standardizing the reporting process of prostate mpMRI, improving the detection of clinically significant cancer, reducing the biopsy rate of indolent tumors, and decreasing inter-reader variability. Early data show an improved performance of PI-RADSv2.1 over PI-RADSv2.0. Updates included in PI-RADSv2.1 and its current experience in clinic will be reviewed in this review.
Collapse
Affiliation(s)
- Stephanie M Walker
- Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Barış Türkbey
- Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| |
Collapse
|
26
|
PI-RADS Versions 2 and 2.1: Interobserver Agreement and Diagnostic Performance in Peripheral and Transition Zone Lesions Among Six Radiologists. AJR Am J Roentgenol 2020; 217:141-151. [PMID: 32903060 DOI: 10.2214/ajr.20.24199] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
BACKGROUND. PI-RADS version 2.1 (v2.1) modifications primarily address transition zone (TZ) interpretation. The revisions also impact peripheral zone (PZ) interpretation, which has received less attention. OBJECTIVE. The purpose of this study was to compare interobserver agreement of PI-RADS version 2 (v2) and v2.1 in the prostate PZ and TZ and perform a pilot comparison of their diagnostic performance in the two zones. METHODS. Six radiologists with varying experience retrospectively assessed 80 prostate lesions (40 PZ, 40 TZ) on MRI in separate sessions for PI-RADS v2 and v2.1. Interobserver agreement was assessed using Conger kappa (κ). For 50 lesions with pathology data, average AUC for detecting clinically significant cancer was compared between versions using multireader multicase statistical methods. Error variance and covariance results informed post hoc power analysis. RESULTS. Interobserver agreement for PI-RADS category 4 or greater was higher for version 2.1 (κ = 0.64) than version 2 (κ = 0.51) in the PZ, but similar for version 2 (κ = 0.64) and version 2.1 (κ = 0.60) in the TZ. The PI-RADS v2.1 DWI descriptor "linear/wedge-shaped" had higher agreement than its predecessor version 2 descriptor "indistinct hypointense" (κ = 0.52 vs κ = 0.18) and yielded 14 more true-negative versus five more false-negative interpretations. The ADC signal descriptor "markedly hypointense," for which only version 2.1 provides a specific definition, had lower agreement in version 2.1 (κ = 0.26) than version 2 (κ = 0.52). Modified TZ T2-weighted category 2 descriptors in version 2.1 had fair agreement (κ = 0.21), and agreement for PI-RADS category 2 in the TZ was lower in version 2.1 (κ = 0.31) than version 2 (κ = 0.57). DWI upgraded a TZ lesion category from 2 to 3 in four patients, detecting two additional cancers. Average AUC was not different between versions 2 and 2.1 for the PZ (AUC, 0.81 vs 0.85; p = .24) or the TZ (AUC, 0.69 vs 0.69; p = .94), though among experienced readers AUC was higher for version 2.1 than version 2 for the PZ (0.91 vs 0.82; p = .001). Overall performance comparison had sufficient power (0.8) to detect a 0.085 difference in AUC. CONCLUSION. Interobserver agreement improved using PI-RADS v2.1 in the PZ but not the TZ. Diagnostic performance improved using version 2.1 only in the PZ for experienced readers. Specific version 2.1 modifications yielded mixed results. CLINICAL IMPACT. The impact of PI-RADS v2.1 in the PZ is notable given the emphasis on version 2.1 TZ modifications. The findings suggest areas in which additional modification could further improve interobserver agreement and performance.
