1
|
Sørland KI, Trimble CG, Wu CY, Bathen TF, Elschot M, Cloos MA. Reducing femoral flow artefacts in radial magnetic resonance fingerprinting of the prostate using region-optimised virtual coils. NMR IN BIOMEDICINE 2024; 37:e5136. [PMID: 38514929 DOI: 10.1002/nbm.5136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 01/19/2024] [Accepted: 02/07/2024] [Indexed: 03/23/2024]
Abstract
High acceleration factors in radial magnetic resonance fingerprinting (MRF) of the prostate lead to strong streak-like artefacts from flow in the femoral blood vessels, possibly concealing important anatomical information. Region-optimised virtual (ROVir) coils is a beamforming-based framework to create virtual coils that maximise signal in a region of interest while minimising signal in a region of interference. In this study, the potential of removing femoral flow streak artefacts in prostate MRF using ROVir coils is demonstrated in silico and in vivo. The ROVir framework was applied to radial MRF k-space data in an automated pipeline designed to maximise prostate signal while minimising signal from the femoral vessels. The method was tested in 15 asymptomatic volunteers at 3 T. The presence of streaks was visually assessed and measurements of whole prostate T1, T2 and signal-to-noise ratio (SNR) with and without streak correction were examined. In addition, a purpose-built simulation framework in which blood flow through the femoral vessels can be turned on and off was used to quantitatively evaluate ROVir's ability to suppress streaks in radial prostate MRF. In vivo it was shown that removing selected ROVir coils visibly reduces streak-like artefacts from the femoral blood flow, without increasing the reconstruction time. On average, 80% of the prostate SNR was retained. A similar reduction of streaks was also observed in silico, while the quantitative accuracy of T1 and T2 mapping was retained. In conclusion, ROVir coils efficiently suppress streaking artefacts from blood flow in radial MRF of the prostate, thereby improving the visual clarity of the images, without significant sacrifices to acquisition time, reconstruction time and accuracy of quantitative values. This is expected to help enable T1 and T2 mapping of prostate cancer in clinically viable times, aiding differentiation between prostate cancer from noncancer and healthy prostate tissue.
Collapse
Affiliation(s)
- Kaia I Sørland
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
| | - Christopher G Trimble
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Radiology and Nuclear Medicine, St. Olavs hospital, Trondheim University Hostpital, Trondheim, Norway
| | - Chia-Yin Wu
- Centre for Advanced Imaging, The University of Queensland, St Lucia, Queensland, Australia
- ARC Training Centre for Innovation on Biomedical Imaging Technology (CIBIT), The University of Queensland, St Lucia, Queensland, Australia
- School of Electrical Engineering and Computer Science, The University of Queensland, St Lucia, Queensland, Australia
| | - Tone F Bathen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Radiology and Nuclear Medicine, St. Olavs hospital, Trondheim University Hostpital, Trondheim, Norway
| | - Mattijs Elschot
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Radiology and Nuclear Medicine, St. Olavs hospital, Trondheim University Hostpital, Trondheim, Norway
| | - Martijn A Cloos
- Centre for Advanced Imaging, The University of Queensland, St Lucia, Queensland, Australia
- ARC Training Centre for Innovation on Biomedical Imaging Technology (CIBIT), The University of Queensland, St Lucia, Queensland, Australia
| |
Collapse
|
2
|
Agrotis G, Pooch E, Abdelatty M, Benson S, Vassiou A, Vlychou M, Beets-Tan RGH, Schoots IG. Diagnostic performance of ADC and ADCratio in MRI-based prostate cancer assessment: A systematic review and meta-analysis. Eur Radiol 2024:10.1007/s00330-024-10890-6. [PMID: 38995382 DOI: 10.1007/s00330-024-10890-6] [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: 02/18/2024] [Revised: 04/26/2024] [Accepted: 05/19/2024] [Indexed: 07/13/2024]
Abstract
OBJECTIVES To identify factors influencing the diagnostic performance of the quantitative imaging biomarkers ADC and ADCratio in prostate cancer (PCa) detection. MATERIALS AND METHODS A systematic literature search was conducted in Embase, Medline and Web of Science, for studies evaluating ADC values and ADCratio for PCa diagnosis, using the same patient cohorts and using histopathological references as ground truth. Pooled sensitivities, specificities, summary ROC curves and AUCs were calculated from constructed contingency data tables. Diagnostic performance (AUC) was quantitatively pooled using a bivariate mixed effects model. For identifying influencing factors, subgroup analysis, publication bias and heterogeneity assessment were investigated. RESULTS Thirteen studies, involving 1038 patients and 1441 lesions, were included. For ADC, the pooled sensitivity and specificity was 80% (95% CI: 74-85%) and 78% (95% CI: 70-85%), respectively. For ADCratio pooled sensitivity and specificity was 80% (95% CI: 74-84%) and 80% (95% CI: 71-87%). Summary ROC analysis revealed AUCs of 0.86 (95% CI: 0.83-0.89) and 0.86 (95% CI: 0.83-0.89), respectively. Meta-regression showed heterogeneity between both imaging biomarkers. Subgroup analysis showed that ADCratio improved diagnostic performance in comparison to ADC when including both peripheral and transitional zone lesions (AUC: 0.87 [95% CI: 0.84-0.90] and 0.82 [95% CI: 0.79-0.85], respectively). CONCLUSION Both ADC and ADCratio imaging biomarkers showed good and comparable diagnostic performance in PCa diagnosis. However, ADCratio shows better diagnostic performance than ADC in diagnosing transition zone cancers. CLINICAL RELEVANCE STATEMENT In quantitative MRI-based PCa diagnosis, the imaging biomarker ADCratio is useful in challenging MRI readings of lesions. Understanding the performance of quantitative imaging biomarkers better can aid diagnostic MRI protocols, enhancing the precision of PCa assessments. KEY POINTS MRI diffusion-weighted imaging-based ADC and ADCratio have comparable diagnostic performance in PCa assessment. In contrast to ADC, the ADCratio improves diagnostic performance, when assessing whole gland lesions. Compared to ADCratio, the ADC demonstrates enhanced diagnostic performance when evaluating peripheral zone lesions.
Collapse
Affiliation(s)
- Georgios Agrotis
- Department of Radiology, University Hospital of Larissa, Larissa, Greece.
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
| | - Eduardo Pooch
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
- GROW School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - Mohamed Abdelatty
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
- Department of Diagnostic and Interventional Radiology, Kasr Al-Ainy Hospital, Cairo University, Giza, Egypt
| | - Sean Benson
- Department of Diagnostic and Interventional Radiology, Kasr Al-Ainy Hospital, Cairo University, Giza, Egypt
| | - Aikaterini Vassiou
- Department of Radiology, University Hospital of Larissa, Larissa, Greece
| | - Marianna Vlychou
- Department of Radiology, University Hospital of Larissa, Larissa, Greece
| | - Regina G H Beets-Tan
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
- GROW School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - Ivo G Schoots
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
- Department of Radiology & Nuclear Medicine, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| |
Collapse
|
3
|
Sheng Y, Chang H, Xue K, Chen J, Jiao T, Cui D, Wang H, Zhang G, Yang Y, Zeng Q. Characterization of prostatic cancer lesion and gleason grade using a continuous-time random-walk diffusion model at high b-values. Front Oncol 2024; 14:1389250. [PMID: 38854720 PMCID: PMC11157027 DOI: 10.3389/fonc.2024.1389250] [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] [Received: 02/21/2024] [Accepted: 05/07/2024] [Indexed: 06/11/2024] Open
Abstract
Background Distinguishing between prostatic cancer (PCa) and chronic prostatitis (CP) is sometimes challenging, and Gleason grading is strongly associated with prognosis in PCa. The continuous-time random-walk diffusion (CTRW) model has shown potential in distinguishing between PCa and CP as well as predicting Gleason grading. Purpose This study aimed to quantify the CTRW parameters (α, β & Dm) and apparent diffusion coefficient (ADC) of PCa and CP tissues; and then assess the diagnostic value of CTRW and ADC parameters in differentiating CP from PCa and low-grade PCa from high-grade PCa lesions. Study type Retrospective (retrospective analysis using prospective designed data). Population Thirty-one PCa patients undergoing prostatectomy (mean age 74 years, range 64-91 years), and thirty CP patients undergoing prostate needle biopsies (mean age 68 years, range 46-79 years). Field strength/Sequence MRI scans on a 3.0T scanner (uMR790, United Imaging Healthcare, Shanghai, China). DWI were acquired with 12 b-values (0, 50, 100, 150, 200, 500, 800, 1200, 1500, 2000, 2500, 3000 s/mm2). Assessment CTRW parameters and ADC were quantified in PCa and CP lesions. Statistical tests The Mann-Whitney U test was used to evaluate the differences in CTRW parameters and ADC between PCa and CP, high-grade PCa, and low-grade PCa. Spearman's correlation of the pathologic grading group (GG) with CTRW parameters and ADC was evaluated. The usefulness of CTRW parameters, ADC, and their combinations (Dm, α and β; Dm, α, β, and ADC) to differentiate PCa from CP and high-grade PCa from low-grade PCa was determined by logistic regression and receiver operating characteristic curve (ROC) analysis. Delong test was used to compare the differences among AUCs. Results Significant differences were found for the CTRW parameters (α, Dm) between CP and PCa (all P<0.001), high-grade PCa, and low-grade PCa (α:P=0.024, Dm:P=0.021). GG is correlated with certain CTRW parameters and ADC(α:P<0.001,r=-0.795; Dm:P<0.001,r=-0.762;ADC:P<0.001,r=-0.790). Moreover, CTRW parameters (α, β, Dm) combined with ADC showed the best diagnostic efficacy for distinguishing between PCa and CP as well as predicting Gleason grading. The differences among AUCs of ADC, CTRW parameters and their combinations were not statistically significant (P=0.051-0.526). Conclusion CTRW parameters α and Dm, as well as their combination were beneficial to distinguish between CA and PCa, low-grade PCa and high-grade PCa lesions, and CTRW parameters and ADC had comparable diagnostic performance.
Collapse
Affiliation(s)
- Yurui Sheng
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China
| | - Huan Chang
- Department of Radiology, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan, Shandong, China
| | - Ke Xue
- Magnenic Resonance (MR) Collaboration, United Imaging Research Institute of Intelligent Imaging, Beijing, China
| | - Jinming Chen
- Department of Radiology, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan, Shandong, China
| | - Tianyu Jiao
- Department of Radiology, Shandong Public Health Clinical Center, Jinan, Shandong, China
| | - Dongqing Cui
- Department of Neurology, The Second Hospital of Shandong University, Jinan, Shandong, China
| | - Hao Wang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China
| | - Guanghui Zhang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China
| | - Yuxin Yang
- Magnenic Resonance (MR) Collaboration, United Imaging Research Institute of Intelligent Imaging, Beijing, China
| | - Qingshi Zeng
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China
| |
Collapse
|
4
|
Das CJ, Malagi AV, Sharma R, Mehndiratta A, Kumar V, Khan MA, Seth A, Kaushal S, Nayak B, Kumar R, Gupta AK. Intravoxel incoherent motion and diffusion kurtosis imaging and their machine-learning-based texture analysis for detection and assessment of prostate cancer severity at 3 T. NMR IN BIOMEDICINE 2024:e5144. [PMID: 38556777 DOI: 10.1002/nbm.5144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 02/01/2024] [Accepted: 02/20/2024] [Indexed: 04/02/2024]
Abstract
OBJECTIVES To evaluate the role of combined intravoxel incoherent motion and diffusion kurtosis imaging (IVIM-DKI) and their machine-learning-based texture analysis for the detection and assessment of severity in prostate cancer (PCa). MATERIALS AND METHODS Eighty-eight patients underwent MRI on a 3 T scanner after giving informed consent. IVIM-DKI data were acquired using 13 b values (0-2000 s/mm2) and analyzed using the IVIM-DKI model with the total variation (TV) method. PCa patients were categorized into two groups: clinically insignificant prostate cancer (CISPCa) (Gleason grade ≤ 6) and clinically significant prostate cancer (CSPCa) (Gleason grade ≥ 7). One-way analysis-of-variance, t test, and receiver operating characteristic analysis was performed to measure the discriminative ability to detect PCa using IVIM-DKI parameters. A chi-square test was used to select important texture features of apparent diffusion coefficient (ADC) and IVIM-DKI parameters. These selected texture features were used in an artificial neural network for PCa detection. RESULTS ADC and diffusion coefficient (D) were significantly lower (p < 0.001), and kurtosis (k) was significantly higher (p < 0.001), in PCa as compared with benign prostatic hyperplasia (BPH) and normal peripheral zone (PZ). ADC, D, and k showed high areas under the curves (AUCs) of 0.92, 0.89, and 0.88, respectively, in PCa detection. ADC and D were significantly lower (p < 0.05) as compared with CISPCa versus CSPCa. D for detecting CSPCa was high, with an AUC of 0.63. A negative correlation of ADC and D with GS (ADC, ρ = -0.33; D, ρ = -0.35, p < 0.05) and a positive correlation of k with GS (ρ = 0.22, p < 0.05) were observed. Combined IVIM-DKI texture showed high AUC of 0.83 for classification of PCa, BPH, and normal PZ. CONCLUSION D, f, and k computed using the IVIM-DKI model with the TV method were able to differentiate PCa from BPH and normal PZ. Texture features of combined IVIM-DKI parameters showed high accuracy and AUC in PCa detection.
