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Palmer J, Winata L, Seale M, Sutherland T, Page M. Micro-enema immediately prior to prostate MRI: effects on rectal gas, image quality and PI-QUAL score. Abdom Radiol (NY) 2024:10.1007/s00261-024-04617-w. [PMID: 39373769 DOI: 10.1007/s00261-024-04617-w] [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: 06/26/2024] [Revised: 09/17/2024] [Accepted: 09/24/2024] [Indexed: 10/08/2024]
Abstract
PURPOSE Our aim was to determine whether the administration of a micro-enema immediately prior to prostate MRI is associated with a reduction in rectal gas, gas related artifacts and an improvement in image quality and PI-QUAL score. METHOD This retrospective analysis enrolled 171 patients who underwent multiparametric 3T prostate MRI at our institution between January 2021 and September 2022. 86 patients received a micro-enema, and a further 85 patients did not. Two fellowship trained abdominal radiologists were blinded and independently reviewed each prostate MRI, recording scores on a dedicated scoring sheet. The quality of T2 weighted (T2W), diffusion weighted (DWI), and dynamic contrast enhancement (DCE) images were assessed according to standardised scales supported in the literature. In addition, gas related artifacts and rectal gas level were examined. An independent-samples Mann-Whitney U and t-test were performed, comparing both the median and mean score between micro-enema and no micro-enema groups for each reader. Spearman's correlation was used to determine the strength of relationship between variables. A quadratic weighted Cohen's Kappa and percent agreement were used to assess inter-observer agreement. RESULTS Image quality was improved in those who received the micro-enema compared to those who did not according to the visual grading scale on the DWI sequence for both readers (reader 1: median 4 vs. 4, p < 0.001, mean 4.27 vs. 3.92, p < 0.001; reader 2: median 5 vs. 4, p < 0.001, mean 4.74 vs. 4.14, p < 0.001). PI-QUAL score was significantly improved in the micro-enema group for reader 2 only (reader 1: median 4 vs. 4, p = 0.25, mean 3.99 vs. 4.08, p = 0.21; reader 2: median 5 vs. 5, p = 0.01, mean 4.95 vs. 4.78, p = 0.01). Visual grading score for both the T2W and DCE images was not significantly different. Rectal gas level was lower in patients who received the micro-enema for both readers (reader 1: median 2 vs. 4, p < 0.001, mean 2.12 vs. 3.60, p < 0.001; reader 2: median 1 vs. 2, p < 0.001, mean 1.37 vs. 2.48, p < 0.001), correlating with a lower score for gas-related artifacts (reader 1: median 1 vs. 2, p < 0.001, mean 1.50 vs. 1.92, p < 0.001; reader 2: median 1 vs. 1, p < 0.001, mean 1.16 vs. 1.71, p < 0.001) in this group. Correlation between rectal gas level and gas-related artifacts on DWI regardless of whether a micro-enema was given was strong (rs = 0.71, p < 0.001). Correlation was moderate to strong between rectal gas level and image quality on DWI (rs = -0.63, p < 0.001). There was only 1 (1.2%) borderline diagnostic or non-diagnostic DWI sequence in those who received the micro-enema, compared to 9 (10.6%) in those who did not (p = 0.009). Interobserver agreement was moderate for image quality on DWI, gas related artifacts and rectal gas level (weighted kappa values of 0.52, 0.49 and 0.53 respectively). CONCLUSIONS The administration of a micro-enema immediately prior to prostate MRI is associated with a significant improvement in image quality on the DWI sequence compared to no bowel preparation. This is mediated through a reduction in rectal gas and gas related artifacts. Improvements in PI-QUAL score was mixed between readers.
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Affiliation(s)
- Jacob Palmer
- St Vincent's Hospital Melbourne, Melbourne, Australia.
| | - Leon Winata
- St Vincent's Hospital Melbourne, Melbourne, Australia
| | - Melanie Seale
- St Vincent's Hospital Melbourne, Melbourne, Australia
| | | | - Mark Page
- St Vincent's Hospital Melbourne, Melbourne, Australia
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Shang Y, Simegn GL, Gillen K, Yang HJ, Han H. Advancements in MR hardware systems and magnetic field control: B 0 shimming, RF coils, and gradient techniques for enhancing magnetic resonance imaging and spectroscopy. PSYCHORADIOLOGY 2024; 4:kkae013. [PMID: 39258223 PMCID: PMC11384915 DOI: 10.1093/psyrad/kkae013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Revised: 07/02/2024] [Accepted: 08/12/2024] [Indexed: 09/12/2024]
Abstract
High magnetic field homogeneity is critical for magnetic resonance imaging (MRI), functional MRI, and magnetic resonance spectroscopy (MRS) applications. B0 inhomogeneity during MR scans is a long-standing problem resulting from magnet imperfections and site conditions, with the main issue being the inhomogeneity across the human body caused by differences in magnetic susceptibilities between tissues, resulting in signal loss, image distortion, and poor spectral resolution. Through a combination of passive and active shim techniques, as well as technological advances employing multi-coil techniques, optimal coil design, motion tracking, and real-time modifications, improved field homogeneity and image quality have been achieved in MRI/MRS. The integration of RF and shim coils brings a high shim efficiency due to the proximity of participants. This technique will potentially be applied to high-density RF coils with a high-density shim array for improved B0 homogeneity. Simultaneous shimming and image encoding can be achieved using multi-coil array, which also enables the development of novel encoding methods using advanced magnetic field control. Field monitoring enables the capture and real-time compensation for dynamic field perturbance beyond the static background inhomogeneity. These advancements have the potential to better use the scanner performance to enhance diagnostic capabilities and broaden applications of MRI/MRS in a variety of clinical and research settings. The purpose of this paper is to provide an overview of the latest advances in B0 magnetic field shimming and magnetic field control techniques as well as MR hardware, and to emphasize their significance and potential impact on improving the data quality of MRI/MRS.
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Affiliation(s)
- Yun Shang
- Department of Radiology, Weill Medical College of Cornell University, New York, NY 10065, United States
| | - Gizeaddis Lamesgin Simegn
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, United States
| | - Kelly Gillen
- Department of Radiology, Weill Medical College of Cornell University, New York, NY 10065, United States
| | - Hsin-Jung Yang
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA 90048, United States
| | - Hui Han
- Department of Radiology, Weill Medical College of Cornell University, New York, NY 10065, United States
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Samuels J, Martin J, Richardson M, Skehan K. Effects of Dietary Supplements on Iron-Loading Susceptibility Artefacts in Pelvic MRI. Cureus 2024; 16:e65605. [PMID: 39205737 PMCID: PMC11350153 DOI: 10.7759/cureus.65605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/28/2024] [Indexed: 09/04/2024] Open
Abstract
We present a case of an 80-year-old male who attended an MRI scan for his prostate cancer radiotherapy planning. His safety screening did not identify any contraindications to our department's MRI safety policy; however, his MRI images displayed significant susceptibility artefacts in the sigmoid colon and rectum and were not clinically acceptable. Further history revealed he had begun regularly taking curcumin supplements at the time of his prostate cancer diagnosis. The patient was instructed to cease taking the curcumin supplements and a repeat MRI appointment was scheduled for one week later. After discontinuing curcumin, repeat imaging was artefact-free and suitable for radiotherapy planning. The chelating properties of curcumin could potentially lead to an accumulation of iron in the bowel, causing MRI susceptibility artefacts in pelvic scans and presenting a possible negative impact on the clinical utility of the images. It may be helpful to screen regular medications including health supplements with known chelation properties where MRI scan quality may be affected.
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Affiliation(s)
- Justin Samuels
- Radiation Oncology, Calvary Mater Hospital, Newcastle, AUS
| | - Jarad Martin
- Radiation Oncology, Calvary Mater Hospital, Newcastle, AUS
| | | | - Kate Skehan
- Radiation Oncology, Calvary Mater Hospital, Newcastle, AUS
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Stanzione A, Lee KL, Sanmugalingam N, Rajendran I, Sushentsev N, Caglič I, Barrett T. Expect the unexpected: investigating discordant prostate MRI and biopsy results. Eur Radiol 2024; 34:4810-4820. [PMID: 38503918 PMCID: PMC11213781 DOI: 10.1007/s00330-024-10702-x] [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: 12/15/2023] [Revised: 02/08/2024] [Accepted: 02/24/2024] [Indexed: 03/21/2024]
Abstract
OBJECTIVES To evaluate discrepant radio-pathological outcomes in biopsy-naïve patients undergoing prostate MRI and to provide insights into the underlying causes. MATERIALS AND METHODS A retrospective analysis was conducted on 2780 biopsy-naïve patients undergoing prostate MRI at a tertiary referral centre between October 2015 and June 2022. Exclusion criteria were biopsy not performed, indeterminate MRI findings (PI-RADS 3), and clinically insignificant PCa (Gleason score 3 + 3). Patients with discrepant findings between MRI and biopsy results were categorised into two groups: MRI-negative/Biopsy-positive and MRI-positive/Biopsy-negative (biopsy-positive defined as Gleason score ≥ 3 + 4). An expert uroradiologist reviewed discrepant cases, retrospectively re-assigning PI-RADS scores, identifying any missed MRI targets, and evaluating the quality of MRI scans. Potential explanations for discrepancies included MRI overcalls (including known pitfalls), benign pathology findings, and biopsy targeting errors. RESULTS Patients who did not undergo biopsy (n = 1258) or who had indeterminate MRI findings (n = 204), as well as those with clinically insignificant PCa (n = 216), were excluded, with a total of 1102 patients analysed. Of these, 32/1,102 (3%) were classified as MRI-negative/biopsy-positive and 117/1102 (11%) as MRI-positive/biopsy-negative. In the MRI-negative/Biopsy-positive group, 44% of studies were considered non-diagnostic quality. Upon retrospective image review, target lesions were identified in 28% of cases. In the MRI-positive/Biopsy-negative group, 42% of cases were considered to be MRI overcalls, and 32% had an explanatory benign pathological finding, with biopsy targeting errors accounting for 11% of cases. CONCLUSION Prostate MRI demonstrated a high diagnostic accuracy, with low occurrences of discrepant findings as defined. Common reasons for MRI-positive/Biopsy-negative cases included explanatory benign findings and MRI overcalls. CLINICAL RELEVANCE STATEMENT This study highlights the importance of optimal prostate MRI image quality and expertise in reducing diagnostic errors, improving patient outcomes, and guiding appropriate management decisions in the prostate cancer diagnostic pathway. KEY POINTS • Discrepancies between prostate MRI and biopsy results can occur, with higher numbers of MRI-positive/biopsy-negative relative to MRI-negative/biopsy-positive cases. • MRI-positive/biopsy-negative cases were mostly overcalls or explainable by benign biopsy findings. • In about one-third of MRI-negative/biopsy-positive cases, a target lesion was retrospectively identified.
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Affiliation(s)
- Arnaldo Stanzione
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131, Naples, Italy
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Hills Road, Box 218, Cambridge, CB2 0QQ, UK
| | - Kang-Lung Lee
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Hills Road, Box 218, Cambridge, CB2 0QQ, UK
- Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Nimalan Sanmugalingam
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Hills Road, Box 218, Cambridge, CB2 0QQ, UK
| | - Ishwariya Rajendran
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Hills Road, Box 218, Cambridge, CB2 0QQ, UK
| | - Nikita Sushentsev
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Hills Road, Box 218, Cambridge, CB2 0QQ, UK
| | - Iztok Caglič
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Hills Road, Box 218, Cambridge, CB2 0QQ, UK
| | - Tristan Barrett
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Hills Road, Box 218, Cambridge, CB2 0QQ, UK.
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Belue MJ, Law YM, Marko J, Turkbey E, Malayeri A, Yilmaz EC, Lin Y, Johnson L, Merriman KM, Lay NS, Wood BJ, Pinto PA, Choyke PL, Harmon SA, Turkbey B. Deep Learning-Based Interpretable AI for Prostate T2W MRI Quality Evaluation. Acad Radiol 2024; 31:1429-1437. [PMID: 37858505 PMCID: PMC11015987 DOI: 10.1016/j.acra.2023.09.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 09/11/2023] [Accepted: 09/21/2023] [Indexed: 10/21/2023]
Abstract
RATIONALE AND OBJECTIVES Prostate MRI quality is essential in guiding prostate biopsies. However, assessment of MRI quality is subjective with variation. Quality degradation sources exert varying impacts based on the sequence under consideration, such as T2W versus DWI. As a result, employing sequence-specific techniques for quality assessment could yield more advantageous outcomes. This study aims to develop an AI tool that offers a more consistent evaluation of T2W prostate MRI quality, efficiently identifying suboptimal scans while minimizing user bias. MATERIALS AND METHODS This retrospective study included 1046 patients from three cohorts (ProstateX [n = 347], All-comer in-house [n = 602], enriched bad-quality MRI in-house [n = 97]) scanned between January 2011 and May 2022. An expert reader assigned T2W MRIs a quality score. A train-validation-test split of 70:15:15 was applied, ensuring equal distribution of MRI scanners and protocols across all partitions. T2W quality AI classification model was based on 3D DenseNet121 architecture using MONAI framework. In addition to multiclassification, binary classification was utilized (Classes 0/1 vs. 2). A score of 0 was given to scans considered non-diagnostic or unusable, a score of 1 was given to those with acceptable diagnostic quality with some usability but with some quality distortions present, and a score of 2 was given to those considered optimal diagnostic quality and usability. Partial occlusion sensitivity maps were generated for anatomical correlation. Three body radiologists assessed reproducibility within a subgroup of 60 test cases using weighted Cohen Kappa. RESULTS The best validation multiclass accuracy of 77.1% (121/157) was achieved during training. In the test dataset, multiclassification accuracy was 73.9% (116/157), whereas binary accuracy was 84.7% (133/157). Sub-class sensitivity for binary quality distortion classification for class 0 was 100% (18/18), and sub-class specificity for T2W classification of absence/minimal quality distortions for class 2 was 90.5% (95/105). All three readers showed moderate to substantial agreement with ground truth (R1-R3 κ = 0.588, κ = 0.649, κ = 0.487, respectively), moderate to substantial agreement with each other (R1-R2 κ = 0.599, R1-R3 κ = 0.612, R2-R3 κ = 0.685), fair to moderate agreement with AI (R1-R3 κ = 0.445, κ = 0.410, κ = 0.292, respectively). AI showed substantial agreement with ground truth (κ = 0.704). 3D quality heatmap evaluation revealed that the most critical non-diagnostic quality imaging features from an AI perspective related to obscuration of the rectoprostatic space (94.4%, 17/18). CONCLUSION The 3D AI model can assess T2W prostate MRI quality with moderate accuracy and translate whole sequence-level classification labels into 3D voxel-level quality heatmaps for interpretation. Image quality has a significant downstream impact on ruling out clinically significant cancers. AI may be able to help with reproducible identification of MRI sequences requiring re-acquisition with explainability.