Collapse
|
27
|
Kim L, Boxall N, George A, Burling K, Acher P, Aning J, McCracken S, Page T, Gnanapragasam VJ. Clinical utility and cost modelling of the phi test to triage referrals into image-based diagnostic services for suspected prostate cancer: the PRIM (Phi to RefIne Mri) study. BMC Med 2020; 18:95. [PMID: 32299423 PMCID: PMC7164355 DOI: 10.1186/s12916-020-01548-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2019] [Accepted: 03/03/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND The clinical pathway to detect and diagnose prostate cancer has been revolutionised by the use of multiparametric MRI (mpMRI pre-biopsy). mpMRI however remains a resource-intensive test and is highly operator dependent with variable effectiveness with regard to its negative predictive value. Here we tested the use of the phi assay in standard clinical practice to pre-select men at the highest risk of harbouring significant cancer and hence refine the use of mpMRI and biopsies. METHODS A prospective five-centre study recruited men being investigated through an mpMRI-based prostate cancer diagnostic pathway. Test statistics for PSA, PSA density (PSAd) and phi were assessed for detecting significant cancers using 2 definitions: ≥ Grade Group (GG2) and ≥ Cambridge Prognostic Groups (CPG) 3. Cost modelling and decision curve analysis (DCA) was simultaneously performed. RESULTS A total of 545 men were recruited and studied with a median age, PSA and phi of 66 years, 8.0 ng/ml and 44 respectively. Overall, ≥ GG2 and ≥ CPG3 cancer detection rates were 64% (349/545), 47% (256/545) and 32% (174/545) respectively. There was no difference across centres for patient demographics or cancer detection rates. The overall area under the curve (AUC) for predicting ≥ GG2 cancers was 0.70 for PSA and 0.82 for phi. AUCs for ≥ CPG3 cancers were 0.81 and 0.87 for PSA and phi respectively. AUC values for phi did not differ between centres suggesting reliability of the test in different diagnostic settings. Pre-referral phi cut-offs between 20 and 30 had NPVs of 0.85-0.90 for ≥ GG2 cancers and 0.94-1.0 for ≥ CPG3 cancers. A strategy of mpMRI in all and biopsy only positive lesions reduced unnecessary biopsies by 35% but missed 9% of ≥ GG2 and 5% of ≥ CPG3 cancers. Using PH ≥ 30 to rule out referrals missed 8% and 5% of ≥ GG2 and ≥ CPG3 cancers (and reduced unnecessary biopsies by 40%). This was achieved however with 25% fewer mpMRI. Pathways incorporating PSAd missed fewer cancers but necessitated more unnecessary biopsies. The phi strategy had the lowest mean costs with DCA demonstrating net clinical benefit over a range of thresholds. CONCLUSION phi as a triaging test may be an effective way to reduce mpMRI and biopsies without compromising detection of significant prostate cancers.
Collapse
Affiliation(s)
- Lois Kim
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Nicholas Boxall
- Department of Urology, Cambridge University Hospitals Trust, Cambridge, UK
| | - Anne George
- Urological Malignancies Programme CRUK & Cambridge Urology Translational Research and Clinical Trials Office, University of Cambridge Box 193, Cambridge Biomedical Campus Cambridge CB20QQ, Cambridge, UK
| | - Keith Burling
- NIHR Cambridge Biomedical Research Centre, Core Biochemical Assay Laboratory, University of Cambridge, Cambridge, UK
| | - Pete Acher
- Department of Urology, Southend Hospital, Essex, UK
| | - Jonathan Aning
- Department of Urology, North Bristol NHS Trust, Bristol, UK
| | - Stuart McCracken
- Department of Urology, South Tyneside and Sunderland NHS Trust, Sunderland, UK
| | - Toby Page
- Department of Urology, Newcastle Hospitals NHS Trust, Newcastle upon Tyne, UK
| | - Vincent J Gnanapragasam
- Department of Urology, Cambridge University Hospitals Trust, Cambridge, UK. .,Urological Malignancies Programme CRUK & Cambridge Urology Translational Research and Clinical Trials Office, University of Cambridge Box 193, Cambridge Biomedical Campus Cambridge CB20QQ, Cambridge, UK. .,Academic Urology Group, Department of Surgery, University of Cambridge, Cambridge, UK.
| |
Collapse
|