Collapse
Affiliation(s)
- Chandan J Das
- Department of Radio-Diagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi, India
| | - Archana Vadiraj Malagi
- Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Raju Sharma
- Department of Radio-Diagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi, India
| | - Amit Mehndiratta
- Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Virendra Kumar
- Department of Nuclear Magnetic Resonance, All India Institute of Medical Sciences, New Delhi, India
| | - Maroof A Khan
- Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, India
| | - Amlesh Seth
- Department of Urology, All India Institute of Medical Sciences, New Delhi, India
| | - Seema Kaushal
- Department of Pathology, All India Institute of Medical Sciences, New Delhi, India
| | - Baibaswata Nayak
- Department of Gastroenterology (Molecular Biology Division), All India Institute of Medical Sciences, New Delhi, India
| | - Rakesh Kumar
- Department of Nuclear Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Arun Kumar Gupta
- Department of Radio-Diagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi, India
| |
Collapse
|
5
|
Lorenzo G, Heiselman JS, Liss MA, Miga MI, Gomez H, Yankeelov TE, Reali A, Hughes TJ. A Pilot Study on Patient-specific Computational Forecasting of Prostate Cancer Growth during Active Surveillance Using an Imaging-informed Biomechanistic Model. CANCER RESEARCH COMMUNICATIONS 2024; 4:617-633. [PMID: 38426815 PMCID: PMC10906139 DOI: 10.1158/2767-9764.crc-23-0449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 12/15/2023] [Accepted: 02/09/2024] [Indexed: 03/02/2024]
Abstract
Active surveillance (AS) is a suitable management option for newly diagnosed prostate cancer, which usually presents low to intermediate clinical risk. Patients enrolled in AS have their tumor monitored via longitudinal multiparametric MRI (mpMRI), PSA tests, and biopsies. Hence, treatment is prescribed when these tests identify progression to higher-risk prostate cancer. However, current AS protocols rely on detecting tumor progression through direct observation according to population-based monitoring strategies. This approach limits the design of patient-specific AS plans and may delay the detection of tumor progression. Here, we present a pilot study to address these issues by leveraging personalized computational predictions of prostate cancer growth. Our forecasts are obtained with a spatiotemporal biomechanistic model informed by patient-specific longitudinal mpMRI data (T2-weighted MRI and apparent diffusion coefficient maps from diffusion-weighted MRI). Our results show that our technology can represent and forecast the global tumor burden for individual patients, achieving concordance correlation coefficients from 0.93 to 0.99 across our cohort (n = 7). In addition, we identify a model-based biomarker of higher-risk prostate cancer: the mean proliferation activity of the tumor (P = 0.041). Using logistic regression, we construct a prostate cancer risk classifier based on this biomarker that achieves an area under the ROC curve of 0.83. We further show that coupling our tumor forecasts with this prostate cancer risk classifier enables the early identification of prostate cancer progression to higher-risk disease by more than 1 year. Thus, we posit that our predictive technology constitutes a promising clinical decision-making tool to design personalized AS plans for patients with prostate cancer. SIGNIFICANCE Personalization of a biomechanistic model of prostate cancer with mpMRI data enables the prediction of tumor progression, thereby showing promise to guide clinical decision-making during AS for each individual patient.
Collapse
Affiliation(s)
- Guillermo Lorenzo
- Department of Civil Engineering and Architecture, University of Pavia, Pavia, Italy
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas
| | - Jon S. Heiselman
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - Michael A. Liss
- Department of Urology, The University of Texas Health Science Center at San Antonio, San Antonio, Texas
| | - Michael I. Miga
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Neurological Surgery, Radiology, and Otolaryngology-Head and Neck Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Hector Gomez
- School of Mechanical Engineering, Weldon School of Biomedical Engineering, and Purdue Institute for Cancer Research, Purdue University, West Lafayette, Indiana
| | - Thomas E. Yankeelov
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas
- Livestrong Cancer Institutes and Departments of Biomedical Engineering, Diagnostic Medicine, and Oncology, The University of Texas at Austin, Austin, Texas
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Alessandro Reali
- Department of Civil Engineering and Architecture, University of Pavia, Pavia, Italy
| | - Thomas J.R. Hughes
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas
| |
Collapse
|
6
|
Qin X, Lv J, Zhang J, Mu R, Zheng W, Liu F, Huang B, Li X, Yang P, Deng K, Zhu X. Amide proton transfer imaging has added value for predicting extraprostatic extension in prostate cancer patients. Front Oncol 2024; 14:1327046. [PMID: 38496759 PMCID: PMC10941336 DOI: 10.3389/fonc.2024.1327046] [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] [Received: 10/24/2023] [Accepted: 02/12/2024] [Indexed: 03/19/2024] Open
Abstract
Background Prostate cancer invades the capsule is a key factor in selecting appropriate treatment methods. Accurate preoperative prediction of extraprostatic extension (EPE) can help achieve precise selection of treatment plans. Purpose The aim of this study is to verify the diagnostic efficacy of tumor size, length of capsular contact (LCC), apparent diffusion coefficient (ADC), and Amide proton transfer (APT) value in predicting EPE. Additionally, the study aims to investigate the potential additional value of APT for predicting EPE. Method This study include 47 tumor organ confined patients (age, 64.16 ± 9.18) and 50 EPE patients (age, 61.51 ± 8.82). The difference of tumor size, LCC, ADC and APT value between groups were compared. Binary logistic regression was used to screen the EPE predictors. The receiver operator characteristic curve analysis was performed to assess the diagnostic performance of variables for predicting EPE. The diagnostic efficacy of combined models (model I: ADC+LCC+tumor size; model II: APT+LCC+tumor size; and model III: APT +ADC+LCC+tumor size) were also analyzed. Results APT, ADC, tumor size and the LCC were independent predictors of EPE. The area under the curve (AUC) of APT, ADC, tumor size and the LCC were 0.752, 0.665, 0.700 and 0.756, respectively. The AUC of model I, model II, and model III were 0.803, 0.845 and 0.869, respectively. The cutoff value of APT, ADC, tumor size and the LCC were 3.65%, 0.97×10-3mm2/s, 17.30mm and 10.78mm, respectively. The sensitivity/specificity of APT, ADC, tumor size and the LCC were 76%/89.4.0%, 80%/59.6%, 54%/78.9%, 72%/66%, respectively. The sensitivity/specificity of model I, Model II and Model III were 74%/72.3%, 82%/72.5% and 84%/80.9%, respectively. Data conclusion Amide proton transfer imaging has added value for predicting EPE. The combination model of APT balanced the sensitivity and specificity.
Collapse
Affiliation(s)
- Xiaoyan Qin
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Jian Lv
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Jianmei Zhang
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Ronghua Mu
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Wei Zheng
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Fuzhen Liu
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Bingqin Huang
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
- Department of Radiology, Graduate School of Guilin Medical University, Guilin, China
| | - Xin Li
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Peng Yang
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Kan Deng
- Philips (China) Investment Co., Ltd., Guangzhou Branch, Guangzhou, China
| | - Xiqi Zhu
- Department of Radiology, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China
| |
Collapse
|
7
|
Recchimuzzi DZ, Diaz de Leon A, Pedrosa I, Travalini D, Latin H, Goldberg K, Meng X, Begovic J, Rayan J, Roehrborn CG, Rofsky NM, Costa DN. Direct MRI-guided In-Bore Targeted Biopsy of the Prostate: A Step-by-Step How To and Lessons Learned. Radiographics 2024; 44:e230142. [PMID: 38175803 DOI: 10.1148/rg.230142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2024]
Abstract
Multiparametric MRI-the most accurate imaging technique for detection of prostate cancer-has transformed the landscape of prostate cancer diagnosis by enabling targeted biopsies. In a targeted biopsy, tissue samples are obtained from suspicious regions identified at prebiopsy diagnostic MRI. The authors briefly compare the different strategies available for targeting an MRI-visible suspicious lesion, followed by a step-by-step description of the direct MRI-guided in-bore approach and an illustrated review of its application in challenging clinical scenarios. In this technique, direct visualization of the needle, needle guide, and needle trajectory during the procedure provides a precise and versatile strategy to accurately sample suspicious lesions, improving detection of clinically significant cancers. Published under a CC BY 4.0 license Test Your Knowledge questions for this article are available in the supplemental material.
Collapse
Affiliation(s)
- Debora Z Recchimuzzi
- From the Departments of Radiology (D.Z.R., I.P., D.T., H.L., J.B., J.R., N.M.R., D.N.C.) and Urology (I.P., K.G., X.M., C.G.R., D.N.C.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Dallas, TX 75390; and Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (A.D.d.L.)
| | - Alberto Diaz de Leon
- From the Departments of Radiology (D.Z.R., I.P., D.T., H.L., J.B., J.R., N.M.R., D.N.C.) and Urology (I.P., K.G., X.M., C.G.R., D.N.C.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Dallas, TX 75390; and Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (A.D.d.L.)
| | - Ivan Pedrosa
- From the Departments of Radiology (D.Z.R., I.P., D.T., H.L., J.B., J.R., N.M.R., D.N.C.) and Urology (I.P., K.G., X.M., C.G.R., D.N.C.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Dallas, TX 75390; and Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (A.D.d.L.)
| | - Debbie Travalini
- From the Departments of Radiology (D.Z.R., I.P., D.T., H.L., J.B., J.R., N.M.R., D.N.C.) and Urology (I.P., K.G., X.M., C.G.R., D.N.C.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Dallas, TX 75390; and Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (A.D.d.L.)
| | - Heather Latin
- From the Departments of Radiology (D.Z.R., I.P., D.T., H.L., J.B., J.R., N.M.R., D.N.C.) and Urology (I.P., K.G., X.M., C.G.R., D.N.C.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Dallas, TX 75390; and Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (A.D.d.L.)
| | - Kenneth Goldberg
- From the Departments of Radiology (D.Z.R., I.P., D.T., H.L., J.B., J.R., N.M.R., D.N.C.) and Urology (I.P., K.G., X.M., C.G.R., D.N.C.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Dallas, TX 75390; and Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (A.D.d.L.)
| | - Xiaosong Meng
- From the Departments of Radiology (D.Z.R., I.P., D.T., H.L., J.B., J.R., N.M.R., D.N.C.) and Urology (I.P., K.G., X.M., C.G.R., D.N.C.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Dallas, TX 75390; and Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (A.D.d.L.)
| | - Jovan Begovic
- From the Departments of Radiology (D.Z.R., I.P., D.T., H.L., J.B., J.R., N.M.R., D.N.C.) and Urology (I.P., K.G., X.M., C.G.R., D.N.C.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Dallas, TX 75390; and Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (A.D.d.L.)