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Affiliation(s)
- Mason J Belue
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA (M.J.B., E.C.Y., Y.L., L.J., K.M.M, N.S.L., P.L.C., S.A.H., B.T.)
| | - Yan Mee Law
- Department of Radiology, Singapore General Hospital, Singapore (Y.M.L.)
| | - Jamie Marko
- Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA (J.M.)
| | - Evrim Turkbey
- Department of Radiology, Clinical Center, National Institutes of Health, Bethesda, Maryland, USA (E.T., A.M., B.J.W.)
| | - Ashkan Malayeri
- Department of Radiology, Clinical Center, National Institutes of Health, Bethesda, Maryland, USA (E.T., A.M., B.J.W.)
| | - Enis C Yilmaz
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA (M.J.B., E.C.Y., Y.L., L.J., K.M.M, N.S.L., P.L.C., S.A.H., B.T.)
| | - Yue Lin
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA (M.J.B., E.C.Y., Y.L., L.J., K.M.M, N.S.L., P.L.C., S.A.H., B.T.)
| | - Latrice Johnson
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA (M.J.B., E.C.Y., Y.L., L.J., K.M.M, N.S.L., P.L.C., S.A.H., B.T.)
| | - Katie M Merriman
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA (M.J.B., E.C.Y., Y.L., L.J., K.M.M, N.S.L., P.L.C., S.A.H., B.T.)
| | - Nathan S Lay
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA (M.J.B., E.C.Y., Y.L., L.J., K.M.M, N.S.L., P.L.C., S.A.H., B.T.)
| | - Bradford J Wood
- Department of Radiology, Clinical Center, National Institutes of Health, Bethesda, Maryland, USA (E.T., A.M., B.J.W.); Center for Interventional Oncology, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA (B.J.W.)
| | - Peter A Pinto
- Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA (P.A.P.)
| | - Peter L Choyke
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA (M.J.B., E.C.Y., Y.L., L.J., K.M.M, N.S.L., P.L.C., S.A.H., B.T.)
| | - Stephanie A Harmon
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA (M.J.B., E.C.Y., Y.L., L.J., K.M.M, N.S.L., P.L.C., S.A.H., B.T.)
| | - Baris Turkbey
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA (M.J.B., E.C.Y., Y.L., L.J., K.M.M, N.S.L., P.L.C., S.A.H., B.T.).
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Hu L, Guo X, Zhou D, Wang Z, Dai L, Li L, Li Y, Zhang T, Long H, Yu C, Shi ZW, Han C, Lu C, Zhao J, Li Y, Zha Y, Liu Z. Development and Validation of a Deep Learning Model to Reduce the Interference of Rectal Artifacts in MRI-based Prostate Cancer Diagnosis. Radiol Artif Intell 2024; 6:e230362. [PMID: 38446042 PMCID: PMC10985636 DOI: 10.1148/ryai.230362] [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: 08/31/2023] [Revised: 01/31/2024] [Accepted: 02/21/2024] [Indexed: 03/07/2024]
Abstract
Purpose To develop an MRI-based model for clinically significant prostate cancer (csPCa) diagnosis that can resist rectal artifact interference. Materials and Methods This retrospective study included 2203 male patients with prostate lesions who underwent biparametric MRI and biopsy between January 2019 and June 2023. Targeted adversarial training with proprietary adversarial samples (TPAS) strategy was proposed to enhance model resistance against rectal artifacts. The automated csPCa diagnostic models trained with and without TPAS were compared using multicenter validation datasets. The impact of rectal artifacts on the diagnostic performance of each model at the patient and lesion levels was compared using the area under the receiver operating characteristic curve (AUC) and the area under the precision-recall curve (AUPRC). The AUC between models was compared using the DeLong test, and the AUPRC was compared using the bootstrap method. Results The TPAS model exhibited diagnostic performance improvements of 6% at the patient level (AUC: 0.87 vs 0.81, P < .001) and 7% at the lesion level (AUPRC: 0.84 vs 0.77, P = .007) compared with the control model. The TPAS model demonstrated less performance decline in the presence of rectal artifact-pattern adversarial noise than the control model (ΔAUC: -17% vs -19%, ΔAUPRC: -18% vs -21%). The TPAS model performed better than the control model in patients with moderate (AUC: 0.79 vs 0.73, AUPRC: 0.68 vs 0.61) and severe (AUC: 0.75 vs 0.57, AUPRC: 0.69 vs 0.59) artifacts. Conclusion This study demonstrates that the TPAS model can reduce rectal artifact interference in MRI-based csPCa diagnosis, thereby improving its performance in clinical applications. Keywords: MR-Diffusion-weighted Imaging, Urinary, Prostate, Comparative Studies, Diagnosis, Transfer Learning Clinical trial registration no. ChiCTR23000069832 Supplemental material is available for this article. Published under a CC BY 4.0 license.
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Affiliation(s)
| | | | - Dawei Zhou
- From the Guangdong Cardiovascular Institute, Guangdong Provincial
People’s Hospital, Guangdong Academy of Sciences, Guangzhou, China
(L.H.); Department of Radiology, Guangdong Provincial People’s Hospital
(Guangdong Academy of Medical Sciences), Southern Medical University, No. 106
Zhongshan Er Road, Guangzhou 510080, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image
Analysis and Application, Guangzhou, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Department of TPS Algorithm, Xi’an OUR United Corporation, Xi’an,
China (X.G.); State Key Laboratory of Integrated Services Networks, School of
Telecommunications Engineering, Xidian University, Xi’an, China (D.Z.);
Department of Radiology, Yichang Central People’s Hospital Affiliated to
the First Clinical Medical College of Three Gorges University, Yichang, China
(Z.W., C.Y.); Institute of Diagnostic and Interventional Radiology, Shanghai
Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University
School of Medicine, Shanghai, China (L.D., H.L., J.Z., Yuehua Li); and
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
(L.L., Ying Li, T.Z., Y.Z.)
| | - Zhen Wang
- From the Guangdong Cardiovascular Institute, Guangdong Provincial
People’s Hospital, Guangdong Academy of Sciences, Guangzhou, China
(L.H.); Department of Radiology, Guangdong Provincial People’s Hospital
(Guangdong Academy of Medical Sciences), Southern Medical University, No. 106
Zhongshan Er Road, Guangzhou 510080, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image
Analysis and Application, Guangzhou, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Department of TPS Algorithm, Xi’an OUR United Corporation, Xi’an,
China (X.G.); State Key Laboratory of Integrated Services Networks, School of
Telecommunications Engineering, Xidian University, Xi’an, China (D.Z.);
Department of Radiology, Yichang Central People’s Hospital Affiliated to
the First Clinical Medical College of Three Gorges University, Yichang, China
(Z.W., C.Y.); Institute of Diagnostic and Interventional Radiology, Shanghai
Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University
School of Medicine, Shanghai, China (L.D., H.L., J.Z., Yuehua Li); and
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
(L.L., Ying Li, T.Z., Y.Z.)
| | - Lisong Dai
- From the Guangdong Cardiovascular Institute, Guangdong Provincial
People’s Hospital, Guangdong Academy of Sciences, Guangzhou, China
(L.H.); Department of Radiology, Guangdong Provincial People’s Hospital
(Guangdong Academy of Medical Sciences), Southern Medical University, No. 106
Zhongshan Er Road, Guangzhou 510080, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image
Analysis and Application, Guangzhou, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Department of TPS Algorithm, Xi’an OUR United Corporation, Xi’an,
China (X.G.); State Key Laboratory of Integrated Services Networks, School of
Telecommunications Engineering, Xidian University, Xi’an, China (D.Z.);
Department of Radiology, Yichang Central People’s Hospital Affiliated to
the First Clinical Medical College of Three Gorges University, Yichang, China
(Z.W., C.Y.); Institute of Diagnostic and Interventional Radiology, Shanghai
Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University
School of Medicine, Shanghai, China (L.D., H.L., J.Z., Yuehua Li); and
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
(L.L., Ying Li, T.Z., Y.Z.)
| | - Liang Li
- From the Guangdong Cardiovascular Institute, Guangdong Provincial
People’s Hospital, Guangdong Academy of Sciences, Guangzhou, China
(L.H.); Department of Radiology, Guangdong Provincial People’s Hospital
(Guangdong Academy of Medical Sciences), Southern Medical University, No. 106
Zhongshan Er Road, Guangzhou 510080, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image
Analysis and Application, Guangzhou, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Department of TPS Algorithm, Xi’an OUR United Corporation, Xi’an,
China (X.G.); State Key Laboratory of Integrated Services Networks, School of
Telecommunications Engineering, Xidian University, Xi’an, China (D.Z.);
Department of Radiology, Yichang Central People’s Hospital Affiliated to
the First Clinical Medical College of Three Gorges University, Yichang, China
(Z.W., C.Y.); Institute of Diagnostic and Interventional Radiology, Shanghai
Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University
School of Medicine, Shanghai, China (L.D., H.L., J.Z., Yuehua Li); and
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
(L.L., Ying Li, T.Z., Y.Z.)
| | - Ying Li
- From the Guangdong Cardiovascular Institute, Guangdong Provincial
People’s Hospital, Guangdong Academy of Sciences, Guangzhou, China
(L.H.); Department of Radiology, Guangdong Provincial People’s Hospital
(Guangdong Academy of Medical Sciences), Southern Medical University, No. 106
Zhongshan Er Road, Guangzhou 510080, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image
Analysis and Application, Guangzhou, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Department of TPS Algorithm, Xi’an OUR United Corporation, Xi’an,
China (X.G.); State Key Laboratory of Integrated Services Networks, School of
Telecommunications Engineering, Xidian University, Xi’an, China (D.Z.);
Department of Radiology, Yichang Central People’s Hospital Affiliated to
the First Clinical Medical College of Three Gorges University, Yichang, China
(Z.W., C.Y.); Institute of Diagnostic and Interventional Radiology, Shanghai
Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University
School of Medicine, Shanghai, China (L.D., H.L., J.Z., Yuehua Li); and
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
(L.L., Ying Li, T.Z., Y.Z.)
| | - Tian Zhang
- From the Guangdong Cardiovascular Institute, Guangdong Provincial
People’s Hospital, Guangdong Academy of Sciences, Guangzhou, China
(L.H.); Department of Radiology, Guangdong Provincial People’s Hospital
(Guangdong Academy of Medical Sciences), Southern Medical University, No. 106
Zhongshan Er Road, Guangzhou 510080, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image
Analysis and Application, Guangzhou, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Department of TPS Algorithm, Xi’an OUR United Corporation, Xi’an,
China (X.G.); State Key Laboratory of Integrated Services Networks, School of
Telecommunications Engineering, Xidian University, Xi’an, China (D.Z.);
Department of Radiology, Yichang Central People’s Hospital Affiliated to
the First Clinical Medical College of Three Gorges University, Yichang, China
(Z.W., C.Y.); Institute of Diagnostic and Interventional Radiology, Shanghai
Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University
School of Medicine, Shanghai, China (L.D., H.L., J.Z., Yuehua Li); and
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
(L.L., Ying Li, T.Z., Y.Z.)
| | - Haining Long
- From the Guangdong Cardiovascular Institute, Guangdong Provincial
People’s Hospital, Guangdong Academy of Sciences, Guangzhou, China
(L.H.); Department of Radiology, Guangdong Provincial People’s Hospital
(Guangdong Academy of Medical Sciences), Southern Medical University, No. 106
Zhongshan Er Road, Guangzhou 510080, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image
Analysis and Application, Guangzhou, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Department of TPS Algorithm, Xi’an OUR United Corporation, Xi’an,
China (X.G.); State Key Laboratory of Integrated Services Networks, School of
Telecommunications Engineering, Xidian University, Xi’an, China (D.Z.);
Department of Radiology, Yichang Central People’s Hospital Affiliated to
the First Clinical Medical College of Three Gorges University, Yichang, China
(Z.W., C.Y.); Institute of Diagnostic and Interventional Radiology, Shanghai
Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University
School of Medicine, Shanghai, China (L.D., H.L., J.Z., Yuehua Li); and
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
(L.L., Ying Li, T.Z., Y.Z.)
| | - Chengxin Yu
- From the Guangdong Cardiovascular Institute, Guangdong Provincial
People’s Hospital, Guangdong Academy of Sciences, Guangzhou, China
(L.H.); Department of Radiology, Guangdong Provincial People’s Hospital
(Guangdong Academy of Medical Sciences), Southern Medical University, No. 106
Zhongshan Er Road, Guangzhou 510080, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image
Analysis and Application, Guangzhou, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Department of TPS Algorithm, Xi’an OUR United Corporation, Xi’an,
China (X.G.); State Key Laboratory of Integrated Services Networks, School of
Telecommunications Engineering, Xidian University, Xi’an, China (D.Z.);
Department of Radiology, Yichang Central People’s Hospital Affiliated to
the First Clinical Medical College of Three Gorges University, Yichang, China
(Z.W., C.Y.); Institute of Diagnostic and Interventional Radiology, Shanghai
Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University
School of Medicine, Shanghai, China (L.D., H.L., J.Z., Yuehua Li); and
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
(L.L., Ying Li, T.Z., Y.Z.)
| | - Zhen-wei Shi
- From the Guangdong Cardiovascular Institute, Guangdong Provincial
People’s Hospital, Guangdong Academy of Sciences, Guangzhou, China
(L.H.); Department of Radiology, Guangdong Provincial People’s Hospital
(Guangdong Academy of Medical Sciences), Southern Medical University, No. 106
Zhongshan Er Road, Guangzhou 510080, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image
Analysis and Application, Guangzhou, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Department of TPS Algorithm, Xi’an OUR United Corporation, Xi’an,
China (X.G.); State Key Laboratory of Integrated Services Networks, School of
Telecommunications Engineering, Xidian University, Xi’an, China (D.Z.);
Department of Radiology, Yichang Central People’s Hospital Affiliated to
the First Clinical Medical College of Three Gorges University, Yichang, China
(Z.W., C.Y.); Institute of Diagnostic and Interventional Radiology, Shanghai
Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University
School of Medicine, Shanghai, China (L.D., H.L., J.Z., Yuehua Li); and
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
(L.L., Ying Li, T.Z., Y.Z.)
| | - Chu Han
- From the Guangdong Cardiovascular Institute, Guangdong Provincial
People’s Hospital, Guangdong Academy of Sciences, Guangzhou, China
(L.H.); Department of Radiology, Guangdong Provincial People’s Hospital
(Guangdong Academy of Medical Sciences), Southern Medical University, No. 106
Zhongshan Er Road, Guangzhou 510080, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image
Analysis and Application, Guangzhou, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Department of TPS Algorithm, Xi’an OUR United Corporation, Xi’an,
China (X.G.); State Key Laboratory of Integrated Services Networks, School of
Telecommunications Engineering, Xidian University, Xi’an, China (D.Z.);
Department of Radiology, Yichang Central People’s Hospital Affiliated to
the First Clinical Medical College of Three Gorges University, Yichang, China
(Z.W., C.Y.); Institute of Diagnostic and Interventional Radiology, Shanghai
Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University
School of Medicine, Shanghai, China (L.D., H.L., J.Z., Yuehua Li); and
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
(L.L., Ying Li, T.Z., Y.Z.)
| | - Cheng Lu
- From the Guangdong Cardiovascular Institute, Guangdong Provincial
People’s Hospital, Guangdong Academy of Sciences, Guangzhou, China
(L.H.); Department of Radiology, Guangdong Provincial People’s Hospital
(Guangdong Academy of Medical Sciences), Southern Medical University, No. 106
Zhongshan Er Road, Guangzhou 510080, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image
Analysis and Application, Guangzhou, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Department of TPS Algorithm, Xi’an OUR United Corporation, Xi’an,
China (X.G.); State Key Laboratory of Integrated Services Networks, School of
Telecommunications Engineering, Xidian University, Xi’an, China (D.Z.);
Department of Radiology, Yichang Central People’s Hospital Affiliated to
the First Clinical Medical College of Three Gorges University, Yichang, China
(Z.W., C.Y.); Institute of Diagnostic and Interventional Radiology, Shanghai
Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University
School of Medicine, Shanghai, China (L.D., H.L., J.Z., Yuehua Li); and
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
(L.L., Ying Li, T.Z., Y.Z.)
| | - Jungong Zhao
- From the Guangdong Cardiovascular Institute, Guangdong Provincial
People’s Hospital, Guangdong Academy of Sciences, Guangzhou, China
(L.H.); Department of Radiology, Guangdong Provincial People’s Hospital
(Guangdong Academy of Medical Sciences), Southern Medical University, No. 106
Zhongshan Er Road, Guangzhou 510080, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image
Analysis and Application, Guangzhou, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Department of TPS Algorithm, Xi’an OUR United Corporation, Xi’an,
China (X.G.); State Key Laboratory of Integrated Services Networks, School of
Telecommunications Engineering, Xidian University, Xi’an, China (D.Z.);
Department of Radiology, Yichang Central People’s Hospital Affiliated to
the First Clinical Medical College of Three Gorges University, Yichang, China
(Z.W., C.Y.); Institute of Diagnostic and Interventional Radiology, Shanghai
Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University
School of Medicine, Shanghai, China (L.D., H.L., J.Z., Yuehua Li); and
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
(L.L., Ying Li, T.Z., Y.Z.)
| | - Yuehua Li
- From the Guangdong Cardiovascular Institute, Guangdong Provincial
People’s Hospital, Guangdong Academy of Sciences, Guangzhou, China
(L.H.); Department of Radiology, Guangdong Provincial People’s Hospital
(Guangdong Academy of Medical Sciences), Southern Medical University, No. 106
Zhongshan Er Road, Guangzhou 510080, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image
Analysis and Application, Guangzhou, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Department of TPS Algorithm, Xi’an OUR United Corporation, Xi’an,
China (X.G.); State Key Laboratory of Integrated Services Networks, School of
Telecommunications Engineering, Xidian University, Xi’an, China (D.Z.);
Department of Radiology, Yichang Central People’s Hospital Affiliated to
the First Clinical Medical College of Three Gorges University, Yichang, China
(Z.W., C.Y.); Institute of Diagnostic and Interventional Radiology, Shanghai
Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University
School of Medicine, Shanghai, China (L.D., H.L., J.Z., Yuehua Li); and
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
(L.L., Ying Li, T.Z., Y.Z.)
| | - Yunfei Zha
- From the Guangdong Cardiovascular Institute, Guangdong Provincial
People’s Hospital, Guangdong Academy of Sciences, Guangzhou, China
(L.H.); Department of Radiology, Guangdong Provincial People’s Hospital
(Guangdong Academy of Medical Sciences), Southern Medical University, No. 106
Zhongshan Er Road, Guangzhou 510080, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image
Analysis and Application, Guangzhou, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Department of TPS Algorithm, Xi’an OUR United Corporation, Xi’an,
China (X.G.); State Key Laboratory of Integrated Services Networks, School of
Telecommunications Engineering, Xidian University, Xi’an, China (D.Z.);
Department of Radiology, Yichang Central People’s Hospital Affiliated to
the First Clinical Medical College of Three Gorges University, Yichang, China
(Z.W., C.Y.); Institute of Diagnostic and Interventional Radiology, Shanghai
Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University
School of Medicine, Shanghai, China (L.D., H.L., J.Z., Yuehua Li); and
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
(L.L., Ying Li, T.Z., Y.Z.)
| | - Zaiyi Liu
- From the Guangdong Cardiovascular Institute, Guangdong Provincial
People’s Hospital, Guangdong Academy of Sciences, Guangzhou, China
(L.H.); Department of Radiology, Guangdong Provincial People’s Hospital
(Guangdong Academy of Medical Sciences), Southern Medical University, No. 106
Zhongshan Er Road, Guangzhou 510080, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image
Analysis and Application, Guangzhou, China (L.H., Z.W.S., C.H., C.L., Z.L.);
Department of TPS Algorithm, Xi’an OUR United Corporation, Xi’an,
China (X.G.); State Key Laboratory of Integrated Services Networks, School of
Telecommunications Engineering, Xidian University, Xi’an, China (D.Z.);
Department of Radiology, Yichang Central People’s Hospital Affiliated to
the First Clinical Medical College of Three Gorges University, Yichang, China
(Z.W., C.Y.); Institute of Diagnostic and Interventional Radiology, Shanghai
Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University
School of Medicine, Shanghai, China (L.D., H.L., J.Z., Yuehua Li); and
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
(L.L., Ying Li, T.Z., Y.Z.)
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7
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Al-Hayali A, Komeili A, Azad A, Sathiadoss P, Schieda N, Ukwatta E. Machine learning based prediction of image quality in prostate MRI using rapid localizer images. J Med Imaging (Bellingham) 2024; 11:026001. [PMID: 38435711 PMCID: PMC10905647 DOI: 10.1117/1.jmi.11.2.026001] [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: 01/13/2023] [Revised: 10/17/2023] [Accepted: 01/29/2024] [Indexed: 03/05/2024] Open
Abstract
Purpose Diagnostic performance of prostate MRI depends on high-quality imaging. Prostate MRI quality is inversely proportional to the amount of rectal gas and distention. Early detection of poor-quality MRI may enable intervention to remove gas or exam rescheduling, saving time. We developed a machine learning based quality prediction of yet-to-be acquired MRI images solely based on MRI rapid localizer sequence, which can be acquired in a few seconds. Approach The dataset consists of 213 (147 for training and 64 for testing) prostate sagittal T2-weighted (T2W) MRI localizer images and rectal content, manually labeled by an expert radiologist. Each MRI localizer contains seven two-dimensional (2D) slices of the patient, accompanied by manual segmentations of rectum for each slice. Cascaded and end-to-end deep learning models were used to predict the quality of yet-to-be T2W, DWI, and apparent diffusion coefficient (ADC) MRI images. Predictions were compared to quality scores determined by the experts using area under the receiver operator characteristic curve and intra-class correlation coefficient. Results In the test set of 64 patients, optimal versus suboptimal exams occurred in 95.3% (61/64) versus 4.7% (3/64) for T2W, 90.6% (58/64) versus 9.4% (6/64) for DWI, and 89.1% (57/64) versus 10.9% (7/64) for ADC. The best performing segmentation model was 2D U-Net with ResNet-34 encoder and ImageNet weights. The best performing classifier was the radiomics based classifier. Conclusions A radiomics based classifier applied to localizer images achieves accurate diagnosis of subsequent image quality for T2W, DWI, and ADC prostate MRI sequences.
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Affiliation(s)
- Abdullah Al-Hayali
- University of Guelph, School of Engineering, Guelph Imaging AI Lab, Guelph, Ontario, Canada
| | - Amin Komeili
- University of Calgary, Department of Biomedical Engineering, Calgary, Alberta, Canada
| | - Azar Azad
- A.I. Vali Inc., Toronto, Ontario, Canada
| | - Paul Sathiadoss
- University of Ottawa, Department of Radiology, Ottawa, Ontario, Canada
| | - Nicola Schieda
- University of Ottawa, Department of Radiology, Ottawa, Ontario, Canada
| | - Eranga Ukwatta
- University of Guelph, School of Engineering, Guelph Imaging AI Lab, Guelph, Ontario, Canada
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8
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Barrett T, Lee KL, de Rooij M, Giganti F. Update on Optimization of Prostate MR Imaging Technique and Image Quality. Radiol Clin North Am 2024; 62:1-15. [PMID: 37973236 DOI: 10.1016/j.rcl.2023.06.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2023]
Abstract
Prostate MR imaging quality has improved dramatically over recent times, driven by advances in hardware, software, and improved functional imaging techniques. MRI now plays a key role in prostate cancer diagnostic work-up, but outcomes of the MRI-directed pathway are heavily dependent on image quality and optimization. MR sequences can be affected by patient-related degradations relating to motion and susceptibility artifacts which may enable only partial mitigation. In this Review, we explore issues relating to prostate MRI acquisition and interpretation, mitigation strategies at a patient and scanner level, PI-QUAL reporting, and future directions in image quality, including artificial intelligence solutions.
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Affiliation(s)
- Tristan Barrett
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.
| | - Kang-Lung Lee
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK; Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Maarten de Rooij
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands
| | - Francesco Giganti
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK; Division of Surgery and Interventional Science, University College London, London, UK
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9
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Sanmugalingam N, Sushentsev N, Lee KL, Caglic I, Englman C, Moore CM, Giganti F, Barrett T. The PRECISE Recommendations for Prostate MRI in Patients on Active Surveillance for Prostate Cancer: A Critical Review. AJR Am J Roentgenol 2023; 221:649-660. [PMID: 37341180 DOI: 10.2214/ajr.23.29518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/22/2023]
Abstract
The Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) recommendations were published in 2016 to standardize the reporting of MRI examinations performed to assess for disease progression in patients on active surveillance for prostate cancer. Although a limited number of studies have reported outcomes from use of PRECISE in clinical practice, the available studies have demonstrated PRECISE to have high pooled NPV but low pooled PPV for predicting progression. Our experience in using PRECISE in clinical practice at two teaching hospitals has highlighted issues with its application and areas requiring clarification. This Clinical Perspective critically appraises PRECISE on the basis of this experience, focusing on the system's key advantages and disadvantages and exploring potential changes to improve the system's utility. These changes include consideration of image quality when applying PRECISE scoring, incorporation of quantitative thresholds for disease progression, adoption of a PRECISE 3F sub-category for progression not qualifying as substantial, and comparisons with both the baseline and most recent prior examinations. Items requiring clarification include derivation of a patient-level score in patients with multiple lesions, intended application of PRECISE score 5 (i.e., if requiring development of disease that is no longer organ-confined), and categorization of new lesions in patients with prior MRI-invisible disease.
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Affiliation(s)
- Nimalan Sanmugalingam
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Box 218, Cambridge Biomedical Campus, CB2 0QQ, Cambridge, UK
| | - Nikita Sushentsev
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Box 218, Cambridge Biomedical Campus, CB2 0QQ, Cambridge, UK
| | - Kang-Lung Lee
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Box 218, Cambridge Biomedical Campus, CB2 0QQ, Cambridge, UK
- Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Iztok Caglic
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Box 218, Cambridge Biomedical Campus, CB2 0QQ, Cambridge, UK
| | - Cameron Englman
- Division of Surgery & Interventional Science, University College London, London, UK
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK
| | - Caroline M Moore
- Division of Surgery & Interventional Science, University College London, London, UK
- Department of Urology, University College London Hospital NHS Foundation Trust, London, UK
| | - Francesco Giganti
- Division of Surgery & Interventional Science, University College London, London, UK
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK
| | - Tristan Barrett
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Box 218, Cambridge Biomedical Campus, CB2 0QQ, Cambridge, UK
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10
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Coelho FMA, Amaral LTW, Mitsutake LKN, Mussi TC, Baroni RH. Quality assessment of prostate MRI by PI-QUAL score: Inter-reader agreement and impact on prostate cancer local staging at 3 Tesla. Eur J Radiol 2023; 165:110921. [PMID: 37336037 DOI: 10.1016/j.ejrad.2023.110921] [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: 03/08/2023] [Revised: 05/07/2023] [Accepted: 06/05/2023] [Indexed: 06/21/2023]
Abstract
PURPOSE To evaluate whether the Prostate Imaging Quality (PI-QUAL) score impacts prostate cancer (PCa) staging on MRI. The secondary goal was to test inter-reader agreement among radiologists experienced in prostate imaging. METHOD A retrospective, single-center study with patients who underwent 3 Tesla prostate MRI scans and were submitted to radical prostatectomy (RP) between January 2018 and November 2021 and were eligible for our study. Extraprostatic extension (EPE) data were collected from original MR reports (EPEm) and pathological reports of RP specimens (EPEp). Three expert prostate radiologists (ESUR/ESUI criteria R1, R2, R3) independently evaluated all MRI exams according to PI-QUAL score for image quality (1 to 5; 1: poor, 5: excellent), blinded to original imaging reports and clinical data. We studied the diagnostic performance of MRI using pooled data from PI-QUAL scores (≤3 vs. ≥4). We also performed univariate and multivariate analyses to assess the PI-QUAL score impact on local PCa staging. Cohen's K and Tau-b Kendall tests were used to assess the inter-reader agreement for PI-QUAL score, T2WI, DWI, and DCE. RESULTS Our final cohort included 146 patients, of which 27.4% presented EPE on pathology. We observed no impact of imaging quality on accuracy for EPE prediction: AUC of 0.750 (95% CI 0.26-1) for PI-QUAL ≤ 3 and 0.705 (95% CI 0.618-0.793) for PI-QUAL ≥ 4. The multivariate analysis demonstrated a correlation of EPEm (OR 3.25, p 0.001) and ISUP grade group (OR 1.89, p 0.012) to predict EPEp. The inter-reader agreement was moderate to substantial (0.539 for R1-R2, 0.522 for R2-R3, and 0.694 for R1-R3). CONCLUSION Our clinical impact evaluation showed no direct correlation between MRI quality by PI-QUAL score and accuracy in detecting EPE in patients undergoing RP. Additionally, we had moderate to a substantial inter-reader agreement for the PI-QUAL score.
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Affiliation(s)
| | - Lucas Tadashi Wada Amaral
- Department of Radiology, Hospital Israelita Albert Einstein. 627 Albert Einstein Ave. Sao Paulo, SP 05652-900, Brazil.
| | - Leonardo Kenji Nesi Mitsutake
- Department of Radiology, Hospital Israelita Albert Einstein. 627 Albert Einstein Ave. Sao Paulo, SP 05652-900, Brazil.
| | - Thais Caldara Mussi
- Department of Radiology, Hospital Israelita Albert Einstein. 627 Albert Einstein Ave. Sao Paulo, SP 05652-900, Brazil.
| | - Ronaldo Hueb Baroni
- Department of Radiology, Hospital Israelita Albert Einstein. 627 Albert Einstein Ave. Sao Paulo, SP 05652-900, Brazil.