| | - Jesse Rayan
- From the Departments of Radiology (D.Z.R., I.P., D.T., H.L., J.B., J.R., N.M.R., D.N.C.) and Urology (I.P., K.G., X.M., C.G.R., D.N.C.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Dallas, TX 75390; and Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (A.D.d.L.)
| | - Claus G Roehrborn
- From the Departments of Radiology (D.Z.R., I.P., D.T., H.L., J.B., J.R., N.M.R., D.N.C.) and Urology (I.P., K.G., X.M., C.G.R., D.N.C.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Dallas, TX 75390; and Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (A.D.d.L.)
| | - Neil M Rofsky
- From the Departments of Radiology (D.Z.R., I.P., D.T., H.L., J.B., J.R., N.M.R., D.N.C.) and Urology (I.P., K.G., X.M., C.G.R., D.N.C.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Dallas, TX 75390; and Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (A.D.d.L.)
| | - Daniel N Costa
- From the Departments of Radiology (D.Z.R., I.P., D.T., H.L., J.B., J.R., N.M.R., D.N.C.) and Urology (I.P., K.G., X.M., C.G.R., D.N.C.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Dallas, TX 75390; and Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (A.D.d.L.)
| |
Collapse
|
8
|
Hanzlikova P, Vilimek D, Vilimkova Kahankova R, Ladrova M, Skopelidou V, Ruzickova Z, Martinek R, Cvek J. Longitudinal analysis of T2 relaxation time variations following radiotherapy for prostate cancer. Heliyon 2024; 10:e24557. [PMID: 38298676 PMCID: PMC10828070 DOI: 10.1016/j.heliyon.2024.e24557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 12/02/2023] [Accepted: 01/10/2024] [Indexed: 02/02/2024] Open
Abstract
Aim of this paper is to evaluate short and long-term changes in T 2 relaxation times after radiotherapy in patients with low and intermediate risk localized prostate cancer. A total of 24 patients were selected for this retrospective study. Each participant underwent 1.5T magnetic resonance imaging on seven separate occasions: initially after the implantation of gold fiducials, the required step for Cyberknife therapy guidance, followed by MRI scans two weeks post-therapy and monthly thereafter. As part of each MRI scan, the prostate region was manually delineated, and the T 2 relaxation times were calculated for quantitative analysis. The T 2 relaxation times between individual follow-ups were analyzed using Repeated Measures Analysis of Variance that revealed a significant difference across all measurements (F (6, 120) = 0.611, p << 0.001). A Bonferroni post hoc test revealed significant differences in median T 2 values between the baseline and subsequent measurements, particularly between pre-therapy (M 0 ) and two weeks post-therapy (M 1 ), as well as during the monthly interval checks (M 2 - M 6 ). Some cases showed a delayed decrease in relaxation times, indicating the prolonged effects of therapy. The changes in T 2 values during the course of radiotherapy can help in monitoring radiotherapy response in unconfirmed patients, quantifying the scarring process, and recognizing the therapy failure.
Collapse
Affiliation(s)
- Pavla Hanzlikova
- Department of Radiology, University Hospital Ostrava, Czech Republic
- Department of Imaging Methods, Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic
| | - Dominik Vilimek
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB - Technical University of Ostrava, 17. listopadu 15, Ostrava – Poruba, 708 00, Czech Republic
| | - Radana Vilimkova Kahankova
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB - Technical University of Ostrava, 17. listopadu 15, Ostrava – Poruba, 708 00, Czech Republic
| | - Martina Ladrova
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB - Technical University of Ostrava, 17. listopadu 15, Ostrava – Poruba, 708 00, Czech Republic
| | - Valeria Skopelidou
- Institute of Molecular and Clinical Pathology and Medical Genetics, University Hospital Ostrava, 70852, Ostrava, Czech Republic
- Institute of Molecular and Clinical Pathology and Medical Genetics, Faculty of Medicine, University of Ostrava, 70300, Ostrava, Czech Republic
| | - Zuzana Ruzickova
- Faculty of Medicine, University of Ostrava, 70300 Ostrava, Czech Republic
- Department of Oncology, University Hospital Ostrava, 70852 Ostrava, Czech Republic
| | - Radek Martinek
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB - Technical University of Ostrava, 17. listopadu 15, Ostrava – Poruba, 708 00, Czech Republic
| | - Jakub Cvek
- Faculty of Medicine, University of Ostrava, 70300 Ostrava, Czech Republic
- Department of Oncology, University Hospital Ostrava, 70852 Ostrava, Czech Republic
| |
Collapse
|
9
|
Xiao VG, Kresnanto J, Moses DA, Pather N. Quantitative MRI in the Local Staging of Prostate Cancer: A Systematic Review and Meta-Analysis. J Magn Reson Imaging 2024; 59:255-296. [PMID: 37165923 DOI: 10.1002/jmri.28742] [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: 12/05/2022] [Revised: 04/04/2023] [Accepted: 04/04/2023] [Indexed: 05/12/2023] Open
Abstract
BACKGROUND Local staging of prostate cancer (PCa) is important for treatment planning. Radiologist interpretation using qualitative criteria is variable with high specificity but low sensitivity. Quantitative methods may be useful in the diagnosis of extracapsular extension (ECE). PURPOSE To assess the performance of quantitative MRI markers for detecting ECE. STUDY TYPE Systematic review and meta-analysis. SUBJECTS 4800 patients from 28 studies with histopathologically confirmed PCa on radical prostatectomy were pooled for meta-analysis. Patients from 46 studies were included for systematic review. FIELD STRENGTH/SEQUENCE Diffusion-weighted, T2-weighted, and dynamic contrast-enhanced MRI at 1.5 T or 3 T. ASSESSMENT PubMed, Embase, Web of Science, Scopus, and Cochrane databases were searched to identify studies on diagnostic test accuracy or association of any quantitative MRI markers with ECE. Results extracted by two independent reviewers for tumor contact length (TCL) and mean apparent diffusion coefficient (ADC-mean) were pooled for meta-analysis, but not for other quantitative markers including radiomics due to low number of studies available. STATISTICAL TESTS Hierarchical summary receiver operating characteristic (HSROC) curves were computed for both TCL and ADC-mean, but summary operating points were computed for TCL only. Heterogeneity was investigated by meta-regression. Results were significant if P ≤ 0.05. RESULTS At the 10 mm threshold for TCL, summary sensitivity and specificity were 0.76 [95% confidence interval (CI) 0.71-0.81] and 0.68 [95% CI 0.63-0.73], respectively. At the 15 mm threshold, summary sensitivity and specificity were 0.70 [95% CI 0.53-0.83] and 0.74 [95% CI 0.60-0.84] respectively. The area under the HSROC curves for TCL and ADC-mean were 0.79 and 0.78, respectively. Significant sources of heterogeneity for TCL included timing of MRI relative to biopsy. DATA CONCLUSION Both 10 mm and 15 mm thresholds for TCL may be reasonable for clinical use. From comparison of the HSROC curves, ADC-mean may be superior to TCL at higher sensitivities. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY STAGE: 2.
Collapse
Affiliation(s)
- Vieley G Xiao
- Medical Education, Faculty of Medicine and Health, University of New South Wales, Kensington, New South Wales, 2052, Australia
- School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Kensington, New South Wales, 2052, Australia
| | - Jordan Kresnanto
- School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Kensington, New South Wales, 2052, Australia
| | - Daniel A Moses
- Graduate School of Biomedical Engineering, Faculty of Engineering, University of New South Wales, Kensington, New South Wales, 2052, Australia
- Prince of Wales Hospital, Sydney, New South Wales, 2031, Australia
| | - Nalini Pather
- Medical Education, Faculty of Medicine and Health, University of New South Wales, Kensington, New South Wales, 2052, Australia
- School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Kensington, New South Wales, 2052, Australia
| |
Collapse
|
10
|
Abreu-Gomez J, Lim C, Haider MA. Contemporary Approach to Prostate Imaging and Data Reporting System Score 3 Lesions. Radiol Clin North Am 2024; 62:37-51. [PMID: 37973244 DOI: 10.1016/j.rcl.2023.06.008] [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] [Indexed: 11/19/2023]
Abstract
The aim of this article is to review the technical and clinical considerations encountered with PI-RADS 3 lesions, which are equivocal for clinically significant Prostate Cancer (csPCa) with detection rates ranging between 10% and 35%. The number of PI-RADS 3 lesions reported vary according to several factors including MRI quality and radiologist training/expertise among the most influential. PI-RADS v.2.1 updated definitions for scores 2 and 3 in the PZ and scores 1 and 2 in the TZ is reviewed. The role of DWI role is highlighted in the assessment of the TZ with the possibility of upgrading score 2 lesions to score 3 based on DWI score. Given the increased utilization for prostate MRI, biparametric MRI can be considered as an alternative for low-risk patients where there is a need to rule out csPCa acknowledging this technique may increase the number of indeterminate cases going for biopsies. Management of patients with equivocal lesions at mpMRI and factors influencing biopsy decision process remain as an unmet need and additional studies using molecular/imaging markers as well as artificial intelligence tools are needed to further address their role in proper patient selection for biopsy.
Collapse
Affiliation(s)
- Jorge Abreu-Gomez
- Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, 610 University Avenue, Suite 3-920, Toronto, ON M5G 2M9, Canada.
| | - Christopher Lim
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Avenue, Room AB 279, Toronto, ON M4N 3M5, Canada
| | - Masoom A Haider
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System and the Joint Department of Medical Imaging, Sinai Health System, Princess Margaret Hospital, University of Toronto, 600 University Avenue, Toronto, ON, Canada M5G 1X5
| |
Collapse
|
11
|
Mori N, Mugikura S, Takase K. The role of magnetic resonance imaging in prostate cancer patients on active surveillance. Br J Radiol 2023; 96:20220140. [PMID: 35604720 PMCID: PMC10607394 DOI: 10.1259/bjr.20220140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 02/23/2022] [Indexed: 11/05/2022] Open
Affiliation(s)
- Naoko Mori
- Department of Diagnostic Radiology, Tohoku University Graduate School of Medicine, Seiryo 1-1, Sendai, Japan
| | | | - Kei Takase
- Department of Diagnostic Radiology, Tohoku University Graduate School of Medicine, Seiryo 1-1, Sendai, Japan
| |
Collapse
|
12
|
Dominguez I, Rios-Ibacache O, Caprile P, Gonzalez J, San Francisco IF, Besa C. MRI-Based Surrogate Imaging Markers of Aggressiveness in Prostate Cancer: Development of a Machine Learning Model Based on Radiomic Features. Diagnostics (Basel) 2023; 13:2779. [PMID: 37685317 PMCID: PMC10486695 DOI: 10.3390/diagnostics13172779] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 08/15/2023] [Accepted: 08/17/2023] [Indexed: 09/10/2023] Open
Abstract
This study aimed to develop a noninvasive Machine Learning (ML) model to identify clinically significant prostate cancer (csPCa) according to Gleason Score (GS) based on biparametric MRI (bpMRI) radiomic features and clinical information. METHODS This retrospective study included 86 adult Hispanic men (60 ± 8.2 years, median prostate-specific antigen density (PSA-D) 0.15 ng/mL2) with PCa who underwent prebiopsy 3T MRI followed by targeted MRI-ultrasound fusion and systematic biopsy. Two observers performed 2D segmentation of lesions in T2WI/ADC images. We classified csPCa (GS ≥ 7) vs. non-csPCa (GS = 6). Univariate statistical tests were performed for different parameters, including prostate volume (PV), PSA-D, PI-RADS, and radiomic features. Multivariate models were built using the automatic feature selection algorithm Recursive Feature Elimination (RFE) and different classifiers. A stratified split separated the train/test (80%) and validation (20%) sets. RESULTS Radiomic features derived from T2WI/ADC are associated with GS in patients with PCa. The best model found was multivariate, including image (T2WI/ADC) and clinical (PV and PSA-D) information. The validation area under the curve (AUC) was 0.80 for differentiating csPCa from non-csPCa, exhibiting better performance than PI-RADS (AUC: 0.71) and PSA-D (AUC: 0.78). CONCLUSION Our multivariate ML model outperforms PI-RADS v2.1 and established clinical indicators like PSA-D in classifying csPCa accurately. This underscores MRI-derived radiomics' (T2WI/ADC) potential as a robust biomarker for assessing PCa aggressiveness in Hispanic patients.