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11
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Żurowska A, Pęksa R, Bieńkowski M, Skrobisz K, Sowa M, Matuszewski M, Biernat W, Szurowska E. Prostate Cancer and Its Mimics-A Pictorial Review. Cancers (Basel) 2023; 15:3682. [PMID: 37509343 PMCID: PMC10378330 DOI: 10.3390/cancers15143682] [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: 05/03/2023] [Revised: 06/24/2023] [Accepted: 07/14/2023] [Indexed: 07/30/2023] Open
Abstract
BACKGROUND Multiparametric prostate MRI (mpMRI) is gaining wider recommendations for diagnosing and following up on prostate cancer. However, despite the high accuracy of mpMRI, false positive and false negative results are reported. Some of these may be related to normal anatomic structures, benign lesions that may mimic cancer, or poor-quality images that hamper interpretation. The aim of this review is to discuss common potential pitfalls in the interpretation of mpMRI. METHODS mpMRI of the prostates was performed on 3T MRI scanners (Philips Achieva or Siemens Magnetom Vida) according to European Society of Urogenital Radiology (ESUR) guidelines and technical requirements. RESULTS This pictorial review discusses normal anatomical structures such as the anterior fibromuscular stroma, periprostatic venous plexus, central zone, and benign conditions such as benign prostate hyperplasia (BPH), post-biopsy hemorrhage, prostatitis, and abscess that may imitate prostate cancer, as well as the appearance of prostate cancer occurring in these locations. Furthermore, suggestions on how to avoid these pitfalls are provided, and the impact of image quality is also discussed. CONCLUSIONS In an era of accelerating prostate mpMRI and high demand for high-quality interpretation of the scans, radiologists should be aware of these potential pitfalls to improve their diagnostic accuracy.
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Affiliation(s)
- Anna Żurowska
- Second Department of Radiology, Medical University of Gdańsk, 80-214 Gdańsk, Poland
| | - Rafał Pęksa
- Department of Pathomorphology, Medical University of Gdańsk, 80-214 Gdańsk, Poland
| | - Michał Bieńkowski
- Department of Pathomorphology, Medical University of Gdańsk, 80-214 Gdańsk, Poland
| | - Katarzyna Skrobisz
- Department of Radiology, Medical University of Gdańsk, 80-214 Gdańsk, Poland
| | - Marek Sowa
- Department of Urology, Medical University of Gdańsk, 80-214 Gdańsk, Poland
| | - Marcin Matuszewski
- Department of Urology, Medical University of Gdańsk, 80-214 Gdańsk, Poland
| | - Wojciech Biernat
- Department of Pathomorphology, Medical University of Gdańsk, 80-214 Gdańsk, Poland
| | - Edyta Szurowska
- Second Department of Radiology, Medical University of Gdańsk, 80-214 Gdańsk, Poland
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12
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Wang R, Pinto D, Liu T, Hamade M, Jubane M, Arif A, Boateng J, Maloney S, Amin A, Sandhu J, Nini S, Manov J, Tordjman L, Villavicencio J, Chamoun M, Leslom S, Aristizabal J, Felix M, Gomez-Rodriguez C, Alessandrino F. Effect of a dedicated PI-QUAL curriculum on the assessment of prostate MRI quality. Eur J Radiol 2023; 164:110865. [PMID: 37167684 DOI: 10.1016/j.ejrad.2023.110865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 04/28/2023] [Accepted: 05/03/2023] [Indexed: 05/13/2023]
Abstract
PURPOSE The Prostate Imaging Quality (PI-QUAL) score is a metric to evaluate the diagnostic quality of multiparametric magnetic resonance imaging (MRI) of the prostate. This study evaluated the impact of a prostate MRI quality training lecture on the participant's ability to assess prostate MRI image quality. METHODS Eighteen in-training-radiologists of varying experience in reviewing diagnostic prostate MRI assessed the image quality of ten examinations. Then, they attended a dedicated lecture on MRI quality assessment using the PI-QUAL score. After the lecture, the same participants evaluated the image quality of a new set of ten scans applying the PI-QUAL score. Results were assessed using receiver operating characteristic (ROC) analysis. The reference standard was the PI-QUAL score assessed by a fellowship trained abdominal radiologist with experience in reading prostate MRI. RESULTS There was a significant improvement in the average area under the curve (AUC) for assessment of prostate MRI image quality from baseline (0.82; [0.576 - 0.888]) to post teaching (1.0; [0.954-1]), with an improvement of 0.18 (p < 0.03). When ROC curves were computed for different cohorts stratified based on year of training, difference ranged from 0.48 for second year residents to 0.32 for fourth year residents (p < 0.001-0.01). For abdominal imaging fellows, the pre-teaching AUC was 0.9 [0.557-1] and post teaching AUC was 1 [0.957-1], a difference of 0.1 (p = 0.20). CONCLUSIONS A dedicated lecture on PI-QUAL improved the ability of radiologists-in-training to assess prostate MRI image quality, with variable impact depending on year of training.
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Affiliation(s)
- Richard Wang
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Denver Pinto
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - TianHao Liu
- Division of Biostatistics, Department of Public Health Science, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Mohamad Hamade
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Maverick Jubane
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Aazim Arif
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Joseph Boateng
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Sean Maloney
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Ayush Amin
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Jagteshwar Sandhu
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Saad Nini
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - John Manov
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Laura Tordjman
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Joseph Villavicencio
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Michelle Chamoun
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Salman Leslom
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Julieta Aristizabal
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Marcelo Felix
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Carolina Gomez-Rodriguez
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA
| | - Francesco Alessandrino
- Department of Radiology, University of Miami/Jackson Memorial Hospital, Leonard M. Miller School of Medicine, Miami, FL, USA; Division of Abdominal Imaging, Department of Radiology, Leonard M. Miller School of Medicine, Miami, FL, USA.
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13
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Lin Y, Yilmaz EC, Belue MJ, Turkbey B. Prostate MRI and image Quality: It is time to take stock. Eur J Radiol 2023; 161:110757. [PMID: 36870241 PMCID: PMC10493032 DOI: 10.1016/j.ejrad.2023.110757] [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: 01/28/2023] [Revised: 02/15/2023] [Accepted: 02/21/2023] [Indexed: 03/06/2023]
Abstract
Multiparametric magnetic resonance imaging (mpMRI) plays a vital role in prostate cancer diagnosis and management. With the increase in use of mpMRI, obtaining the best possible quality images has become a priority. The Prostate Imaging Reporting and Data System (PI-RADS) was introduced to standardize and optimize patient preparation, scanning techniques, and interpretation. However, the quality of the MRI sequences depends not only on the hardware/software and scanning parameters, but also on patient-related factors. Common patient-related factors include bowel peristalsis, rectal distension, and patient motion. There is currently no consensus regarding the best approaches to address these issues and improve the quality of mpMRI. New evidence has been accrued since the release of PI-RADS, and this review aims to explore the key strategies which aim to improve prostate MRI quality, such as imaging techniques, patient preparation methods, the new Prostate Imaging Quality (PI-QUAL) criteria, and artificial intelligence on prostate MRI quality.
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Affiliation(s)
- Yue Lin
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Enis C Yilmaz
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Mason J Belue
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Baris Turkbey
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States.
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14
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Foley RW, Komber H, Charters P, Ali N, Burns-Cox N, Burn PR. The Effect of Oral Laxatives on Rectal Distension and Image Quality in Magnetic Resonance Imaging of the Prostate. Cureus 2023; 15:e35539. [PMID: 37007417 PMCID: PMC10055861 DOI: 10.7759/cureus.35539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/27/2023] [Indexed: 03/03/2023] Open
Abstract
Introduction Increasing rectal size is associated with increased artefacts on magnetic resonance imaging (MRI) of the prostate and has the potential to degrade image quality. The objective of this study was to analyse the effect of oral laxative medication on rectal distension and image quality in prostate MRI. Methods Eighty patients prospectively received either 15 mg of oral senna (laxative group) or no medication (control group). Patients underwent prostate MRI according to standard local protocol and seven rectal dimensions on axial and sagittal images were measured. A subjective assessment of rectal distension was also made using a five-point Likert scale. Finally, artefacts on diffusion-weighted sequences were assessed using a four-point Likert scale. Results There was a small reduction in rectal diameter on sagittal images in the laxative group compared to the control group, with mean diameters of 27.1 mm and 30.0 mm respectively, p=0.02. There was no significant difference in rectal measurements of anteroposterior diameter, transverse diameter, or rectal circumference on axial imaging. Subjective scoring also demonstrated no significant difference in diffusion-weighted imaging quality between the laxative group and control group, p=0.82. Conclusion Bowel preparation with the oral laxative, senna, provided only a marginal decrease in rectal distension on one measure and no reduction in artefacts on diffusion-weighted sequences. The findings of this study do not support the routine use of this medication in patients undergoing prostate MRI.
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15
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Prabhakar S, Schieda N. Patient preparation for prostate MRI: A scoping review. Eur J Radiol 2023; 162:110758. [PMID: 36905717 DOI: 10.1016/j.ejrad.2023.110758] [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: 01/31/2023] [Revised: 02/17/2023] [Accepted: 02/22/2023] [Indexed: 02/27/2023]
Abstract
PURPOSE To perform a scoping review of the literature evaluating patient preparation for prostate MRI. METHODS We conducted a search of English language literature, between 1989 and 2022 using MEDLINE and EMBASE for key terms: diet, enema, gel, catheter and anti-spasmodic agents linked to prostate MRI. Studies were reviewed for: level of evidence (LOE), study design and key results. Knowledge gaps were identified. RESULTS Three studies evaluated dietary modification in 655 patients. LOE was 3. All studies showed improved DWI and T2W image quality (IQ) and reduced DWI artifact. Nine studies evaluated enema use in 1551 patients. Mean LOE was 2.8 (range 2-3). Six studies reported IQ; DWI and T2W IQ were significantly improved with enema in 5/6 and 4/6 studies respectively. Only one study evaluated DWI/T2W lesion visibility which was improved with enema. One study evaluated impact of enema on eventual prostate cancer diagnosis, showing no benefit in false negative reduction. One study (LOE = 2, 150 patients) evaluated rectal gel; however, in combination with enema showing improved DWI and T2W IQ, lesion visibility and PI-QUAL compared to no preparation. Two studies evaluated use of rectal catheter in 396 patients. LOE was 3. One study showed improved DWI and T2W IQ and artifact compared to no preparation; however, the other showed inferior results comparing rectal catheter to enema. Six studies evaluated anti-spasmodic agent use in 888 patients. Mean LOE was 2.8 (range 2-3). Benefit of anti-spasmodic agent use on image quality and artifact on DWI and T2W are conflicting with no clear benefit. CONCLUSION Data evaluating patient preparation for prostate MRI is limited by level of evidence, study design and conflicting results. The majority of published studies do not evaluate impact of patient preparation on eventual prostate cancer diagnosis.
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Affiliation(s)
| | - Nicola Schieda
- Department of Medical Imaging, The Ottawa Hospital, 1053 Carling Avenue, Room C159, Ottawa, ON K1Y 4E9, Canada.
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16
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Kim CK. [Prostate Imaging Reporting and Data System (PI-RADS) v 2.1: Overview and Critical Points]. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2023; 84:75-91. [PMID: 36818694 PMCID: PMC9935951 DOI: 10.3348/jksr.2022.0169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 01/15/2023] [Accepted: 01/20/2023] [Indexed: 02/09/2023]
Abstract
The technical parameters and imaging interpretation criteria of the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) using multiparametric MRI (mpMRI) are updated in PI-RADS v2.1. These changes have been an expected improvement for prostate cancer evaluation, although some issues remain unsolved, and new issues have been raised. In this review, a brief overview of PI-RADS v2.1 is and several critical points are discussed as follows: the need for more detailed protocols of mpMRI, lack of validation of the revised transition zone interpretation criteria, the need for clarification for the revised diffusion-weighted imaging and dynamic contrast-enhanced imaging criteria, anterior fibromuscular stroma and central zone assessment, assessment of background signal and tumor aggressiveness, changes in the structured report, the need for the parameters for imaging quality and performance control, and indications for expansion of the system to include other indications.
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Affiliation(s)
- Chan Kyo Kim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
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17
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Barrett T, de Rooij M, Giganti F, Allen C, Barentsz JO, Padhani AR. Quality checkpoints in the MRI-directed prostate cancer diagnostic pathway. Nat Rev Urol 2023; 20:9-22. [PMID: 36168056 DOI: 10.1038/s41585-022-00648-4] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/11/2022] [Indexed: 01/11/2023]
Abstract
Multiparametric MRI of the prostate is now recommended as the initial diagnostic test for men presenting with suspected prostate cancer, with a negative MRI enabling safe avoidance of biopsy and a positive result enabling MRI-directed sampling of lesions. The diagnostic pathway consists of several steps, from initial patient presentation and preparation to performing and interpreting MRI, communicating the imaging findings, outlining the prostate and intra-prostatic target lesions, performing the biopsy and assessing the cores. Each component of this pathway requires experienced clinicians, optimized equipment, good inter-disciplinary communication between specialists, and standardized workflows in order to achieve the expected outcomes. Assessment of quality and mitigation measures are essential for the success of the MRI-directed prostate cancer diagnostic pathway. Quality assurance processes including Prostate Imaging-Reporting and Data System, template biopsy, and pathology guidelines help to minimize variation and ensure optimization of the diagnostic pathway. Quality control systems including the Prostate Imaging Quality scoring system, patient-level outcomes (such as Prostate Imaging-Reporting and Data System MRI score assignment and cancer detection rates), multidisciplinary meeting review and audits might also be used to provide consistency of outcomes and ensure that all the benefits of the MRI-directed pathway are achieved.
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Affiliation(s)
- Tristan Barrett
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.
| | - Maarten de Rooij
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands
| | - Francesco Giganti
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK
- Division of Surgery and Interventional Science, University College London, London, UK
| | - Clare Allen
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK
| | - Jelle O Barentsz
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands
| | - Anwar R Padhani
- Paul Strickland Scanner Centre, Mount Vernon Hospital, Middlesex, UK
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18
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Reduced field-of-view and multi-shot DWI acquisition techniques: Prospective evaluation of image quality and distortion reduction in prostate cancer imaging. Magn Reson Imaging 2022; 93:108-114. [DOI: 10.1016/j.mri.2022.08.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 08/03/2022] [Accepted: 08/03/2022] [Indexed: 11/20/2022]
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19
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Hosseiny M, Sung KH, Felker E, Suvannarerg V, Tubtawee T, Shafa A, Arora KR, Ching J, Gulati A, Azadikhah A, Zhong X, Sayre J, Lu D, Raman SS. Read-out Segmented Echo Planar Imaging with Two-Dimensional Navigator Correction (RESOLVE): An Alternative Sequence to Improve Image Quality on Diffusion-Weighted Imaging of Prostate. Br J Radiol 2022; 95:20211165. [PMID: 35671135 PMCID: PMC10162059 DOI: 10.1259/bjr.20211165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 04/28/2022] [Accepted: 05/23/2022] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE We aimed to investigate if the use of read-out segmented echoplanar imaging with additional two-dimensional navigator correction (Readout Segmentation of Long Variable Echo, RESOLVE) for acquiring prostate diffusion-weighted imaging (DWI) improves image quality, compared to single-shot echoplanar imaging (ss-EPI). METHODS This single-center prospective study cohort included 162 males with suspected prostate cancer, who underwent 3 Tesla multiparametric MRI (3T-mpMRI). Two abdominal radiologists, blinded to the clinical information, separately reviewed each 3T-mpMRI study to rank geometrical distortion, degree of rectal distention, lesion conspicuity, and anatomic details delineation first on ss-EPI-DWI and later on RESOLVE-DWI using 5-point scales (1 = excellent, 5 = poor). The average of the ranking scores given by two readers was generated and used as the final score. RESULTS There was good-to-excellent interreader agreement for scoring image quality parameters on both ss-EPI and RESOLVE. Geometrical distortion scores > 3 was seen in 12.3% (20/162) of ss-EPI images, with all having geometrical distortion score <3 on RESOLVE (p < .001). The mean image distortion score was significantly less on RESOLVE than ss-EPI (1.16 vs 1.61, p < .01 regardless of rectal gas, p< .05 when stratified by the degree of rectal distention ). RESOLVE was superior to ss-EPI for lesion conspicuity (mean 1.35 vs 1.53, p< .002) and anatomic delineation (2.60 vs 2.68, p< .001) of prostate on DWI. CONCLUSION Compared to conventional ss-EPI, the use of RESOLVE for acquisition of prostate DWI resulted in significantly enhanced image quality and reduced geometrical distortion. ADVANCES IN KNOWLEDGE RESOLVE could be an alternative or replacement of ss-EPI for acquiring prostate DWI with significantly less geometrical distortion and significantly improved lesion conspicuity and anatomic delineation.
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Affiliation(s)
- Melina Hosseiny
- Department of Radiology, Ronald Reagan-UCLA Medical Center, David Geffen School of Medicine at UCLA, Los Angeles, California, United States
| | - Kyung Hyun Sung
- Department of Radiology, Ronald Reagan-UCLA Medical Center, David Geffen School of Medicine at UCLA, Los Angeles, California, United States
| | - Ely Felker
- Department of Radiology, Ronald Reagan-UCLA Medical Center, David Geffen School of Medicine at UCLA, Los Angeles, California, United States
| | - Voraparee Suvannarerg
- Department of Radiology, Ronald Reagan-UCLA Medical Center, David Geffen School of Medicine at UCLA, Los Angeles, California, United States
| | | | - Ariel Shafa
- Department of Radiology, Ronald Reagan-UCLA Medical Center, David Geffen School of Medicine at UCLA, Los Angeles, California, United States
| | - Krishan R. Arora
- Department of Radiology, Ronald Reagan-UCLA Medical Center, David Geffen School of Medicine at UCLA, Los Angeles, California, United States
| | - Justin Ching
- Department of Radiology, Ronald Reagan-UCLA Medical Center, David Geffen School of Medicine at UCLA, Los Angeles, California, United States
| | - Anjalie Gulati
- Department of Radiology, Ronald Reagan-UCLA Medical Center, David Geffen School of Medicine at UCLA, Los Angeles, California, United States
| | - Afshin Azadikhah
- Department of Radiology, Ronald Reagan-UCLA Medical Center, David Geffen School of Medicine at UCLA, Los Angeles, California, United States
| | - Xiaodong Zhong
- Siemens Healthcare, MR R&D Collaborations, Lilburn, Georgia, United States
| | - James Sayre
- Department of Bioinformatics, David Geffen School of Medicine at UCLA, Los Angeles, California, United States
| | - David Lu
- Department of Radiology, Ronald Reagan-UCLA Medical Center, David Geffen School of Medicine at UCLA, Los Angeles, California, United States
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20
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Impact of enema prep on the false-negative rate of a PI-RADS 1 MRI of the prostate for clinically significant prostate cancer. Abdom Radiol (NY) 2022; 47:2494-2499. [PMID: 35583821 DOI: 10.1007/s00261-022-03547-9] [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: 01/11/2022] [Revised: 04/27/2022] [Accepted: 04/28/2022] [Indexed: 11/01/2022]
Abstract
PURPOSE To investigate whether use of an enema prep reduces the false-negative (FN) rate of PI-RADS 1 MRI of the prostate for clinically significant prostate cancer (csPCa). MATERIALS AND METHODS 1108 consecutive patients with a PI-RADS 1 MRI performed 01/2016-09/2021 were retrospectively collected. Patient charts were examined for subsequent systematic prostate biopsy performed within 1 year if positive or anytime thereafter if negative. Patients without biopsy were excluded. Use of an enema prep 1-2 h before MRI, which was implemented in 03/2019, was recorded. FN rate of MRI for detection of csPCa, defined as Gleason score ≥ 7, using systematic biopsy was assessed per patient and compared between those with and without an enema prep. Χ2 test and logistic regression were performed. RESULTS 255 patients (median age 64, IQR 58-69) with median PSA 5.6 (IQR 4.2-8.1), PI-RADS 1 MRI, and subsequent biopsy were included in the analysis. 66 patients (26%) had an enema prep and 189 patients (74%) did not. 7 (11%) patients with and 21 (11%) patients without enema prep had a FN biopsy. There was no significant association between enema prep and FN biopsy (OR 0.95, 95% CI 0.38-2.35, p = 0.91). CONCLUSIONS Use of an enema prep prior to prostate MRI did not decrease the FN rate of PI-RADS 1 MRI of the prostate for clinically significant prostate cancer.
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21
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Karanasios E, Caglic I, Zawaideh JP, Barrett T. Prostate MRI quality: clinical impact of the PI-QUAL score in prostate cancer diagnostic work-up. Br J Radiol 2022; 95:20211372. [PMID: 35179971 PMCID: PMC10993954 DOI: 10.1259/bjr.20211372] [Citation(s) in RCA: 50] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/21/2022] [Accepted: 01/29/2022] [Indexed: 12/27/2022] Open
Abstract
OBJECTIVE To assess the reproducibility and impact of prostate imaging quality (PI-QUAL) scores in a clinical cohort undergoing prostate multiparametric MRI. METHODS PI-QUAL scores were independently recorded by three radiologists (two senior, one junior). Readers also recorded whether MRI was sufficient to rule-in/out cancer and if repeat imaging was required. Inter-reader agreement was assessed using Cohen's κ. PI-QUAL scores were further correlated to PI-RADS score, number of biopsy procedures, and need for repeat imaging. RESULTS Image quality was sufficient (≥PI-QUAL-3) in 237/247 (96%) and optimal (≥PI-QUAL-4) in 206/247 (83%) of males undergoing 3T-MRI. Overall PI-QUAL scores showed moderate inter-reader agreement for senior (K = 0.51) and junior-senior readers (K = 0.47), with DCE showing highest agreement (K = 0.47). With PI-QUAL-5 studies, the negative MRI calls increased from 50 to 87% and indeterminate PI-RADS-3 rates decreased from 31.8. to 10.4% compared to lower quality PI-QUAL-3 studies. More patients with PI-QUAL scores 1-3 underwent biopsy for negative (47%) and indeterminate probability (100%) MRIs compared to PI-QUAL score 4-5 (30 and 75%, respectively). Ability to rule-in cancer increased with PI-QUAL score, from 50% at PI-QUAL 1-2 to 90% for PI-QUAL 4-5, with a similarly, but greater effect for ruling-out cancer and at a lower threshold, from 0% for scans of PI-QUAL 1-2 to 67.1% for PI-QUAL 4 and 100% for PI-QUAL-5. CONCLUSION Higher PI-QUAL scores for image quality are associated with decreased uncertainty in MRI decision-making and improved efficiency of diagnostic pathway delivery. ADVANCES IN KNOWLEDGE This study demonstrates moderate inter-reader agreement for PI-QUAL scoring and validates the score in a clinical setting, showing correlation of image quality to certainty of decision making and clinical outcomes of repeat imaging and biopsy of low-to-intermediate risk cases.
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Affiliation(s)
| | - Iztok Caglic
- Department of Radiology, Addenbrooke’s Hospital and
University of Cambridge, Cambridge,
UK
| | - Jeries P. Zawaideh
- Department of Radiology, Addenbrooke’s Hospital and
University of Cambridge, Cambridge,
UK
- Department of Radiology, IRCCS Policlinico San
Martino, Genoa,
Italy
| | - Tristan Barrett
- Department of Radiology, Addenbrooke’s Hospital and
University of Cambridge, Cambridge,
UK
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22
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Jung W, Kim EH, Ko J, Jeong G, Choi MH. Convolutional neural network-based reconstruction for acceleration of prostate T 2 weighted MR imaging: a retro- and prospective study. Br J Radiol 2022; 95:20211378. [PMID: 35148172 PMCID: PMC10993971 DOI: 10.1259/bjr.20211378] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 01/19/2022] [Accepted: 01/24/2022] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE The aim of this study was to develop a deep neural network (DNN)-based parallel imaging reconstruction for highly accelerated 2D turbo spin echo (TSE) data in prostate MRI without quality degradation compared to conventional scans. METHODS 155 participant data were acquired for training and testing. Two DNN models were generated according to the number of acquisitions (NAQ) of input images: DNN-N1 for NAQ = 1 and DNN-N2 for NAQ = 2. In the test data, DNN and TSE images were compared by quantitative error metrics. The visual appropriateness of DNN reconstructions on accelerated scans (DNN-N1 and DNN-N2) and conventional scans (TSE-Conv) was assessed for nine parameters by two radiologists. The lesion detection was evaluated at DNNs and TES-Conv by prostate imaging-reporting and data system. RESULTS The scan time was reduced by 71% at NAQ = 1, and 42% at NAQ = 2. Quantitative evaluation demonstrated the better error metrics of DNN images (29-43% lower NRMSE, 4-13% higher structure similarity index, and 2.8-4.8 dB higher peak signal-to-noise ratio; p < 0.001) than TSE images. In the assessment of the visual appropriateness, both radiologists evaluated that DNN-N2 showed better or comparable performance in all parameters compared to TSE-Conv. In the lesion detection, DNN images showed almost perfect agreement (κ > 0.9) scores with TSE-Conv. CONCLUSIONS DNN-based reconstruction in highly accelerated prostate TSE imaging showed comparable quality to conventional TSE. ADVANCES IN KNOWLEDGE Our framework reduces the scan time by 42% of conventional prostate TSE imaging without sequence modification, revealing great potential for clinical application.
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Affiliation(s)
| | - Eu Hyun Kim
- Department of Radiology, St.Vincent’s Hospital, College
of Medicine, The Catholic University of Korea, Suwon,
Gyeonggi-do, Republic of Korea
| | - Jingyu Ko
- AIRS Medical, 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
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23
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Takeuchi T, Hayashi N, Asai Y, Kayaoka Y, Yoshida K. Novel method for evaluating spatial resolution of magnetic resonance images. Phys Eng Sci Med 2022; 45:487-496. [PMID: 35230638 DOI: 10.1007/s13246-022-01114-6] [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: 08/17/2021] [Accepted: 02/22/2022] [Indexed: 11/29/2022]
Abstract
Recently, several methods for evaluating the spatial resolution of magnetic resonance imaging have been reported. However, these methods are not simple and can only be used for specific devices. In this study, we develop a new method (the ladder method) and evaluate its measurement accuracy by adapting the International Electrotechnical Commission (IEC) method to evaluate the spatial resolution. First, the suitable condition for the ladder method was determined by numerical experiments. The ladder method uses a phantom with a periodic pattern which is based on IEC method. Subsequently, the ladder method is evaluated in terms of spatial resolution by dividing the standard deviation (SD) by the average signal in the region of interest (ROI) on the ladder phantom image. To evaluate the precision of the ladder method, it is compared with the modulation transfer function (MTF) calculated from an edge image. The numerical experiment result shows that the evaluation of the spatial resolution using the ladder method is viable, in which a single regression analysis's coefficient of correlation between ladder and MTF of 0.90 or higher is obtained for all evaluations. The ladder method can be assessed using only the signal mean value and SD in the ROI on the target image and exhibit a strong correlation with the MTF. Therefore, the ladder method is a promising method as a substitute for the MTF.
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Affiliation(s)
- Tomokazu Takeuchi
- Graduate School, Gunma Prefectural College of Health Sciences, Maebashi, Gunma, Japan.
| | - Norio Hayashi
- Graduate School, Gunma Prefectural College of Health Sciences, Maebashi, Gunma, Japan
| | - Yuta Asai
- Department of Radiology, Nippon Medical School Hospital, Tokyo, Japan
| | - Yuka Kayaoka
- MedCity21, Division of Premier Preventive Medicine, Osaka City University Hospital, Osaka, Japan
| | - Kiichi Yoshida
- Department of Radiology, Nippon Medical School Hospital, Tokyo, Japan
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24
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Ippoliti S, Fletcher P, Orecchia L, Miano R, Kastner C, Barrett T. Optimal biopsy approach for detection of clinically significant prostate cancer. Br J Radiol 2022; 95:20210413. [PMID: 34357796 PMCID: PMC8978235 DOI: 10.1259/bjr.20210413] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 07/14/2021] [Accepted: 07/18/2021] [Indexed: 11/05/2022] Open
Abstract
Prostate cancer (PCa) diagnostic and therapeutic work-up has evolved significantly in the last decade, with pre-biopsy multiparametric MRI now widely endorsed within international guidelines. There is potential to move away from the widespread use of systematic biopsy cores and towards an individualised risk-stratified approach. However, the evidence on the optimal biopsy approach remains heterogeneous, and the aim of this review is to highlight the most relevant features following a critical assessment of the literature. The commonest biopsy approaches are via the transperineal (TP) or transrectal (TR) routes. The former is considered more advantageous due to its negligible risk of post-procedural sepsis and reduced need for antimicrobial prophylaxis; the more recent development of local anaesthetic (LA) methods now makes this approach feasible in the clinic. Beyond this, several techniques are available, including cognitive registration, MRI-Ultrasound fusion imaging and direct MRI in-bore guided biopsy. Evidence shows that performing targeted biopsies reduces the number of cores required and can achieve acceptable rates of detection whilst helping to minimise complications and reducing pathologist workloads and costs to health-care facilities. Pre-biopsy MRI has revolutionised the diagnostic pathway for PCa, and optimising the biopsy process is now a focus. Combining MR imaging, TP biopsy and a more widespread use of LA in an outpatient setting seems a reasonable solution to balance health-care costs and benefits, however, local choices are likely to depend on the expertise and experience of clinicians and on the technology available.