Collapse
Affiliation(s)
- Ignacio Dominguez
- Department of Radiology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago 8320000, Chile;
| | - Odette Rios-Ibacache
- Institute of Physics, Pontifical Catholic University of Chile, Av. Vicuña Mackenna 4860, Macul, Santiago 7820436, Chile;
- Medical Physics Unit, McGill University, Montreal, QC H4A 3J1, Canada
| | - Paola Caprile
- Institute of Physics, Pontifical Catholic University of Chile, Av. Vicuña Mackenna 4860, Macul, Santiago 7820436, Chile;
- Millennium Institute for Intelligent Healthcare Engineering, iHEALTH, ANID, Macul, Santiago 7820436, Chile
| | - Jose Gonzalez
- School of Medicine, Pontifical Catholic University of Chile, Santiago 8320000, Chile
| | - Ignacio F. San Francisco
- Department of Urology, School of Medicine, Pontifical Catholic University of Chile, Santiago 8320000, Chile
| | - Cecilia Besa
- Department of Radiology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago 8320000, Chile;
- Millennium Institute for Intelligent Healthcare Engineering, iHEALTH, ANID, Macul, Santiago 7820436, Chile
| |
Collapse
|
13
|
Jager A, Postema AW, van der Linden H, Nooijen PTGA, Bekers E, Kweldam CF, Daures G, Zwart W, Mischi M, Beerlage HP, Oddens JR. Reliability of whole mount radical prostatectomy histopathology as the ground truth for artificial intelligence assisted prostate imaging. Virchows Arch 2023; 483:197-206. [PMID: 37407736 PMCID: PMC10412486 DOI: 10.1007/s00428-023-03589-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 06/05/2023] [Accepted: 06/26/2023] [Indexed: 07/07/2023]
Abstract
The development of artificial intelligence-based imaging techniques for prostate cancer (PCa) detection and diagnosis requires a reliable ground truth, which is generally based on histopathology from radical prostatectomy specimens. This study proposes a comprehensive protocol for the annotation of prostatectomy pathology slides. To evaluate the reliability of the protocol, interobserver variability was assessed between five pathologists, who annotated ten radical prostatectomy specimens consisting of 74 whole mount pathology slides. Interobserver variability was assessed for both the localization and grading of PCa. The results indicate excellent overall agreement on the localization of PCa (Gleason pattern ≥ 3) and clinically significant PCa (Gleason pattern ≥ 4), with Dice similarity coefficients (DSC) of 0.91 and 0.88, respectively. On a per-slide level, agreement for primary and secondary Gleason pattern was almost perfect and substantial, with Fleiss Kappa of .819 (95% CI .659-.980) and .726 (95% CI .573-.878), respectively. Agreement on International Society of Urological Pathology Grade Group was evaluated for the index lesions and showed agreement in 70% of cases, with a mean DSC of 0.92 for all index lesions. These findings show that a standardized protocol for prostatectomy pathology annotation provides reliable data on PCa localization and grading, with relatively high levels of interobserver agreement. More complicated tissue characterization, such as the presence of cribriform growth and intraductal carcinoma, remains a source of interobserver variability and should be treated with care when used in ground truth datasets.
Collapse
Affiliation(s)
- Auke Jager
- Amsterdam UMC, University of Amsterdam, Department of Urology, Meibergdreef 9, Amsterdam, The Netherlands.
| | - Arnoud W Postema
- Amsterdam UMC, University of Amsterdam, Department of Urology, Meibergdreef 9, Amsterdam, The Netherlands
- Department of Urology, Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Hans van der Linden
- Pathology DNA, Jeroen Bosch Hospital, Henri Dunantstraat 1, 5223, GZ, 's-Hertogenbosch, The Netherlands
| | - Peet T G A Nooijen
- Pathology DNA, Jeroen Bosch Hospital, Henri Dunantstraat 1, 5223, GZ, 's-Hertogenbosch, The Netherlands
| | - Elise Bekers
- Department of Pathology, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | | | - Gautier Daures
- Angiogenesis Analytics, JADS Venture Campus, 's-Hertogenbosch, AA, The Netherlands
| | - Wim Zwart
- Angiogenesis Analytics, JADS Venture Campus, 's-Hertogenbosch, AA, The Netherlands
| | - M Mischi
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Harrie P Beerlage
- Amsterdam UMC, University of Amsterdam, Department of Urology, Meibergdreef 9, Amsterdam, The Netherlands
| | - Jorg R Oddens
- Amsterdam UMC, University of Amsterdam, Department of Urology, Meibergdreef 9, Amsterdam, The Netherlands
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| |
Collapse
|
14
|
Özer H, Koplay M, Baytok A, Seher N, Demir LS, Kılınçer A, Kaynar M, Göktaş S. Texture analysis of multiparametric magnetic resonance imaging for differentiating clinically significant prostate cancer in the peripheral zone. Turk J Med Sci 2023; 53:701-711. [PMID: 37476894 PMCID: PMC10387871 DOI: 10.55730/1300-0144.5633] [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: 07/31/2022] [Accepted: 02/01/2023] [Indexed: 07/22/2023] Open
Abstract
BACKGROUND Texture analysis (TA) provides additional tissue heterogeneity data that may assist in differentiating peripheral zone(PZ) lesions in multiparametric magnetic resonance imaging (mpMRI). This study investigates the role of magnetic resonance imaging texture analysis (MRTA) in detecting clinically significant prostate cancer (csPCa) in the PZ. METHODS This retrospective study included 80 consecutive patients who had an mpMRI and a prostate biopsy for suspected prostate cancer. Two radiologists in consensus interpreted mpMRI and performed texture analysis based on their histopathology. The first-, second-, and higher-order texture parameters were extracted from mpMRI and were compared between groups. Univariate and multivariate logistic regression analyses were performed using the texture parameters to determine the independent predictors of csPCa. Receiver operating characteristic (ROC) curve analysis was conducted to assess the diagnostic performance of the texture parameters. RESULTS : In the periferal zone, 39 men had csPCa, while 41 had benign lesions or clinically insignificant prostate cancer (cisPCa). Themajority of texture parameters showed statistically significant differences between the groups. Univariate ROC analysis showed that the ADC mean and ADC median were the best variables in differentiating csPCa (p < 0.001). The first-order logistic regression model (mean + entropy) based on the ADC maps had a higher AUC value (0.996; 95% CI: 0.989-1) than other texture-based logistic regression models (p < 0.001). DISCUSSION MRTA is useful in differentiating csPCa from other lesions in the PZ. Consequently, the first-order multivariate regressionmodel based on ADC maps had the highest diagnostic performance in differentiating csPCa.
Collapse
Affiliation(s)
- Halil Özer
- Department of Radiology, Faculty of Medicine, Selcuk University, Konya, Turkey
| | - Mustafa Koplay
- Department of Radiology, Faculty of Medicine, Selcuk University, Konya, Turkey
| | - Ahmet Baytok
- Department of Radiology, Faculty of Medicine, Selcuk University, Konya, Turkey
| | - Nusret Seher
- Department of Radiology, Faculty of Medicine, Selcuk University, Konya, Turkey
| | - Lütfi Saltuk Demir
- Department of Public Health, Faculty of Medicine, Necmettin Erbakan University, Konya, Turkey
| | - Abidin Kılınçer
- Department of Radiology, Faculty of Medicine, Selcuk University, Konya, Turkey
| | - Mehmet Kaynar
- Department of Urology, Faculty of Medicine, Selcuk University, Konya, Turkey
| | - Serdar Göktaş
- Department of Urology, Faculty of Medicine, Selcuk University, Konya, Turkey
| |
Collapse
|
15
|
Comparison of Diffusion Kurtosis Imaging and Standard Mono-Exponential Apparent Diffusion Coefficient in Diagnosis of Significant Prostate Cancer-A Correlation with Gleason Score Assessed on Whole-Mount Histopathology Specimens. Diagnostics (Basel) 2023; 13:diagnostics13020173. [PMID: 36672983 PMCID: PMC9858256 DOI: 10.3390/diagnostics13020173] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 12/29/2022] [Accepted: 01/01/2023] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND The study was undertaken to compare the diagnostic performance of diffusion kurtosis imaging (DKI) with the standard monoexponential (ME) apparent diffusion coefficient (ADC) model in the detection of significant prostate cancer (PCa), using whole-mount histopathology of radical prostatectomy specimens as a reference standard. METHODS 155 patients with prostate cancer had undergone multiparametric magnetic resonance imaging (mpMRI) at 3T before prostatectomy. Quantitative diffusion parameters-the apparent diffusion coefficient corrected for non-Gaussian behavior (Dapp), kurtosis (K), ADC1200, and ADC2000 were correlated with Gleason score and compared between cancerous and benign tissue and between GS ≤ 3 + 3 and GS ≥ 3 + 4 tumors. RESULTS The mean values of all diffusion parameters (Dapp, K, ADC1200, ADC2000) were significantly different both between malignant and benign tissue and between GS ≤ 3 + 3 and GS ≥ 3 + 4 tumors. Although the kurtosis model was better fitted to DWI data, the diagnostic performance in receiver operating characteristic (ROC) analysis of DKI and the standard ADC model in the detection of significant PCa was similar in the peripheral zone (PZ) and in peripheral and transitional zones (TZ) together. In conclusion, our study was not able to demonstrate a clear superiority of the kurtosis model over standard ADC in the diagnosis of significant PCa in PZ and in both zones combined.
Collapse
|
16
|
Harmath C. Prospective Validation of MRI Signal Abnormalities and Clinically Significant Cancer. Radiology 2022; 307:e222436. [PMID: 36511810 DOI: 10.1148/radiol.222436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Carla Harmath
- From the Department of Radiology, University of Chicago Medicine, 5841 S Maryland Ave, Room Q202, Chicago, IL 60637
| |
Collapse
|
17
|
Tamada T, Kido A, Ueda Y, Takeuchi M, Kanki A, Neelavalli J, Yamamoto A. Comparison of single-shot EPI and multi-shot EPI in prostate DWI at 3.0 T. Sci Rep 2022; 12:16070. [PMID: 36168032 PMCID: PMC9515065 DOI: 10.1038/s41598-022-20518-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 09/14/2022] [Indexed: 12/02/2022] Open
Abstract
In prostate MRI, single-shot EPI (ssEPI) DWI still suffers from distortion and blurring. Multi-shot EPI (msEPI) overcomes the drawbacks of ssEPI DWI. The aim of this article was to compare the image quality and diagnostic performance for clinically significant prostate cancer (csPC) between ssEPI DWI and msEPI DWI. This retrospective study included 134 patients with suspected PC who underwent 3.0 T MRI and subsequent MRI-guided biopsy. Three radiologists independently assessed anatomical distortion, prostate edge clarity, and lesion conspicuity score for pathologically confirmed csPC. Lesion apparent diffusion coefficient (ADC) and benign ADC were also calculated. In 17 PC patients who underwent prostatectomy, three radiologists independently assessed eight prostate regions by DWI score in PI-RADS v 2.1. Anatomical distortion and prostate edge clarity were significantly higher in msEPI DWI than in ssEPI DWI in the three readers. Lesion conspicuity score was significantly higher in msEPI DWI than in ssEPI DWI in reader 1 and reader 3. Regarding discrimination ability between PC with GS ≤ 3 + 4 and PC with GS ≥ 4 + 3 using lesion ADC, AUC was comparable between ssEPI DWI and msEPI DWI. For diagnostic performance of csPC using DWI score, AUC was comparable between msEPI DWI and ssEPI DWI in all readers. Compared with ssEPI DWI, msEPI DWI had improved image quality and similar or higher diagnostic performance.