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Affiliation(s)
- Simona Ippoliti
- Urology Department, The Queen Elizabeth Hospital NHS Foundation Trust, King’s Lynn, Norfolk, UK
| | - Peter Fletcher
- Urology Department, Cambridge University Hospitals, Cambridge, UK
| | | | | | - Christof Kastner
- Urology Department, Cambridge University Hospitals, Cambridge, UK
| | - Tristan Barrett
- Radiology Department, Cambridge University Hospitals, Cambridge, UK
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25
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Arnoldner MA, Polanec SH, Lazar M, Kadhjavi S, Clauser P, Pötsch N, Schwarz-Nemec U, Korn S, Hübner N, Shariat SF, Helbich TH, Baltzer PAT. Rectal preparation significantly improves prostate imaging quality: Assessment of the PI-QUAL score with visual grading characteristics. Eur J Radiol 2022; 147:110145. [PMID: 35007983 DOI: 10.1016/j.ejrad.2021.110145] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 12/23/2021] [Accepted: 12/29/2021] [Indexed: 01/13/2023]
Abstract
PURPOSE To investigate the effects of a rectal preparation regimen, that consisted of a rectal cleansing enema and an endorectal gel filling protocol, on prostate imaging quality (PI-QUAL). METHODS Multiparametric MRI (mpMRI) was performed in 150 consecutive patients divided into two groups of 75 patients. One group received a rectal preparation with a cleansing enema and endorectal gel filling (median age 65.3 years, median PSA level 6 ng/ml). The other patient group did not receive such a preparation (median age 64 years, median PSA level 6 ng/ml). Two uroradiologists independently rated general image quality and lesion visibility on diffusion-weighted imaging (DWI), T2-weighted (T2w), and dynamic contrast-enhanced (DCE) images using a five-point ordinal scale. In addition, two uroradiologists assigned PI-QUAL scores, using the dedicated scoring sheet. Data sets were compared using visual grading characteristics (VGC) and receiver operating characteristics (ROC)/ area under the curve (AUC) analysis. RESULTS VGC revealed significantly better general image quality for DWI (AUC R1 0.708 (0.628-0.779 CI, p < 0.001; AUC R2 0.687 (0.606-0.760 CI, p < 0.001) and lesion visibility for both readers (AUC R1 0.729 (0.607-0.831 CI, p < 0.001); AUC R2 0.714 (0.590-0.818CI, p < 0.001) in the preparation group. For T2w imaging, rectal preparation resulted in significantly better lesion visibility for both readers (R1 0.663 (0.537-0.774 CI, p = 0.014; R2 0.663 (0.537-0.774 CI, p = 0.014)). Averaged PI-QUAL scores were significantly improved with rectal preparation (AUC R3/R4 0.667, CI 0.581-0.754, p < 0.001). CONCLUSION Rectal preparation significantly improved prostate imaging quality (PI-QUAL) and lesion visibility. Hence, a rectal preparation regimen consisting of a rectal cleansing enema and an endorectal gel filling could be considered.
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Affiliation(s)
- Michael A Arnoldner
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Austria
| | | | | | - Sam Kadhjavi
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Austria
| | - Paola Clauser
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Austria
| | - Nina Pötsch
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Austria
| | - Ursula Schwarz-Nemec
- Department of Biomedical Imaging and Image-guided Therapy, Division of Neuroradiology and Musculoskeletal Radiology, Medical University of Vienna, Austria
| | - Stephan Korn
- Department of Urology, Medical University of Vienna, Austria
| | - Nicolai Hübner
- Department of Urology, Medical University of Vienna, Austria
| | - Shahrokh F Shariat
- Department of Urology, Medical University of Vienna, Austria; Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, Weill Cornell Medical College, New York, NY, USA; Department of Urology, University of Texas Southwestern, Dallas, TX, USA; Department of Urology, Second Faculty of Medicine, Charles University, Prag, Czech Republic; Institute for Urology and Reproductive Health, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Thomas H Helbich
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Austria
| | - Pascal A T Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Austria.
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Surasi DSS, Wang X, Bathala TK, Hwang H, Arora S, Westphalen AC, Chang SD, Turkbey B. The impact and collateral damage of COVID-19 on prostate MRI and guided biopsy operations: Society of Abdominal Radiology Prostate Cancer Disease-Focused Panel survey analysis. Abdom Radiol (NY) 2021; 46:4362-4369. [PMID: 33904992 PMCID: PMC8077193 DOI: 10.1007/s00261-021-03087-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 04/03/2021] [Accepted: 04/09/2021] [Indexed: 11/30/2022]
Abstract
The Coronavirus disease 2019 (COVID-19) pandemic has significantly affected health care systems throughout the world. A Qualtrics survey was targeted for radiologists around the world to study its effect on the operations of prostate MRI studies and biopsies. Descriptive statistics were reported. A total of 60 complete responses from five continents were included in the analysis. 70% of the responses were from academic institutions. Among all participants, the median (range) number of prostate MRI was 20 (0, 135) per week before the COVID-19 pandemic versus 10 (0, 30) during the lockdown period; the median (range) number of prostate biopsies was 4.5 (0, 60) per week before the COVID-19 versus 0 (0, 12) during the lockdown period. Among the 30% who used bowel preparation for their patients prior to MRI routinely, 11% stopped the bowel preparation due to the pandemic. 47% reported that their radiology departments faced staff disruptions, while 68% reported changes in clinic schedules in other clinical departments, particularly urology, genitourinary medical oncology, and radiation oncology. Finally, COVID-19 pandemic was found to disrupt not only the clinical prostate MRI operations but also impacted prostate MRI/biopsy research in up to 50% of institutions. The impact of this collateral damage in delaying diagnosis and treatment of prostate cancer is yet to be explored.
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Affiliation(s)
- Devaki Shilpa S Surasi
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Society of Abdominal Radiology, 1061 E. Main Street, Suite 300, East Dundee, IL, USA.
| | - Xuemei Wang
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Tharakeswara K Bathala
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Society of Abdominal Radiology, 1061 E. Main Street, Suite 300, East Dundee, IL, USA
| | - Hyunsoo Hwang
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sandeep Arora
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
- Society of Abdominal Radiology, 1061 E. Main Street, Suite 300, East Dundee, IL, USA
| | - Antonio C Westphalen
- Departments of Radiology, Urology and Radiation Oncology, University of Washington, Seattle, WA, USA
- Society of Abdominal Radiology, 1061 E. Main Street, Suite 300, East Dundee, IL, USA
| | - Silvia D Chang
- Department of Radiology, Vancouver General Hospital, University of British Columbia, Vancouver, Canada
- Society of Abdominal Radiology, 1061 E. Main Street, Suite 300, East Dundee, IL, USA
| | - Baris Turkbey
- Department Molecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- Society of Abdominal Radiology, 1061 E. Main Street, Suite 300, East Dundee, IL, USA
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Czyzewska D, Sushentsev N, Latoch E, Slough RA, Barrett T. T2-PROPELLER Compared to T2-FRFSE for Image Quality and Lesion Detection at Prostate MRI. Can Assoc Radiol J 2021; 73:355-361. [PMID: 34423672 DOI: 10.1177/08465371211030206] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
PURPOSE The primary objective was to compare T2-FRFSE and T2-PROPELLER sequences for image quality. The secondary objective was to compare the ability to detect prostate lesions at MRI in the presence and absence of motion artefact using the 2 sequences. METHODS 99 patients underwent 3 T MRI examination of the prostate, including T2-FRFSE and T2-PROPELLER sequences. All patients underwent prostate biopsy. Two independent readers rated overall image quality, presence of motion artefact, and blurring for both sequences using a 5-point Likert scale. Scores were compared for the whole group and for subgroups with and without significant motion artefact. Outcome for lesion detection at an MRI threshold of PI-RADS score ≥3 was compared between T2-FRFSE and T2-PROPELLER. RESULTS The overall image quality was not significantly different between T2-FRFSE and T2-PROPELLER sequences (3.74 vs. 3.93, p = 0.275). T2-PROPELLER recorded a lesser degree of motion artefact (score 4.53 vs. 3.78, p <0.0001), but demonstrated greater image blurring (score 3.29 vs. 3.73, p <0.001). However, in a subgroup of patients with significant motion artefact on T2-FRFSE, the T2-PROPELLER sequence demonstrated significantly higher image quality (3.46 vs. 2.49, p <0.001). T2-FRFSE and T2-PROPELLER showed comparable positive predictive values for lesion detection at 93.2% and 97.7%, respectively. CONCLUSIONS T2-PROPELLER provides higher quality imaging in the presence of motion artefact, but T2-FRFSE is preferred in the absence of motion. T2-PROPELLER is therefore recommended as a secondary T2 sequence when imaging requires repeat acquisition due to motion artefact.
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Affiliation(s)
- Dorota Czyzewska
- Department of Clinical Physiology, Nuclear Medicine & PET, Rigshospitalet, Copenhagen, Denmark
| | - Nikita Sushentsev
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
| | - Eryk Latoch
- Department of Pediatric Oncology and Hematology, Medical University of Bialystok, Poland
| | - Rhys A Slough
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
| | - Tristan Barrett
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.,CamPARI Prostate Cancer Group, Addenbrooke's Hospital and University of Cambridge, Cambridge, United Kingdom
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Sathiadoss P, Haroon M, Osman H, Ahmad F, Papadatos P, Schieda N. Comparison of 5 Rectal Preparation Strategies for Prostate MRI and Impact on Image Quality. Can Assoc Radiol J 2021; 73:346-354. [PMID: 34404240 DOI: 10.1177/08465371211033753] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
PURPOSE To compare 5 different rectal preparation strategies for prostate MRI. METHODS This 5-arm quality-assurance study evaluated 56 patients per arm (280 patients) including: no preparation, clear-fluids diet (CFD) beginning at 00:00 hours on the day of MRI, Fleet®-enema, enema + CFD, enema + CFD + IV-antispasmodic agent. The study was powered to 0.80 with alpha-error of 0.05. Three blinded radiologists independently evaluated T2-Weighted (T2W) and Diffusion Weighed Imaging (DWI) for: rectal diameter (maximal AP diameter), rectal content (stool, fluid, gas), rectal motion, T2W/DWI image quality, T2W image sharpness and DWI susceptibility artifact using 5-point Likert scales. Overall comparisons were performed using analysis of variance (ANOVA) and Kruskal-Wallis, with pair-wise comparisons using paired t-tests and Wilcoxon sign-rank tests. RESULTS Rectal diameter and amount of gas were lower in enema compared to non-enema groups (p < 0.001), with smallest diameter and least gas in the enema + CFD + IV-antispasmodic group (p = 0.022-<0.001). T2W image quality and sharpness were highest in the enema + CFD groups (p < 0.001) with no difference comparing enema + CFD with/without IV-antispasmodic (p = 0.064, 0.084). Motion artifact was least in enema + CFD + IV-antispasmodic group compared to all other groups (p < 0.001), followed by the enema + CFD group (p = 0.008-<0.001). DWI image quality was highest (p < 0.001) and DWI susceptibility artifact lowest (p < 0.001) in the enema + CFD groups (p < 0.001) and did not differ comparing enema + CFD with/without anti-spasmodic (p = 0.058-0.202). CONCLUSIONS Use of enema + clear-fluids diet before prostate MRI yields the highest T2W and DWI image quality with the least DWI artifact. IV-antispasmodic use reduces motion on T2W but does not improve image quality on T2W or DWI, or lessen DWI artifact compared to enema + clear-fluids diet.
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Affiliation(s)
- Paul Sathiadoss
- Department of Medical Imaging, The Ottawa Hospital, 6363University of Ottawa, Ottawa, Ontario, Canada
| | - Mohammad Haroon
- Department of Medical Imaging, The Ottawa Hospital, 6363University of Ottawa, Ottawa, Ontario, Canada
| | - Heba Osman
- Department of Medical Imaging, The Ottawa Hospital, 6363University of Ottawa, Ottawa, Ontario, Canada
| | - Faraz Ahmad
- Faculty of Medicine, 6363University of Ottawa, Ottawa, Ontario, Canada
| | - Philip Papadatos
- Department of Medical Imaging, The Ottawa Hospital, 6363University of Ottawa, Ottawa, Ontario, Canada
| | - Nicola Schieda
- Department of Medical Imaging, The Ottawa Hospital, 6363University of Ottawa, Ottawa, Ontario, Canada
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Cipollari S, Guarrasi V, Pecoraro M, Bicchetti M, Messina E, Farina L, Paci P, Catalano C, Panebianco V. Convolutional Neural Networks for Automated Classification of Prostate Multiparametric Magnetic Resonance Imaging Based on Image Quality. J Magn Reson Imaging 2021; 55:480-490. [PMID: 34374181 PMCID: PMC9291235 DOI: 10.1002/jmri.27879] [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: 06/07/2021] [Revised: 07/28/2021] [Accepted: 07/29/2021] [Indexed: 12/26/2022] Open
Abstract
Background Prostate magnetic resonance imaging (MRI) is technically demanding, requiring high image quality to reach its full diagnostic potential. An automated method to identify diagnostically inadequate images could help optimize image quality. Purpose To develop a convolutional neural networks (CNNs) based analysis pipeline for the classification of prostate MRI image quality. Study Type Retrospective. Subjects Three hundred sixteen prostate mpMRI scans and 312 men (median age 67). Field Strength/Sequence A 3 T; fast spin echo T2WI, echo planar imaging DWI, ADC, gradient‐echo dynamic contrast enhanced (DCE). Assessment MRI scans were reviewed by three genitourinary radiologists (V.P., M.D.M., S.C.) with 21, 12, and 5 years of experience, respectively. Sequences were labeled as high quality (Q1) or low quality (Q0) and used as the reference standard for all analyses. Statistical Tests Sequences were split into training, validation, and testing sets (869, 250, and 120 sequences, respectively). Inter‐reader agreement was assessed with the Fleiss kappa. Following preprocessing and data augmentation, 28 CNNs were trained on MRI slices for each sequence. Model performance was assessed on both a per‐slice and a per‐sequence basis. A pairwise t‐test was performed to compare performances of the classifiers. Results The number of sequences labeled as Q0 or Q1 was 38 vs. 278 for T2WI, 43 vs. 273 for DWI, 41 vs. 275 for ADC, and 38 vs. 253 for DCE. Inter‐reader agreement was almost perfect for T2WI and DCE and substantial for DWI and ADC. On the per‐slice analysis, accuracy was 89.95% ± 0.02% for T2WI, 79.83% ± 0.04% for DWI, 76.64% ± 0.04% for ADC, 96.62% ± 0.01% for DCE. On the per‐sequence analysis, accuracy was 100% ± 0.00% for T2WI, DWI, and DCE, and 92.31% ± 0.00% for ADC. The three best algorithms performed significantly better than the remaining ones on every sequence (P‐value < 0.05). Data Conclusion CNNs achieved high accuracy in classifying prostate MRI image quality on an individual‐slice basis and almost perfect accuracy when classifying the entire sequences. Evidence Level 4 Technical Efficacy Stage 1
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Affiliation(s)
- Stefano Cipollari
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Rome, Italy
| | - Valerio Guarrasi
- Department of Computer, Control and Management Engineering, Sapienza University of Rome, Italy
| | - Martina Pecoraro
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Rome, Italy
| | - Marco Bicchetti
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Rome, Italy
| | - Emanuele Messina
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Rome, Italy
| | - Lorenzo Farina
- Department of Computer, Control and Management Engineering, Sapienza University of Rome, Italy
| | - Paola Paci
- Department of Computer, Control and Management Engineering, Sapienza University of Rome, Italy
| | - Carlo Catalano
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Rome, Italy
| | - Valeria Panebianco
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Rome, Italy
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30
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Value of bowel preparation techniques for prostate MRI: a preliminary study. Abdom Radiol (NY) 2021; 46:4002-4013. [PMID: 33770222 PMCID: PMC8286932 DOI: 10.1007/s00261-021-03046-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 03/05/2021] [Accepted: 03/09/2021] [Indexed: 12/24/2022]
Abstract
Background Bowel preparation before multiparametric MRI (mpMRI) of the prostate is performed widely, despite contradictory or no evidence for efficacy. Purpose To investigate the value of hyoscine N-butylbromide (HBB), microenema (ME) and ‘dietary restrictions’ (DR) for artifact reduction and image quality (IQ) in mpMRI of the prostate. Study type Retrospective. Population Between 10/2018 and 02/2020 treatment-naïve men (median age, 64.9; range 39.8–87.3) who underwent mpMRI of the prostate were included. The total patient sample comprised of n = 180 patients, who received either HBB, ME, were instructed to adhere to DR, or received a combination of those measures prior to the MR scan. Field strength/sequence T2-weighted imaging (T2w), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced MRI (DCE-MRI) scanned on two 3T systems. Assessment A radiologist specialized in urogenital imaging (R1) and a senior radiology resident (R2) visually assessed IQ parameters on transversal T2w, DWI and ADC maps on a 5-point Likert-like scale. Statistical tests Group comparison between IQ parameters was performed on reader level using Kruskal–Wallis and Mann–Whitney U tests. Binary univariate logistic regression analysis was used to assess independent predictors of IQ. Interrater agreement was assessed using Intraclass Correlation Coefficient (ICC). Results ‘DWI geometric distortion’ was significantly more pronounced in the HBB+/ME−/DR− (R1, 3.6 and R2, 4.0) as compared to the HBB−/ME+/DR− (R1, 4.2 and R2, 4.6) and HBB+/ME+/DR− (R1, 4.3 and R2, 4.7) cohort, respectively. Parameters ‘DWI IQ’ and ‘Whole MRI IQ’ were rated similarly by both readers. ME was a significant independent predictor of ‘good IQ’ for the whole MRI for R1 [b = 1.09, OR 2.98 (95% CI 1.29, 6.87)] and R2 [b = 1.01, OR 2.73 (95% CI 1.24, 6.04)], respectively. Data conclusion ME seems to significantly improve image quality of DWI and the whole mpMRI image set of the prostate. HBB and DR did not have any benefit.