Collapse
Affiliation(s)
- Tsutomu Tamada
- Department of Radiology, Kawasaki Medical School, 577 Matsushima, Kurashiki, Okayama, 701-0192, Japan.
| | - Ayumu Kido
- Department of Radiology, Kawasaki Medical School, 577 Matsushima, Kurashiki, Okayama, 701-0192, Japan
| | | | | | - Akihiko Kanki
- Department of Radiology, Kawasaki Medical School, 577 Matsushima, Kurashiki, Okayama, 701-0192, Japan
| | | | - Akira Yamamoto
- Department of Radiology, Kawasaki Medical School, 577 Matsushima, Kurashiki, Okayama, 701-0192, Japan
| |
Collapse
|
18
|
Dwivedi DK, Jagannathan NR. Emerging MR methods for improved diagnosis of prostate cancer by multiparametric MRI. MAGMA (NEW YORK, N.Y.) 2022; 35:587-608. [PMID: 35867236 DOI: 10.1007/s10334-022-01031-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 06/28/2022] [Accepted: 07/08/2022] [Indexed: 06/15/2023]
Abstract
Current challenges of using serum prostate-specific antigen (PSA) level-based screening, such as the increased false positive rate, inability to detect clinically significant prostate cancer (PCa) with random biopsy, multifocality in PCa, and the molecular heterogeneity of PCa, can be addressed by integrating advanced multiparametric MR imaging (mpMRI) approaches into the diagnostic workup of PCa. The standard method for diagnosing PCa is a transrectal ultrasonography (TRUS)-guided systematic prostate biopsy, but it suffers from sampling errors and frequently fails to detect clinically significant PCa. mpMRI not only increases the detection of clinically significant PCa, but it also helps to reduce unnecessary biopsies because of its high negative predictive value. Furthermore, non-Cartesian image acquisition and compressed sensing have resulted in faster MR acquisition with improved signal-to-noise ratio, which can be used in quantitative MRI methods such as dynamic contrast-enhanced (DCE)-MRI. With the growing emphasis on the role of pre-biopsy mpMRI in the evaluation of PCa, there is an increased demand for innovative MRI methods that can improve PCa grading, detect clinically significant PCa, and biopsy guidance. To meet these demands, in addition to routine T1-weighted, T2-weighted, DCE-MRI, diffusion MRI, and MR spectroscopy, several new MR methods such as restriction spectrum imaging, vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT) method, hybrid multi-dimensional MRI, luminal water imaging, and MR fingerprinting have been developed for a better characterization of the disease. Further, with the increasing interest in combining MR data with clinical and genomic data, there is a growing interest in utilizing radiomics and radiogenomics approaches. These big data can also be utilized in the development of computer-aided diagnostic tools, including automatic segmentation and the detection of clinically significant PCa using machine learning methods.
Collapse
Affiliation(s)
- Durgesh Kumar Dwivedi
- Department of Radiodiagnosis, King George Medical University, Lucknow, UP, 226 003, India.
| | - Naranamangalam R Jagannathan
- Department of Radiology, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Kelambakkam, TN, 603 103, India.
- Department of Radiology, Sri Ramachandra Institute of Higher Education and Research, Chennai, TN, 600 116, India.
- Department of Electrical Engineering, Indian Institute Technology Madras, Chennai, TN, 600 036, India.
| |
Collapse
|
19
|
Pseudo-T2 mapping for normalization of T2-weighted prostate MRI. MAGMA (NEW YORK, N.Y.) 2022; 35:573-585. [PMID: 35150363 PMCID: PMC9363383 DOI: 10.1007/s10334-022-01003-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 12/22/2021] [Accepted: 01/23/2022] [Indexed: 01/04/2023]
Abstract
Objective Signal intensity normalization is necessary to reduce heterogeneity in T2-weighted (T2W) magnetic resonance imaging (MRI) for quantitative analysis of multicenter data. AutoRef is an automated dual-reference tissue normalization method that normalizes transversal prostate T2W MRI by creating a pseudo-T2 map. The aim of this study was to evaluate the accuracy of pseudo-T2s and multicenter standardization performance for AutoRef with three pairs of reference tissues: fat/muscle (AutoRefF), femoral head/muscle (AutoRefFH) and pelvic bone/muscle (AutoRefPB). Materials and methods T2s measured by multi-echo spin echo (MESE) were compared to AutoRef pseudo-T2s in the whole prostate (WP) and zones (PZ and TZ/CZ/AFS) for seven asymptomatic volunteers with a paired Wilcoxon signed-rank test. AutoRef normalization was assessed on T2W images from a multicenter evaluation set of 1186 prostate cancer patients. Performance was measured by inter-patient histogram intersections of voxel intensities in the WP before and after normalization in a selected subset of 80 cases. Results AutoRefFH pseudo-T2s best approached MESE T2s in the volunteer study, with no significant difference shown (WP: p = 0.30, TZ/CZ/AFS: p = 0.22, PZ: p = 0.69). All three AutoRef versions increased inter-patient histogram intersections in the multicenter dataset, with median histogram intersections of 0.505 (original data), 0.738 (AutoRefFH), 0.739 (AutoRefF) and 0.726 (AutoRefPB). Discussion All AutoRef versions reduced variation in the multicenter data. AutoRefFH pseudo-T2s were closest to experimentally measured T2s. Supplementary Information The online version contains supplementary material available at 10.1007/s10334-022-01003-9.
Collapse
|
20
|
So S, Park HW, Kim B, Fritz FJ, Poser BA, Roebroeck A, Bilgic B. BUDA-MESMERISE: Rapid acquisition and unsupervised parameter estimation for T 1 , T 2 , M 0 , B 0 , and B 1 maps. Magn Reson Med 2022; 88:292-308. [PMID: 35344611 DOI: 10.1002/mrm.29228] [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: 08/12/2021] [Revised: 02/21/2022] [Accepted: 02/22/2022] [Indexed: 11/10/2022]
Abstract
PURPOSE Rapid acquisition scheme and parameter estimation method are proposed to acquire distortion-free spin- and stimulated-echo signals and combine the signals with a physics-driven unsupervised network to estimate T1 , T2 , and proton density (M0 ) parameter maps, along with B0 and B1 information from the acquired signals. THEORY AND METHODS An imaging sequence with three 90° RF pulses is utilized to acquire spin- and stimulated-echo signals. We utilize blip-up/-down acquisition to eliminate geometric distortion incurred by the effects of B0 inhomogeneity on rapid EPI acquisitions. For multislice imaging, echo-shifting is applied to utilize dead time between the second and third RF pulses to encode information from additional slice positions. To estimate parameter maps from the spin- and stimulated-echo signals with high fidelity, 2 estimation methods, analytic fitting and a novel unsupervised deep neural network method, are developed. RESULTS The proposed acquisition provided distortion-free T1 , T2 , relative proton density (M0), B0 , and B1 maps with high fidelity both in phantom and in vivo brain experiments. From the rapidly acquired spin- and stimulated-echo signals, analytic fitting and the network-based method were able to estimate T1 , T2 , M0 , B0 , and B1 maps with high accuracy. Network estimates demonstrated noise robustness owing to the fact that the convolutional layers take information into account from spatially adjacent voxels. CONCLUSION The proposed acquisition/reconstruction technique enabled whole-brain acquisition of coregistered, distortion-free, T1 , T2 , M0 , B0 , and B1 maps at 1 × 1 × 5 mm3 resolution in 50 s. The proposed unsupervised neural network provided noise-robust parameter estimates from this rapid acquisition.
Collapse
Affiliation(s)
- Seohee So
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Hyun Wook Park
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Byungjai Kim
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Francisco J Fritz
- Institute of Systems Neuroscience, Center for Experimental Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Benedikt A Poser
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Alard Roebroeck
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Charlestown, Massachusetts, USA.,Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| |
Collapse
|
21
|
Lee YS, Choi MH, Lee YJ, Han D, Kim DH. Magnetic resonance fingerprinting in prostate cancer before and after contrast enhancement. Br J Radiol 2022; 95:20210479. [PMID: 34415785 PMCID: PMC8978224 DOI: 10.1259/bjr.20210479] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVES To assess the apparent diffusion coefficient (ADC) values and the T1 and T2 values derived from nonenhanced (NE) and contrast-enhanced (CE) magnetic resonance fingerprinting (MRF) in the prostate gland and to evaluate differences in values among prostate cancer, the normal peripheral zone (PZ) and the normal transition zone (TZ). METHODS Fifty-seven patients (median age, 73 years; range, 48-86) with prostate cancer who underwent multiparametric MRI including NE and CE MRF were included in this study. T1 and T2 values were extracted from NE and CE MRF, respectively. Five quantitative values (the ADC, NE T1, NE T2, CE T1 and CE T2 values) were measured in three areas: prostate cancer, PZ and TZ. We compared the values among the three areas and evaluated the differences between NE MRF and CE MRF values. RESULTS ADC values and MRF-derived values were significantly higher in PZ than prostate cancer or TZ (p < 0.001). TZ had a significantly lower CE T1 but significantly higher values of the other variables than prostate cancer (p < 0.001). The T1 values in all three areas and the T2 values in prostate cancer and TZ were significantly lower on CE MRF than on NE MRF (p < 0.001). CONCLUSIONS Quantitative analysis of NE and CE MRI can be conducted by using the MRF technique. The ADC value and the T1 and T2 values from CE MRF and NE MRF were found to be significantly different between prostate cancer and normal prostate tissue. ADVANCES IN KNOWLEDGE The T1 and T2 values from contrast-enhanced MR fingerprinting are significantly different between prostate cancer and normal prostate tissue.
Collapse
Affiliation(s)
- Young Sub Lee
- Department of Hospital Pathology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Moon Hyung Choi
- Department of Radiology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Young Joon Lee
- Department of Radiology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Dongyeob Han
- Siemens Healthineers Ltd., Seoul, Republic of Korea
| | - Dong-Hyun Kim
- School of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea
| |
Collapse
|
22
|
Li W, Shang W, Lu F, Sun Y, Tian J, Wu Y, Dong A. Diagnostic Performance of Extraprostatic Extension Grading System for Detection of Extraprostatic Extension in Prostate Cancer: A Diagnostic Systematic Review and Meta-Analysis. Front Oncol 2022; 11:792120. [PMID: 35145904 PMCID: PMC8824228 DOI: 10.3389/fonc.2021.792120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Accepted: 12/27/2021] [Indexed: 11/13/2022] Open
Abstract
Purpose To evaluate the diagnostic performance of the extraprostatic extension (EPE) grading system for detection of EPE in patients with prostate cancer (PCa). Materials and Methods We performed a literature search of Web of Science, MEDLINE (Ovid and PubMed), Cochrane Library, EMBASE, and Google Scholar to identify eligible articles published before August 31, 2021, with no language restrictions applied. We included studies using the EPE grading system for the prediction of EPE, with histopathological results as the reference standard. The pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR−), and diagnostic odds ratio (DOR) were calculated with the bivariate model. Quality assessment of included studies was performed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Results A total of 4 studies with 1,294 patients were included in the current systematic review. The pooled sensitivity and specificity were 0.82 (95% CI 0.76–0.87) and 0.63 (95% CI 0.51–0.73), with the area under the hierarchical summary receiver operating characteristic (HSROC) curve of 0.82 (95% CI 0.79–0.85). The pooled LR+, LR−, and DOR were 2.20 (95% CI 1.70–2.86), 0.28 (95% CI 0.22–0.36), and 7.77 (95% CI 5.27–11.44), respectively. Quality assessment for included studies was high, and Deeks’s funnel plot indicated that the possibility of publication bias was low (p = 0.64). Conclusion The EPE grading system demonstrated high sensitivity and moderate specificity, with a good inter-reader agreement. However, this scoring system needs more studies to be validated in clinical practice.