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Giganti F, Kasivisvanathan V, Kirkham A, Punwani S, Emberton M, Moore CM, Allen C. Prostate MRI quality: a critical review of the last 5 years and the role of the PI-QUAL score. Br J Radiol 2021; 95:20210415. [PMID: 34233502 PMCID: PMC8978249 DOI: 10.1259/bjr.20210415] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
There is increasing interest in the use of multiparametric magnetic resonance imaging (mpMRI) in the prostate cancer pathway. The European Association of Urology (EAU) and the British Association of Urological Surgeons (BAUS) now advise mpMRI prior to biopsy, and the Prostate Imaging Reporting and Data System (PI-RADS) recommendations set out the minimal technical requirements for the acquisition of mpMRI of the prostate.The widespread and swift adoption of this technique has led to variability in image quality. Suboptimal image acquisition reduces the sensitivity and specificity of mpMRI for the detection and staging of clinically significant prostate cancer.This critical review outlines the studies aimed at improving prostate MR quality that have been published over the last 5 years. These span from the use of specific MR sequences, magnets and coils to patient preparation. The rates of adherence of prostate mpMRI to technical standards in different cohorts across the world are also discussed.Finally, we discuss the first standardised scoring system (i.e., Prostate Imaging Quality, PI-QUAL) that has been created to evaluate image quality, although further iterations of this score are expected in the future.
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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
| | - Veeru Kasivisvanathan
- Division of Surgery & Interventional Science, University College London, London, UK.,Department of Urology, University College London Hospital NHS Foundation Trust, London, UK
| | - Alex Kirkham
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK
| | - Shonit Punwani
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK.,Centre for Medical Imaging, University College London, London, UK
| | - Mark Emberton
- Division of Surgery & Interventional Science, University College London, London, UK.,Department of Urology, University College London Hospital NHS Foundation Trust, London, UK
| | - Caroline M Moore
- Division of Surgery & Interventional Science, University College London, London, UK.,Department of Urology, University College London Hospital NHS Foundation Trust, London, UK
| | - Clare Allen
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK
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Susceptibility artifacts and PIRADS 3 lesions in prostatic MRI: how often is the dynamic contrast-enhance sequence necessary? Abdom Radiol (NY) 2021; 46:3401-3409. [PMID: 33683430 DOI: 10.1007/s00261-021-03011-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 02/15/2021] [Accepted: 02/20/2021] [Indexed: 10/22/2022]
Abstract
PURPOSE To assess the need of the dynamic contrast-enhanced (DCE) sequence in addition to T2-weighted imaging (T2-WI) and diffusion-weighted imaging (DWI) for the detection of clinically significant prostate cancer in the presence of artifacts associated with rectal gas (which compromise the diffusion assessment) and/or PIRADS 3 lesions. METHODS This retrospective study was approved by the institutional review board; informed consent was not required. Patients referred consecutively over a period of 5 months for elevated PSA underwent multiparametric magnetic resonance imaging (mpMRI). mpMRI was performed using a 3T MRI system without an endorectal coil. The MRI findings were reviewed by two radiologists and were scored according to the Prostate Imaging Reporting and Data System version 2.0 (PI-RADSv2). Any discrepancies were resolved by consensus. For statistical purposes, lesions were classified as PIRADS 1-2, PIRADS 3, or PIRADS 4-5. First, all studies were reviewed using a biparametric assessment (T2-WI + DWI), and the presence or absence of susceptibility artifacts was assessed for each prostate. Subsequently, all images were analyzed using the standard multiparametric approach (T2-WI + DWI + DCE). RESULTS The biparametric evaluation (T2-WI + DWI) showed artifacts (due to the presence of rectal gas or other) in 87 patients (43.5%) and no artifacts in 113 patients (56.5%). In the latter group, 15 patients had peripheral zone (PZ) PIRADS 3 lesions. Thus, a total of 102 patients (51%) had artifacts or PZ PIRADS 3 lesions and therefore required DCE. When evaluating the group of prostates without artifacts, 13.3% of prostates required DCE. A total of 17 (23.9%) PIRADS 4-5 prostate lesions would have not been detected without the use of DCE. CONCLUSION Biparametric evaluation of the prostate revealed some limitation due to the presence of artifacts or PIRADS 3 PZ lesions. Artifacts were present in almost 44% of our patients, but when the DWI was correctly evaluated, only 13.3% of prostates required DCE.
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Brennan DL, Lazarakis S, Lee A, Tan TH, Chin KY, Oon SF. Do antispasmodics or rectal enemas improve image quality on multiparametric prostate MRI? An 'Evidence-Based Practice' review of the literature. Abdom Radiol (NY) 2021; 46:2770-2778. [PMID: 33464364 DOI: 10.1007/s00261-020-02916-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 12/10/2020] [Accepted: 12/12/2020] [Indexed: 01/02/2023]
Abstract
Multiparametric magnetic resonance imaging (mpMRI) of the prostate is increasingly used for the preoperative detection and staging of prostate cancer. Image quality of prostate mpMRI can be significantly degraded by motion related artefact due to bowel peristalsis and susceptibility related artefact, which reduces cancer detection sensitivity. The use of several different methods including anstispasmodic medications and rectal enemas were proposed as potential methods to reduce mpMRI artefacts, but current recommendations in the scientific literature are conflicting and inconsistent. This article seeks to identify the best available evidence to determine which patient preparation method is most effective in improving prostate mpMRI, and provides recommendations for further areas of research. We used the five-step 'Evidence-Based Practice' systematic approach of 'Ask, Search, Appraise, Apply and Evaluate' described by the McMaster University and National Health Service for critical appraisal of topics. We developed a focused clinical question using a PICO format, and performed a primary and secondary literature search through Ovid Medline, Ovid Embase and Cochrane CENTRAL (Wiley). All identified articles were appraised for strength and validity. Seven articles were retrieved which demonstrated conflicting sensitivities and specificities for intravenous hyoscine butylbromide and rectal enema in improving image susceptibility artefact, motion artefact, and anatomic distortion on the T2 or diffusion weighted imaging sequences. Intravenous hysoscine butylbromide is the optimum patient preparation method for improving T2W and DWI image quality in prostate mpMRI. The use of a preparatory rectal enema is not currently recommended, but better quality studies are required.
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Caglic I, Sushentsev N, Shah N, Warren AY, Lamb BW, Barrett T. Comparison of biparametric versus multiparametric prostate MRI for the detection of extracapsular extension and seminal vesicle invasion in biopsy naïve patients. Eur J Radiol 2021; 141:109804. [PMID: 34062473 DOI: 10.1016/j.ejrad.2021.109804] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 05/22/2021] [Accepted: 05/26/2021] [Indexed: 12/31/2022]
Abstract
PURPOSE To compare biparametric MRI (bpMRI) with multiparametric MRI (mpMRI) staging accuracy in assessing extracapsular extension (ECE) and seminal vesicle invasion (SVI). METHOD Biopsy-naïve patients undergoing 3 T-MRI before radical prostatectomy for clinically significant prostate cancer were included in this single-centre retrospective study. Two uroradiologists separately evaluated bpMRI and mpMRI for presence of ECE and SVI using a 5-point Likert scale (1: ECE/SVI highly unlikely, 5: ECE/SVI highly likely). RESULTS 110 men of median age 63 years and PSA 8.5 ng/mL were included. ECE and SVI was confirmed histologically in 71/110 (64.5 %) and 18/110 (16.4 %) patients, respectively. Sensitivity and specificity of bpMRI versus mpMRI for predicting ECE was 59.1 % and 87.2 % versus 66.2 % and 84.6 %, respectively. For SVI detection, the sensitivity and specificity for bpMRI versus mpMRI was 66.7 % and 92.4 % versus 83.3 % and 97.8 %, respectively. At an optimal cut-off Likert score ≥3 for ECE prediction, mpMRI area under the receiver operating curve (AUC) was 0.80 (95 % confidence interval (CI) 0.72-0.87) versus 0.78 (95 % CI 0.69-0.86) for bpMRI (p = 0.52) and for SVI, mpMRI AUC was 0.91 (95 % CI 0.84-0.96) versus 0.86 (95 % CI 0.78-0.92) for bpMRI (p = 0.02), respectively. Inter-reader agreement for both ECE and SVI prediction was substantial, with a marginally higher k-value for mpMRI (k range, 0.67-0.75) than bpMRI (k range, 0.65-0.69). CONCLUSIONS Diagnostic performance of bpMRI and mpMRI was comparable for detection of ECE, however, mpMRI with contrast was superior for SVI detection and improved the inter-reader agreement.
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Affiliation(s)
- Iztok Caglic
- CamPARI Prostate Cancer Group, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK; Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.
| | - Nikita Sushentsev
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.
| | - Nimish Shah
- CamPARI Prostate Cancer Group, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK; Department of Urology, Addenbrooke's Hospital, Cambridge, UK.
| | - Anne Y Warren
- CamPARI Prostate Cancer Group, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK; Department of Pathology, Addenbrooke's Hospital, Cambridge, UK.
| | - Benjamin W Lamb
- CamPARI Prostate Cancer Group, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK; Department of Urology, Addenbrooke's Hospital, Cambridge, UK.
| | - Tristan Barrett
- CamPARI Prostate Cancer Group, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK; Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.
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Giganti F, Kirkham A, Kasivisvanathan V, Papoutsaki MV, Punwani S, Emberton M, Moore CM, Allen C. Understanding PI-QUAL for prostate MRI quality: a practical primer for radiologists. Insights Imaging 2021; 12:59. [PMID: 33932167 PMCID: PMC8088425 DOI: 10.1186/s13244-021-00996-6] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 04/01/2021] [Indexed: 12/19/2022] Open
Abstract
Prostate magnetic resonance imaging (MRI) of high diagnostic quality is a key determinant for either detection or exclusion of prostate cancer. Adequate high spatial resolution on T2-weighted imaging, good diffusion-weighted imaging and dynamic contrast-enhanced sequences of high signal-to-noise ratio are the prerequisite for a high-quality MRI study of the prostate. The Prostate Imaging Quality (PI-QUAL) score was created to assess the diagnostic quality of a scan against a set of objective criteria as per Prostate Imaging-Reporting and Data System recommendations, together with criteria obtained from the image. The PI-QUAL score is a 1-to-5 scale where a score of 1 indicates that all MR sequences (T2-weighted imaging, diffusion-weighted imaging and dynamic contrast-enhanced sequences) are below the minimum standard of diagnostic quality, a score of 3 means that the scan is of sufficient diagnostic quality, and a score of 5 implies that all three sequences are of optimal diagnostic quality. The purpose of this educational review is to provide a practical guide to assess the quality of prostate MRI using PI-QUAL and to familiarise the radiologist and all those involved in prostate MRI with this scoring system. A variety of images are also presented to demonstrate the difference between suboptimal and good prostate MR scans.
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Affiliation(s)
- Francesco Giganti
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK. .,Division of Surgery and Interventional Science, University College London, London, W1W 7TS, UK.
| | - Alex Kirkham
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK
| | - Veeru Kasivisvanathan
- Division of Surgery and Interventional Science, University College London, London, W1W 7TS, UK.,Department of Urology, University College London Hospital NHS Foundation Trust, London, UK
| | | | - Shonit Punwani
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK.,Centre for Medical Imaging, University College London, London, UK
| | - Mark Emberton
- Division of Surgery and Interventional Science, University College London, London, W1W 7TS, UK.,Department of Urology, University College London Hospital NHS Foundation Trust, London, UK
| | - Caroline M Moore
- Division of Surgery and Interventional Science, University College London, London, W1W 7TS, UK.,Department of Urology, University College London Hospital NHS Foundation Trust, London, UK
| | - Clare Allen
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK
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Papoutsaki MV, Allen C, Giganti F, Atkinson D, Dickinson L, Goodman J, Saunders H, Barrett T, Punwani S. Standardisation of prostate multiparametric MRI across a hospital network: a London experience. Insights Imaging 2021; 12:52. [PMID: 33877459 PMCID: PMC8058121 DOI: 10.1186/s13244-021-00990-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 03/22/2021] [Indexed: 12/04/2022] Open
Abstract
OBJECTIVES National guidelines recommend prostate multiparametric (mp) MRI in men with suspected prostate cancer before biopsy. In this study, we explore prostate mpMRI protocols across 14 London hospitals and determine whether standardisation improves diagnostic quality. METHODS An MRI physicist facilitated mpMRI set-up across several regional hospitals, working together with experienced uroradiologists who judged diagnostic quality. Radiologists from the 14 hospitals participated in the assessment and optimisation of prostate mpMRI image quality, assessed according to both PiRADSv2 recommendations and on the ability to "rule in" and/or "rule out" prostate cancer. Image quality and sequence parameters of representative mpMRI scans were evaluated across 23 MR scanners. Optimisation visits were performed to improve image quality, and 2 radiologists scored the image quality pre- and post-optimisation. RESULTS 20/23 mpMRI protocols, consisting of 111 sequences, were optimised by modifying their sequence parameters. Pre-optimisation, only 15% of T2W images were non-diagnostic, whereas 40% of ADC maps, 50% of high b-value DWI and 41% of DCE-MRI were considered non-diagnostic. Post-optimisation, the scores were increased with 80% of ADC maps, 74% of high b-value DWI and 88% of DCE-MRI to be partially or fully diagnostic. T2W sequences were not optimised, due to their higher baseline quality scores. CONCLUSIONS Targeted intervention at a regional level can improve the diagnostic quality of prostate mpMRI protocols, with implications for improving prostate cancer detection rates and targeted biopsies.