Collapse
Affiliation(s)
- Wei Li
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Wenwen Shang
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Feng Lu
- Department of Radiology, Wuxi No. 2 People's Hospital, Wuxi, China
| | - Yuan Sun
- Department of Burn and Plastic Surgery, 71st Group Army Hospital of People's Liberation Army of China, Xuzhou, China
| | - Jun Tian
- Department of Basic Medicine, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Yiman Wu
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Anding Dong
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| |
Collapse
|
23
|
Tsuruta C, Hirata K, Kudo K, Masumori N, Hatakenaka M. DWI-related texture analysis for prostate cancer: differences in correlation with histological aggressiveness and data repeatability between peripheral and transition zones. Eur Radiol Exp 2022; 6:1. [PMID: 35018507 PMCID: PMC8752657 DOI: 10.1186/s41747-021-00252-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 10/25/2021] [Indexed: 11/10/2022] Open
Abstract
Background We investigated the correlation between texture features extracted from apparent diffusion coefficient (ADC) maps or diffusion-weighted images (DWIs), and grade group (GG) in the prostate peripheral zone (PZ) and transition zone (TZ), and assessed reliability in repeated examinations. Methods Patients underwent 3-T pelvic magnetic resonance imaging (MRI) before radical prostatectomy with repeated DWI using b-values of 0, 100, 1,000, and 1,500 s/mm2. Region of interest (ROI) for cancer was assigned to the first and second DWI acquisition separately. Texture features of ROIs were extracted from comma-separated values (CSV) data of ADC maps generated from several sets of two b-value combinations and DWIs, and correlation with GG, discrimination ability between GG of 1–2 versus 3–5, and data repeatability were evaluated in PZ and TZ. Results Forty-four patients with 49 prostate cancers met the eligibility criteria. In PZ, ADC 10% and 25% based on ADC map of two b-value combinations of 100 and 1,500 s/mm2 and 10% based on ADC map with b-value of 0 and 1,500 s/mm2 showed significant correlation with GG, acceptable discrimination ability, and good repeatability. In TZ, higher-order texture feature of busyness extracted from ADC map of 100 and 1,500 s/mm2, and high gray-level run emphasis, short-run high gray-level emphasis, and high gray-level zone emphasis from DWI with b-value of 100 s/mm2 demonstrated significant correlation, excellent discrimination ability, but moderate repeatability. Conclusions Some DWI-related features showed significant correlation with GG, acceptable to excellent discrimination ability, and moderate to good data repeatability in prostate cancer, and differed between PZ and TZ. Supplementary Information The online version contains supplementary material available at 10.1186/s41747-021-00252-y.
Collapse
Affiliation(s)
- Chie Tsuruta
- Department of Diagnostic Radiology, School of Medicine, Sapporo Medical University, South 1, West 17, Chuo-ku, Sapporo, 060-8556, Japan
| | - Kenji Hirata
- Department of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, Sapporo, Japan
| | - Kohsuke Kudo
- Department of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, Sapporo, Japan.,Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, Sapporo, Japan
| | - Naoya Masumori
- Department of Urology, School of Medicine, Sapporo Medical University, Sapporo, Japan
| | - Masamitsu Hatakenaka
- Department of Diagnostic Radiology, School of Medicine, Sapporo Medical University, South 1, West 17, Chuo-ku, Sapporo, 060-8556, Japan.
| |
Collapse
|
24
|
Arita Y, Akita H, Fujiwara H, Hashimoto M, Shigeta K, Kwee TC, Yoshida S, Kosaka T, Okuda S, Oya M, Jinzaki M. Synthetic magnetic resonance imaging for primary prostate cancer evaluation: Diagnostic potential of a non-contrast-enhanced bi-parametric approach enhanced with relaxometry measurements. Eur J Radiol Open 2022; 9:100403. [PMID: 35242886 PMCID: PMC8857584 DOI: 10.1016/j.ejro.2022.100403] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 02/09/2022] [Indexed: 12/28/2022] Open
Abstract
Purpose Bi-parametric magnetic resonance imaging (bpMRI) with diffusion-weighted images has wide utility in diagnosing clinically significant prostate cancer (csPCa). However, bpMRI yields more false-negatives for PI-RADS category 3 lesions than multiparametric (mp)MRI with dynamic-contrast-enhanced (DCE)-MRI. We investigated the utility of synthetic MRI with relaxometry maps for bpMRI-based diagnosis of csPCa. Methods One hundred and five treatment-naïve patients who underwent mpMRI and synthetic MRI before prostate biopsy for suspected PCa between August 2019 and December 2020 were prospectively included. Three experts and three basic prostate radiologists evaluated the diagnostic performance of conventional bpMRI and synthetic bpMRI for csPCa. PI-RADS version 2.1 category 3 lesions were identified by consensus, and relaxometry measurements (T1-value, T2-value, and proton density [PD]) were performed. The diagnostic performance of relaxometry measurements for PI-RADS category 3 lesions in peripheral zone was compared with that of DCE-MRI. Histopathological evaluation results were used as the reference standard. Statistical analysis was performed using the areas under the receiver operating characteristic curve (AUC) and McNemar test. Results In 102 patients without significant MRI artefacts, the diagnostic performance of conventional bpMRI was not significantly different from that of synthetic bpMRI for all readers (p = 0.11–0.79). The AUCs of the combination of T1-value, T2-value, and PD (T1 + T2 + PD) for csPCa in peripheral zone for PI-RADS category 3 lesions were 0.85 for expert and 0.86 for basic radiologists, with no significant difference between T1 + T2 + PD and DCE-MRI for both expert and basic radiologists (p = 0.29–0.45). Conclusion Synthetic MRI with relaxometry maps shows promise for contrast media-free evaluation of csPCa. Diagnostic performances of synthetic bpMRI and conventional bpMRI are comparable for primary PCa Diagnostic performance of synthetic MRI variables are similar to that of DCE-MRI for csPCa in PZ Synthetic bpMRI shows potential as a contrast agent-free method for primary PCa
Collapse
|
25
|
Li W, Sun Y, Wu Y, Lu F, Xu H. The Quantitative Assessment of Using Multiparametric MRI for Prediction of Extraprostatic Extension in Patients Undergoing Radical Prostatectomy: A Systematic Review and Meta-Analysis. Front Oncol 2021; 11:771864. [PMID: 34881183 PMCID: PMC8645791 DOI: 10.3389/fonc.2021.771864] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 10/28/2021] [Indexed: 11/13/2022] Open
Abstract
Purpose To investigate the diagnostic performance of using quantitative assessment with multiparametric MRI (mpMRI) for prediction of extraprostatic extension (EPE) in patients with prostate cancer (PCa). Methods We performed a computerized search of MEDLINE, Embase, Cochrane Library, Web of Science, and Google Scholar from inception until July 31, 2021. Summary estimates of sensitivity and specificity were pooled with the bivariate model, and quality assessment of included studies was performed with the Quality Assessment of Diagnostic Accuracy Studies-2. We plotted forest plots to graphically present the results. Multiple subgroup analyses and meta-regression were performed to explore the variate clinical settings and heterogeneity. Results A total of 23 studies with 3,931 participants were included. The pooled sensitivity and specificity for length of capsular contact (LCC) were 0.79 (95% CI 0.75-0.83) and 0.77 (95% CI 0.73-0.80), for apparent diffusion coefficient (ADC) were 0.71 (95% CI 0.50-0.86) and 0.71 (95% CI 059-0.81), for tumor size were 0.62 (95% CI 0.57-0.67) and 0.75 (95% CI 0.67-0.82), and for tumor volume were 0.77 (95% CI 0.68-0.84) and 0.72 (95% CI 0.56-0.83), respectively. Substantial heterogeneity was presented among included studies, and meta-regression showed that publication year (≤2017 vs. >2017) was the significant factor in studies using LCC as the quantitative assessment (P=0.02). Conclusion Four quantitative assessments of LCC, ADC, tumor size, and tumor volume showed moderate to high diagnostic performance of predicting EPE. However, the optimal cutoff threshold varied widely among studies and needs further investigation to establish.
Collapse
Affiliation(s)
- Wei Li
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Yuan Sun
- Department of Burn and Plastic Surgery, 71st Group Army Hospital of People's Liberation Army of China, Xuzhou, China
| | - Yiman Wu
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Feng Lu
- Department of Radiology, Wuxi No. 2 People's Hospital, Wuxi, China
| | - Hongtao Xu
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
| |
Collapse
|
26
|
Liu Y, Dong Y, Liu J, Zhang X, Lin M, Xu B. Comparison between 18 F-DCFPyL PET and MRI for the detection of transition zone prostate cancer. Prostate 2021; 81:1329-1336. [PMID: 34516670 DOI: 10.1002/pros.24230] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 08/09/2021] [Accepted: 08/30/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND We aimed to compare the diagnostic performance of 18 F-DCFPyL positron emission tomography (PET) and multiparameter magnetic resonance imaging (mp-MRI) in detecting transition zone (TZ) prostate cancer (PCa). METHODS This retrospective study included 20 patients who underwent 18 F-DCFPyL PET/MRI and 32 patients who underwent 18 F-DCFPyL PET/CT and MRI from January 2019 to June 2020. All patients had TZ lesions and underwent prostate biopsies. One senior (reader 1) and one junior (reader 2) nuclear medicine physician evaluated each TZ lesion independently, according to the molecular imaging prostate-specific membrane antigen scoring system and the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1). The histologic diagnosis of prostate biopsy was used as the reference standard. The diagnostic performance of the two methods was compared in terms of inter-reader agreement and area under the receiver operating characteristic (AUC-ROC) curve. RESULTS Of the 52 patients, 43 had TZ PCa. For inter-reader agreement, the kappa value was 0.883 for 18 F-DCFPyL PET and 0.393 for mp-MRI. For PET, both readers had the same diagnostic sensitivity, specificity, and accuracy of 93.0%, 77.8%, and 90.4%, respectively. For mp-MRI, the diagnostic sensitivity, specificity, and accuracy was 67.4%, 33.3%, and 61.5% for reader 1, and 51.2%, 44.4%, and 51.9% for reader 2, respectively. PET outperformed mp-MRI for both readers with an AUC of 0.872 for PET versus 0.584 for mp-MRI, p = .0209 for reader 1, and an AUC of 0.860 for PET versus 0.505 for mp-MRI, p = .0213 for reader 2. Among the 43 patients with TZ PCa, 18 F-DCFPyL PET detected a distant bone metastasis missed by the CT in one case and two small lymph node metastases missed by the CT and MRI in another case. CONCLUSIONS These results suggest that 18 F-DCFPyL PET, which was almost independent of the experience of the readers, was more objective in the evaluation of TZ lesions, and had higher diagnostic value than mp-MRI.
Collapse
Affiliation(s)
- Yachao Liu
- Department of Nuclear Medicine, Chinese PLA General Hospital, Beijing, China
| | - Yanliang Dong
- Department of Nuclear Medicine, Chinese PLA General Hospital, Beijing, China
| | - Jiajin Liu
- Department of Nuclear Medicine, Chinese PLA General Hospital, Beijing, China
| | - Xiaojun Zhang
- Department of Nuclear Medicine, Chinese PLA General Hospital, Beijing, China
| | - Mu Lin
- MR Collaboration, Diagnostic Imaging, Siemens Healthineers Ltd., Shanghai, China
| | - Baixuan Xu
- Department of Nuclear Medicine, Chinese PLA General Hospital, Beijing, China
| |
Collapse
|
27
|
Lim CS, Abreu-Gomez J, Thornhill R, James N, Al Kindi A, Lim AS, Schieda N. Utility of machine learning of apparent diffusion coefficient (ADC) and T2-weighted (T2W) radiomic features in PI-RADS version 2.1 category 3 lesions to predict prostate cancer diagnosis. Abdom Radiol (NY) 2021; 46:5647-5658. [PMID: 34467426 DOI: 10.1007/s00261-021-03235-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 07/31/2021] [Accepted: 07/31/2021] [Indexed: 12/22/2022]
Abstract
PURPOSE To evaluate if machine learning (ML) of radiomic features extracted from apparent diffusion coefficient (ADC) and T2-weighted (T2W) MRI can predict prostate cancer (PCa) diagnosis in Prostate Imaging-Reporting and Data System (PI-RADS) version 2.1 category 3 lesions. METHODS This multi-institutional review board-approved retrospective case-control study evaluated 158 men with 160 PI-RADS category 3 lesions (79 peripheral zone, 81 transition zone) diagnosed at 3-Tesla MRI with histopathology diagnosis by MRI-TRUS-guided targeted biopsy. A blinded radiologist confirmed PI-RADS v2.1 score and segmented lesions on axial T2W and ADC images using 3D Slicer, extracting radiomic features with an open-source software (Pyradiomics). Diagnostic accuracy for (1) any PCa and (2) clinically significant (CS; International Society of Urogenital Pathology Grade Group ≥ 2) PCa was assessed using XGBoost with tenfold cross -validation. RESULTS From 160 PI-RADS 3 lesions, there were 50.0% (80/160) PCa, including 36.3% (29/80) CS-PCa (63.8% [51/80] ISUP 1, 23.8% [19/80] ISUP 2, 8.8% [7/80] ISUP 3, 3.8% [3/80] ISUP 4). The remaining 50.0% (80/160) lesions were benign. ML of all radiomic features from T2W and ADC achieved area under receiver operating characteristic curve (AUC) for diagnosis of (1) CS-PCa 0.547 (95% Confidence Intervals 0.510-0.584) for T2W and 0.684 (CI 0.652-0.715) for ADC and (2) any PCa 0.608 (CI 0.579-0.636) for T2W and 0.642 (CI 0.614-0.0.670) for ADC. CONCLUSION Our results indicate ML of radiomic features extracted from T2W and ADC achieved at best moderate accuracy for determining which PI-RADS category 3 lesions represent PCa.
Collapse
Affiliation(s)
- Christopher S Lim
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Avenue, Rm AB 279, Toronto, ON, M4N 3M5, Canada.
| | - Jorge Abreu-Gomez
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
- Department of Medical Imaging, Joint Department of Medical Imaging, University of Toronto, 585 University Avenue PMB-298, Toronto, ON, M5G2N2, Canada
| | - Rebecca Thornhill
- Department of Medical Imaging, The Ottawa Hospital, The University of Ottawa, 1053 Carling Ave, Civic Campus C1, Ottawa, ON, K1Y 4E9, Canada
| | - Nick James
- Software Solutions, The Ottawa Hospital, Ottawa, Canada
| | - Ahmed Al Kindi
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Avenue, Rm AB 279, Toronto, ON, M4N 3M5, Canada
| | - Andrew S Lim
- Department of Radiation Oncology, Seattle Cancer Care Alliance, University of Washington, 825 Eastlake Ave. E, Seattle Washington, 98109-1023, USA
| | - Nicola Schieda
- Department of Medical Imaging, The Ottawa Hospital, The University of Ottawa, 1053 Carling Ave, Civic Campus C1, Ottawa, ON, K1Y 4E9, Canada
| |
Collapse
|
28
|
Diffusion-weighted imaging in prostate cancer. MAGMA (NEW YORK, N.Y.) 2021; 35:533-547. [PMID: 34491467 DOI: 10.1007/s10334-021-00957-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 08/11/2021] [Accepted: 08/29/2021] [Indexed: 12/21/2022]
Abstract
Diffusion-weighted imaging (DWI), a key component in multiparametric MRI (mpMRI), is useful for tumor detection and localization in clinically significant prostate cancer (csPCa). The Prostate Imaging Reporting and Data System versions 2 and 2.1 (PI-RADS v2 and PI-RADS v2.1) emphasize the role of DWI in determining PIRADS Assessment Category in each of the transition and peripheral zones. In addition, several recent studies have demonstrated comparable performance of abbreviated biparametric MRI (bpMRI), which incorporates only T2-weighted imaging and DWI, compared with mpMRI with dynamic contrast-enhanced MRI. Therefore, further optimization of DWI is essential to achieve clinical application of bpMRI for efficient detection of csPC in patients with elevated PSA levels. Although DWI acquisition is routinely performed using single-shot echo-planar imaging, this method suffers from such as susceptibility artifact and anatomic distortion, which remain to be solved. In this review article, we will outline existing problems in standard DWI using the single-shot echo-planar imaging sequence; discuss solutions that employ newly developed imaging techniques, state-of-the-art technologies, and sequences in DWI; and evaluate the current status of quantitative DWI for assessment of tumor aggressiveness in PC.
Collapse
|
29
|
Medved M, Chatterjee A, Devaraj A, Harmath C, Lee G, Yousuf A, Antic T, Oto A, Karczmar GS. High spectral and spatial resolution MRI of prostate cancer: a pilot study. Magn Reson Med 2021; 86:1505-1513. [PMID: 33963782 PMCID: PMC8887834 DOI: 10.1002/mrm.28802] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 03/18/2021] [Accepted: 03/22/2021] [Indexed: 11/09/2022]
Abstract
PURPOSE High spectral and spatial resolution (HiSS) MRI is a spectroscopic imaging method focusing on water and fat resonances that has good diagnostic utility in breast imaging. The purpose of this work was to assess the feasibility and potential utility of HiSS MRI for the diagnosis of prostate cancer. METHODS HiSS MRI was acquired at 3 T from six patients who underwent prostatectomy, yielding a train of 127 phase-coherent gradient echo (GRE) images. In the temporal domain, changes in voxel intensity were analyzed and linear (R) and quadratic (R1, R2) quantifiers of signal logarithm decay were calculated. In the spectral domain, three signal scaling-independent parameters were calculated: water resonance peak width (PW), relative peak asymmetry (PRA), and relative peak distortion from ideal Lorentzian shape (PRD). Seven cancer and five normal tissue regions of interest were identified in correlation with pathology and compared. RESULTS HiSS-derived quantifiers, except R2, showed high reproducibility (coefficients of variation, 5%-14%). Spectral domain quantifiers performed better than temporal domain quantifiers, with receiver operator characteristic areas under the curve ranging from of 0.83 to 0.91. For temporal domain parameters, the range was 0.74 to 0.91. Low absolute values of the coefficients of correlation between monoexponential decay markers (R, PW) and resonance shape markers (PRA, PRD) were observed (range, 0.23-0.38). CONCLUSION The feasibility and potential diagnostic utility of HiSS MRI in the prostate at 3 T without an endorectal coil was confirmed. Weak correlation between well-performing markers indicates that complementary information could be leveraged to further improve diagnostic accuracy.
Collapse
Affiliation(s)
- Milica Medved
- Department of Radiology, University of Chicago, Chicago, Illinois, USA,Sanford J. Grossman Center of Excellence in Prostate Imaging and Image Guided Therapy, University of Chicago, Chicago, Illinois, USA
| | - Aritrick Chatterjee
- Department of Radiology, University of Chicago, Chicago, Illinois, USA,Sanford J. Grossman Center of Excellence in Prostate Imaging and Image Guided Therapy, University of Chicago, Chicago, Illinois, USA
| | - Ajit Devaraj
- Philips Research NA, Cambridge, Massachusetts, USA
| | - Carla Harmath
- Department of Radiology, University of Chicago, Chicago, Illinois, USA
| | - Grace Lee
- Department of Radiology, University of Chicago, Chicago, Illinois, USA
| | - Ambereen Yousuf
- Department of Radiology, University of Chicago, Chicago, Illinois, USA,Sanford J. Grossman Center of Excellence in Prostate Imaging and Image Guided Therapy, University of Chicago, Chicago, Illinois, USA
| | - Tatjana Antic
- Department of Pathology, University of Chicago, Chicago, Illinois, USA
| | - Aytekin Oto
- Department of Radiology, University of Chicago, Chicago, Illinois, USA,Sanford J. Grossman Center of Excellence in Prostate Imaging and Image Guided Therapy, University of Chicago, Chicago, Illinois, USA
| | - Gregory S. Karczmar
- Department of Radiology, University of Chicago, Chicago, Illinois, USA,Sanford J. Grossman Center of Excellence in Prostate Imaging and Image Guided Therapy, University of Chicago, Chicago, Illinois, USA
| |
Collapse
|
30
|
Kim MJ, Park SY. Biparametric Magnetic Resonance Imaging-Derived Nomogram to Detect Clinically Significant Prostate Cancer by Targeted Biopsy for Index Lesion. J Magn Reson Imaging 2021; 55:1226-1233. [PMID: 34296803 DOI: 10.1002/jmri.27841] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 07/02/2021] [Accepted: 07/02/2021] [Indexed: 11/07/2022] Open
Abstract
BACKGROUND Currently, it is necessary to investigate how to combine biparametric magnetic resonance imaging (bpMRI) with various clinical parameters for the detection of clinically significant prostate cancer (csPCa). PURPOSE To develop a multivariate prebiopsy nomogram using clinical and bpMRI parameters for estimating the probability of csPCa. STUDY TYPE Retrospective, single-center study. SUBJECTS Two hundred and twenty-six patients who underwent targeted biopsy (TBx) for the MRI-suspected index lesion because of clinical suspicions of PCa. FIELD STRENGTH/SEQUENCE A 3 T MRI including turbo spin-echo T2 -weighted and diffusion-weighted single-shot echo-planar imaging sequences. ASSESSMENT Prebiopsy clinical and bpMRI parameters were patient age, biopsy history (biopsy-naïve or repeated biopsy status), prostate-specific antigen density (PSAD), Prostate Imaging-Reporting and Data System version 2.1 (PI-RADSv2.1), and apparent diffusion coefficient ratio (ADCR). ADCR was defined as mean ADC of the index lesion divided by mean ADC of the contralateral prostatic region. A multivariate prebiopsy nomogram for csPCa (i.e. Gleason sum ≥7) was developed. Area under the curve (AUC) of each parameter and prebiopsy nomogram was assessed. Five-fold cross-validation was performed for robust estimation of performance of the prebiopsy nomogram. STATISTICAL TESTS Logistic regression, receiver-operating curve, and 5-fold cross-validation. P-value < 0.05 was considered statistically significant. RESULTS Proportion of csPCa was 31.9% (72/226). The AUCs of age, biopsy-naïve status, PSAD, PI-RADSv2.1, ADCR, and prebiopsy nomogram were 0.657 (95% confidence interval [CI], 0.580-0.733), 0.593 (95% CI, 0.525-0.660), 0.762 (95% CI, 0.697-0.826), 0.824 (95% CI, 0.770-0.878), 0.829 (95% CI, 0.769-0.888), and 0.906 (95% CI, 0.863-0.948), respectively: AUC of nomogram was significantly different than that of individual parameter. In the 5-fold cross-validation, the mean AUC of the prebiopsy nomogram for csPCa was 0.888 (95% CI, 0.786-0.983). DATA CONCLUSIONS This multivariate prebiopsy nomogram using clinical and bpMRI parameters may help estimate the probability of csPCa in patients undergoing TBx. ADCR seems to enhance the role of bpMRI in detecting csPCa. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY: Stage 2.
Collapse
Affiliation(s)
- Min Je Kim
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Sung Yoon Park
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| |
Collapse
|
31
|
Sathiadoss P, Schieda N, Haroon M, Osman H, Alrasheed S, Flood TA, Melkus G. Utility of Quantitative T2-Mapping Compared to Conventional and Advanced Diffusion Weighted Imaging Techniques for Multiparametric Prostate MRI in Men with Hip Prosthesis. J Magn Reson Imaging 2021; 55:265-274. [PMID: 34223675 DOI: 10.1002/jmri.27803] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 06/11/2021] [Accepted: 06/11/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Diffusion weighted imaging (DWI) is fundamental for prostate cancer (PCa) detection with MRI; however, limited by susceptibility artifact from hip prosthesis. PURPOSE To evaluate image quality and ability to detect PCa with quantitative T2-mapping and DWI in men with hip prosthesis undergoing prostate MRI. STUDY TYPE Prospective, cross-sectional study. POPULATION Thirty consecutive men with hip replacement (18 unilateral, 12 bilateral) undergoing prostate MRI from 2019 to 2021. FIELD STRENGTH/SEQUENCE 3-T; multiparametric MRI (T2W, DCE-MRI, echo-planar [EPI]-DWI), T2-mapping (Carr-Purcell-Meiboom-Gill), FOCUS-EPI-DWI, PROPELLER-DWI. ASSESSMENT Five blinded radiologists independently evaluated MRI image quality using a 5-point Likert scale. PI-RADS v2.1 scores were applied in four interpretation strategies: 1) T2W-FSE+DCE-MRI+EPI-DWI, 2) T2W-FSE+DCE-MRI+EPI-DWI+FOCUS-EPI-DWI, 3) T2W-FSE+DCE-MRI+EPI-DWI+PROPELLER-DWI, 4) T2W-FSE+DCE-MRI+EPI-DWI+T2-maps. Five-point confidence scores were recorded. STATISTICAL ANALYSIS ANOVA, Kruskal-Wallis with pair-wise comparisons by Wilcoxon sign-rank, and paired t-tests, P < 0.05 was considered significant. Cohen's Kappa (k) for PI-RADSv2.1 scoring and proportion of correctly classified lesions tabulated for pathology-confirmed cases with 95% confidence intervals (CIs). RESULTS For all radiologists, T2-map image quality was significantly higher than EPI-DWI, FOCUS-EPI-DWI, and PROPELLER-DWI and similar (P = 0.146-0.706) or significantly better (for two readers) than T2W-FSE and DCE-MRI. PI-RADS v2.1 agreement improved comparing strategy A (k = 0.46) to strategy B (k = 0.58) to strategy C (k = 0.58) and was highest with strategy D which included T2-maps (k = 1.00). Radiologists' confidence was significantly highest with strategy D. Strategies B and C had similar confidence (P = 0.051-0.063) both significantly outperforming strategy A. Twelve men with 17 lesions had pathology confirmed diagnoses (13 PCa, 4 benign). Strategy D had the highest proportion of correctly classified lesions (76.5-82.4%) with overlapping 95% confidence intervals. DATA CONCLUSION T2-mapping may be a valuable adjunct to prostate MRI in men with hip replacement resulting in improved image quality, higher reader confidence, interobserver agreement, and accuracy in PI-RADS scoring. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY STAGE: 2.
Collapse
Affiliation(s)
- Paul Sathiadoss
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Nicola Schieda
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Mohammad Haroon
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Heba Osman
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Sumaya Alrasheed
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Trevor A Flood
- Department of Anatomical Pathology, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Gerd Melkus
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| |
Collapse
|
32
|
MRI-derived radiomics model for baseline prediction of prostate cancer progression on active surveillance. Sci Rep 2021; 11:12917. [PMID: 34155265 PMCID: PMC8217549 DOI: 10.1038/s41598-021-92341-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 06/03/2021] [Indexed: 02/05/2023] Open
Abstract
Nearly half of patients with prostate cancer (PCa) harbour low- or intermediate-risk disease considered suitable for active surveillance (AS). However, up to 44% of patients discontinue AS within the first five years, highlighting the unmet clinical need for robust baseline risk-stratification tools that enable timely and accurate prediction of tumour progression. In this proof-of-concept study, we sought to investigate the added value of MRI-derived radiomic features to standard-of-care clinical parameters for improving baseline prediction of PCa progression in AS patients. Tumour T2-weighted imaging (T2WI) and apparent diffusion coefficient radiomic features were extracted, with rigorous calibration and pre-processing methods applied to select the most robust features for predictive modelling. Following leave-one-out cross-validation, the addition of T2WI-derived radiomic features to clinical variables alone improved the area under the ROC curve for predicting progression from 0.61 (95% confidence interval [CI] 0.481-0.743) to 0.75 (95% CI 0.64-0.86). These exploratory findings demonstrate the potential benefit of MRI-derived radiomics to add incremental benefit to clinical data only models in the baseline prediction of PCa progression on AS, paving the way for future multicentre studies validating the proposed model and evaluating its impact on clinical outcomes.
Collapse
|
33
|
Wang YF, Tadimalla S, Hayden AJ, Holloway L, Haworth A. Artificial intelligence and imaging biomarkers for prostate radiation therapy during and after treatment. J Med Imaging Radiat Oncol 2021; 65:612-626. [PMID: 34060219 DOI: 10.1111/1754-9485.13242] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 04/18/2021] [Accepted: 05/02/2021] [Indexed: 12/15/2022]
Abstract
Magnetic resonance imaging (MRI) is increasingly used in the management of prostate cancer (PCa). Quantitative MRI (qMRI) parameters, derived from multi-parametric MRI, provide indirect measures of tumour characteristics such as cellularity, angiogenesis and hypoxia. Using Artificial Intelligence (AI), relevant information and patterns can be efficiently identified in these complex data to develop quantitative imaging biomarkers (QIBs) of tumour function and biology. Such QIBs have already demonstrated potential in the diagnosis and staging of PCa. In this review, we explore the role of these QIBs in monitoring treatment response during and after PCa radiotherapy (RT). Recurrence of PCa after RT is not uncommon, and early detection prior to development of metastases provides an opportunity for salvage treatments with curative intent. However, the current method of monitoring treatment response using prostate-specific antigen levels lacks specificity. QIBs, derived from qMRI and developed using AI techniques, can be used to monitor biological changes post-RT providing the potential for accurate and early diagnosis of recurrent disease.
Collapse
Affiliation(s)
- Yu-Feng Wang
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
- Ingham Institute for Applied Medical Research, Liverpool, New South Wales, Australia
| | - Sirisha Tadimalla
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
| | - Amy J Hayden
- Sydney West Radiation Oncology, Westmead Hospital, Wentworthville, New South Wales, Australia
- Faculty of Medicine, Western Sydney University, Sydney, New South Wales, Australia
- Faculty of Medicine, Health & Human Sciences, Macquarie University, Sydney, New South Wales, Australia
| | - Lois Holloway
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
- Ingham Institute for Applied Medical Research, Liverpool, New South Wales, Australia
- Liverpool and Macarthur Cancer Therapy Centre, Liverpool Hospital, Liverpool, New South Wales, Australia
| | - Annette Haworth
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
| |
Collapse
|
34
|
Update on Multiparametric Prostate MRI During Active Surveillance: Current and Future Trends and Role of the PRECISE Recommendations. AJR Am J Roentgenol 2021; 216:943-951. [PMID: 32755219 DOI: 10.2214/ajr.20.23985] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Active surveillance for low-to-intermediate risk prostate cancer is a conservative management approach that aims to avoid or delay active treatment until there is evidence of disease progression. In recent years, multiparametric MRI (mpMRI) has been increasingly used in active surveillance and has shown great promise in patient selection and monitoring. This has been corroborated by publication of the Prostate Cancer Radiologic Estimation of Change in Sequential Evaluation (PRECISE) recommendations, which define the ideal reporting standards for mpMRI during active surveillance. The PRECISE recommendations include a system that assigns a score from 1 to 5 (the PRECISE score) for the assessment of radiologic change on serial mpMRI scans. PRECISE scores are defined as follows: a score of 3 indicates radiologic stability, a score of 1 or 2 denotes radiologic regression, and a score of 4 or 5 indicates radiologic progression. In the present study, we discuss current and future trends in the use of mpMRI during active surveillance and illustrate the natural history of prostate cancer on serial scans according to the PRECISE recommendations. We highlight how the ability to classify radiologic change on mpMRI with use of the PRECISE recommendations helps clinical decision making.
Collapse
|
35
|
Sushentsev N, Kaggie JD, Slough RA, Carmo B, Barrett T. Reproducibility of magnetic resonance fingerprinting-based T1 mapping of the healthy prostate at 1.5 and 3.0 T: A proof-of-concept study. PLoS One 2021; 16:e0245970. [PMID: 33513165 PMCID: PMC7846281 DOI: 10.1371/journal.pone.0245970] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 01/11/2021] [Indexed: 11/18/2022] Open
Abstract
Facilitating clinical translation of quantitative imaging techniques has been suggested as means of improving interobserver agreement and diagnostic accuracy of multiparametric magnetic resonance imaging (mpMRI) of the prostate. One such technique, magnetic resonance fingerprinting (MRF), has significant competitive advantages over conventional mapping techniques in terms of its multi-site reproducibility, short scanning time and inherent robustness to motion. It has also been shown to improve the detection of clinically significant prostate cancer when added to standard mpMRI sequences, however, the existing studies have all been conducted on 3.0 T MRI systems, limiting the technique's use on 1.5 T MRI scanners that are still more widely used for prostate imaging across the globe. The aim of this proof-of-concept study was, therefore, to evaluate the cross-system reproducibility of prostate MRF T1 in healthy volunteers (HVs) using 1.5 and 3.0 T MRI systems. The initial validation of MRF T1 against gold standard inversion recovery fast spin echo (IR-FSE) T1 in the ISMRM/NIST MRI system revealed a strong linear correlation between phantom-derived MRF and IR-FSE T1 values was observed at both field strengths (R2 = 0.998 at 1.5T and R2 = 0.993 at 3T; p = < 0.0001 for both). In young HVs, inter-scanner CVs demonstrated marginal differences across all tissues with the highest difference of 3% observed in fat (2% at 1.5T vs 5% at 3T). At both field strengths, MRF T1 could confidently differentiate prostate peripheral zone from transition zone, which highlights the high quantitative potential of the technique given the known difficulty of tissue differentiation in this age group. The high cross-system reproducibility of MRF T1 relaxometry of the healthy prostate observed in this preliminary study, therefore, supports the technique's prospective clinical validation as part of larger trials employing 1.5 T MRI systems, which are still widely used clinically for routine mpMRI of the prostate.
Collapse
Affiliation(s)
- Nikita Sushentsev
- Department of Radiology, Addenbrooke’s Hospital and University of Cambridge, Cambridge, United Kingdom
- * E-mail:
| | - Joshua D. Kaggie
- Department of Radiology, Addenbrooke’s Hospital and University of Cambridge, Cambridge, United Kingdom
| | - Rhys A. Slough
- Department of Radiology, Addenbrooke’s Hospital and University of Cambridge, Cambridge, United Kingdom
| | - Bruno Carmo
- Department of Radiology, Addenbrooke’s Hospital and University of Cambridge, Cambridge, United Kingdom
| | - Tristan Barrett
- Department of Radiology, Addenbrooke’s Hospital and University of Cambridge, Cambridge, United Kingdom
- CamPARI Prostate Cancer Group, Addenbrooke’s Hospital and University of Cambridge, Cambridge, United Kingdom
| |
Collapse
|
36
|
Abstract
The Prostate Imaging Reporting and Data System (PI-RADS) guidelines set out the minimal technical requirements for the acquisition of multiparametric MRI (mpMRI) of the prostate. However, the rapid diffusion of this technique has inevitably led to variability in scan quality among centres across the UK and the world. Suboptimal image acquisition reduces the sensitivity and specificity of this technique for the detection of clinically significant prostate cancer and results in clinicians losing confidence in the technique.Two expert panels, one from the UK and one from the European Society of Urogenital Radiology (ESUR)/EAU Section of Urologic Imaging (ESUI), have stressed the importance to establish quality criteria for the acquisition of mpMRI of the prostate. A first attempt to address this issue has been the publication of the Prostate Imaging Quality (PI-QUAL) score, which assesses the mpMRI quality against a set of objective criteria (PI-RADS guidelines) together with criteria obtained from the image.PI-QUAL represents the first step towards the standardisation of a scoring system to assess the quality of prostate mpMRI prior to reporting and allows clinicians to have more confidence in using the scan to determine patient care. Further refinements after robust consensus among experts at an international level need to be agreed before its widespread adoption in the clinical setting.
Collapse
Affiliation(s)
- Francesco Giganti
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK.,Division of Surgery & Interventional Science, University College London, London, UK
| | - Clare Allen
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK
| |
Collapse
|