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Affiliation(s)
- Marianthi-Vasiliki Papoutsaki
- Centre for Medical Imaging, University College London, 2nd Floor Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK
| | - Clare Allen
- Department of Radiology, University College London Hospital NHS Foundation Trust, Euston Road, London, WC1H 8NJ, UK
| | - Francesco Giganti
- Department of Radiology, University College London Hospital NHS Foundation Trust, Euston Road, London, WC1H 8NJ, UK
- Division of Surgery and Interventional Science, University College London, 43-45 Foley Street, London, W1W 7TS, UK
| | - David Atkinson
- Centre for Medical Imaging, University College London, 2nd Floor Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK
| | - Louise Dickinson
- Department of Radiology, University College London Hospital NHS Foundation Trust, Euston Road, London, WC1H 8NJ, UK
| | - Jacob Goodman
- North East London Cancer Alliance, Tower Hamlets CCG, London, E1 4DG, UK
| | - Helen Saunders
- North Middlesex University Hospital, Sterling Way, London, N18 1QX, UK
| | - Tristan Barrett
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Hills Road, Cambridge, CB2 0SP, UK
| | - Shonit Punwani
- Centre for Medical Imaging, University College London, 2nd Floor Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK.
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Reischauer C, Cancelli T, Malekzadeh S, Froehlich JM, Thoeny HC. How to improve image quality of DWI of the prostate-enema or catheter preparation? Eur Radiol 2021; 31:6708-6716. [PMID: 33758955 PMCID: PMC8379127 DOI: 10.1007/s00330-021-07842-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Revised: 02/12/2021] [Accepted: 02/25/2021] [Indexed: 12/28/2022]
Abstract
OBJECTIVES To compare the impact of laxative enema preparation versus air/gas suction through a small catheter on image quality of prostate DWI. METHODS In this single-center study, 200 consecutive patients (100 in each arm) with either enema or catheter preparation were retrospectively included. Two blinded readers independently assessed aspects of image quality on 5-point Likert scales. Scores were compared between groups and the influence of confounding factors evaluated using multivariable logistic regression. Prostate diameters were compared on DWI and T2-weighted imaging using intraclass correlation coefficients. RESULTS Image quality was significantly higher in the enema group regarding the severity of susceptibility-related artifacts (reader 1: 0.34 ± 0.77 vs. 1.73 ± 1.34, reader 2: 0.38 ± 0.86 vs. 1.76 ± 1.39), the differentiability of the anatomy (reader 1: 3.36 ± 1.05 vs. 2.08 ± 1.31, reader 2: 3.37 ± 1.05 vs. 2.09 ± 1.35), and the overall image quality (reader 1: 3.66 ± 0.77 vs. 2.26 ± 1.33, Reader 2: 3.59 ± 0.87 vs. 2.23 ± 1.38) with almost perfect inter-observer agreement (κ = 0.92-0.95). In the enema group, rectal distention was significantly lower and strongly correlated with the severity of artifacts (reader 1: ρ = 0.79, reader 2: ρ = 0.73). Furthermore, there were significantly fewer substantial image distortions, with odds ratios of 0.051 and 0.084 for the two readers which coincided with a higher agreement of the prostate diameters in the phase-encoding direction (0.96 vs. 0.89). CONCLUSIONS Enema preparation is superior to catheter preparation and yields substantial improvements in image quality. KEY POINTS • Enema preparation is superior to decompression of the rectum using air/gas suction through a small catheter. • Enema preparation markedly improves the image quality of prostate DWI regarding the severity of susceptibility-related artifacts, the differentiability of the anatomy, and the overall image quality and considerably reduces substantial artifacts that may impair a reliable diagnosis.
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Affiliation(s)
- Carolin Reischauer
- Department of Medicine, University of Fribourg, Chemin du Musée 8, 1700, Fribourg, CH, Switzerland.
- Department of Radiology, Cantonal Hospital Fribourg, Fribourg, Switzerland.
| | - Timmy Cancelli
- Department of Radiology, Cantonal Hospital Fribourg, Fribourg, Switzerland
| | - Sonaz Malekzadeh
- Department of Medicine, University of Fribourg, Chemin du Musée 8, 1700, Fribourg, CH, Switzerland
- Department of Radiology, Cantonal Hospital Fribourg, Fribourg, Switzerland
| | - Johannes M Froehlich
- Department of Medicine, University of Fribourg, Chemin du Musée 8, 1700, Fribourg, CH, Switzerland
- Department of Radiology, Cantonal Hospital Fribourg, Fribourg, Switzerland
| | - Harriet C Thoeny
- Department of Medicine, University of Fribourg, Chemin du Musée 8, 1700, Fribourg, CH, Switzerland
- Department of Radiology, Cantonal Hospital Fribourg, Fribourg, Switzerland
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38
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Franiel T, Asbach P, Beyersdorff D, Blondin D, Kaufmann S, Mueller-Lisse UG, Quentin M, Rödel S, Röthke M, Schlemmer HP, Schimmöller L. mpMRI of the Prostate (MR-Prostatography): Updated Recommendations of the DRG and BDR on Patient Preparation and Scanning Protocol. ROFO-FORTSCHR RONTG 2021; 193:763-777. [PMID: 33735931 DOI: 10.1055/a-1406-8477] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
The Working Group Uroradiology and Urogenital Diagnosis of the German Roentgen Society (DRG) revised and updated the recommendations for preparation and scanning protocol of the multiparametric MRI of the Prostate in a consensus process and harmonized it with the managing board of German Roentgen Society and Professional Association of the German Radiologist (BDR e. V.). These detailed recommendation define the referenced "validated quality standards" of the German S3-Guideline Prostate Cancer and describe in detail the topic 1. anamnestic datas, 2. termination of examinations and preparation of examinations, 3. examination protocol and 4. MRI-(in-bore)-biopsy. KEY POINTS:: · The recommendations for preparation and scanning protocol of the multiparametric MRI of the Prostate were revised and updated in a consensus process and harmonized with the managing board of German Roentgen Society (DRG) and Professional Asssociation of the German Radiologist (BDR).. · Detailed recommendations are given for topic 1. anamnestic datas, 2. termination and preparation of examinations, 3. examination protocoll and 4. MRI-(in-bore)-biopsy.. · These recommendations define the referenced "validated quality standards" of the German S3-Guideline Prostate Cancer.. CITATION FORMAT: · Franiel T, Asbach P, Beyersdorff D et al. mpMRI of the Prostate (MR-Prostatography): Updated Recommendations of the DRG and BDR on Patient Preparation and Examination Protocol. Fortschr Röntgenstr 2021; 193: 763 - 776.
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Affiliation(s)
- Tobias Franiel
- Institut für diagnostische und interventionelle Radiologie, Universitätsklinikum Jena, Deutschland
| | - Patrick Asbach
- Klinik für Radiologie, Charité Campus Benjamin Franklin, Charité-Universitätsmedizin Berlin, Deutschland
| | - Dirk Beyersdorff
- Klinik und Poliklinik für Diagnostische und Interventionelle Radiologie und Nuklearmedizin, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Dirk Blondin
- Klinik für Radiologie, Gefäßradiologie und Nuklearmedizin, Städtische Kliniken Mönchengladbach GmbH Elisabeth-Krankenhaus Rheydt, Mönchengladbach, Germany.,Klinik für Radiologie, Gefäßradiologie und Nuklearmedizin, Städtische Kliniken Mönchengladbach, Germany
| | - Sascha Kaufmann
- Institut für Diagnostische und Interventionelle Radiologie, Siloah St. Trudpert Klinikum, Pforzheim, Deutschland
| | | | - Michael Quentin
- Centrum für Diagnostik und Therapie GmbH, Medizinisches Versorgungszentrum CDT Strahleninstitut GmbH, Köln, Germany
| | - Stefan Rödel
- Radiologische Klinik, Städtisches Klinikum Dresden, Germany
| | - Matthias Röthke
- Conradia Radiologie und Nuklearmedizin, Conradia Hamburg MVZ GmbH, Hamburg, Germany
| | | | - Lars Schimmöller
- Institut für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Düsseldorf, Düsseldorf, Germany
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Sackett J, Shih JH, Reese SE, Brender JR, Harmon SA, Barrett T, Coskun M, Madariaga M, Marko J, Law YM, Turkbey EB, Mehralivand S, Sanford T, Lay N, Pinto PA, Wood BJ, Choyke PL, Turkbey B. Quality of Prostate MRI: Is the PI-RADS Standard Sufficient? Acad Radiol 2021; 28:199-207. [PMID: 32143993 PMCID: PMC8459209 DOI: 10.1016/j.acra.2020.01.031] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2019] [Revised: 01/21/2020] [Accepted: 01/22/2020] [Indexed: 12/22/2022]
Abstract
RATIONALE AND OBJECTIVE The Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) published a set of minimum technical standards (MTS) to improve image quality and reduce variability in multiparametric prostate MRI. The effect of PIRADSv2 MTS on image quality has not been validated. We aimed to determine whether adherence to PI-RADSv2 MTS improves study adequacy and perceived quality. MATERIALS AND METHODS Sixty-two prostate MRI examinations including T2 weighted (T2W) and diffusion weighted image (DWI) consecutively referred to our center from 62 different institutions within a 12-month period (September 2017 to September 2018) were included. Six readers assessed images as adequate or inadequate for use in PCa detection and a numerical image quality ranking was given using a 1-5 scale. The PI-RADSv2 MTS were synthesized into sets of seven and 10 rules for T2W and DWI, respectively. Image adherence was assessed using Digital Imaging and Communications in Medicine (DICOM) metadata. Statistical analysis of survey results and image adherence was performed based on reader quality scoring (Kendall Rank tau-b) and reader adequate scoring (Wilcoxon test for association) for T2 and DWI quality assessment. RESULTS Out of 62 images, 52 (83%) T2W and 38 (61%) DWIs were rated to be adequate by a majority of readers. Reader adequacy scores showed no significant association with adherence to PI-RADSv2. There was a weak (tau-b = 0.22) but significant (p value = 0.01) correlation between adherence to PIRADSv2 MTS and image quality for T2W. Studies following all PI-RADSv2 T2W rules achieved a higher median average quality score (3.58 for 7/7 vs. 3.0 for <7/7, p = 0.012). No statistical relationship with PI-RADSv2 MTS adherence and DWI quality was found. CONCLUSION Among 62 sites performing prostate MRI, few were considered of high quality, but the majority were considered adequate. DWI showed considerably lower rates of adequate studies in the sample. Adherence to PI-RADSv2 MTS did not increase the likelihood of having a qualitatively adequate T2W or DWI.
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Affiliation(s)
- Jonathan Sackett
- Molecular Imaging Program, National Cancer Institute, NIH, Bethesda, MD, USA; Loma Linda University School of Medicine, Loma Linda, CA, USA
| | - Joanna H Shih
- Division of Cancer Treatment and Diagnosis: Biometric Research Program, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Sarah E Reese
- General Dynamics Information Technology, Falls Church, VA, USA
| | - Jeffrey R Brender
- Radiation Biology Branch, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Stephanie A Harmon
- Molecular Imaging Program, National Cancer Institute, NIH, Bethesda, MD, USA; Leidos Biomedical Research, Inc., NCI Campus at Frederick, Clinical Research Directorate/Clinical Monitoring Research Program, Bethesda, MD, USA
| | - Tristan Barrett
- University of Cambridge School of Clinical Medicine, Cambridge UK
| | - Mehmet Coskun
- Department of Radiology, Dr. Behcet Uz Child Disease and Pediatric Surgery Training and Research Hospital, University of Health Sciences, izmir, Turkey
| | | | - Jamie Marko
- Department of Radiology, Clinical Center, NIH, Bethesda, MD, USA
| | - Yan Mee Law
- Department of Diagnostic Radiology, Singapore General Hospital, Singapore
| | - Evrim B Turkbey
- Department of Radiology, Clinical Center, NIH, Bethesda, MD, USA
| | - Sherif Mehralivand
- Molecular Imaging Program, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Thomas Sanford
- Molecular Imaging Program, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Nathan Lay
- Molecular Imaging Program, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Peter A Pinto
- Urologic Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Bradford J Wood
- Department of Radiology, Clinical Center, NIH, Bethesda, MD, USA; Center for Interventional Oncology, National Cancer Institute, Bethesda, MD, USA
| | - Peter L Choyke
- Molecular Imaging Program, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Baris Turkbey
- Molecular Imaging Program, National Cancer Institute, NIH, Bethesda, MD, USA.
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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.
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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
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Eusebi L, Carpagnano FA, Sortino G, Bartelli F, Guglielmi G. Prostate Multiparametric MRI: Common Pitfalls in Primary Diagnosis and How to Avoid Them. CURRENT RADIOLOGY REPORTS 2021. [DOI: 10.1007/s40134-021-00378-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Abstract
Purpose of Review
To provide the radiologist with basic knowledge about normal and abnormal findings in the prostatic mp-MRI, taking a look at the possible diagnostic pitfalls commonly seen in daily clinical practice, allowing him to recognize and consequently avoid them.
Recent Findings
Prostate mp-MRI has now become commonly used in most diagnostic imaging centers, as a precise, accurate and above all non-invasive tool, useful in the diagnosis, staging and follow-up of prostate diseases, first of all prostatic carcinoma. For this reason, it is important to take into account the existence of numerous possible anatomic and pathologic processes which can mimick or masquerade as prostate cancer.
Summary
Through the combination of anatomical (T2WI) and functional sequences (DWI/ADC and DCE), the mp-MRI of the prostate provides all the information necessary for a correct classification of patients with prostate disease, cancer in particular. It is not uncommon, however, for the radiologist to make errors in the interpretation of imaging due to conditions, pathological or otherwise, that mimic prostate cancer and that, consequently, affect the diagnostic/therapeutic process of patients. The strategy, and what this pictorial review aims at, is to learn to recognize the potential pitfalls of the prostatic mp-MRI and avoid them.
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Coskun M, Mehralivand S, Shih JH, Merino MJ, Wood BJ, Pinto PA, Barrett T, Choyke PL, Turkbey B. Impact of bowel preparation with Fleet's™ enema on prostate MRI quality. Abdom Radiol (NY) 2020; 45:4252-4259. [PMID: 32211948 DOI: 10.1007/s00261-020-02487-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
AIM To investigate the effects of cleansing Fleet's™ enema (FE) on rectal distention and image quality of diffusion-weighted imaging (DWI) in prostate magnetic resonance imaging (MRI). METHODS This study included 117 prospectively accrued active surveillance patients who underwent prostate MRI both without (prep-) and with bowel preparation consisting of FE (prep+) obtained within 12 months of each other. The anterior-posterior (AP) diameter of the rectum, degree of perceived distention in the rectum and image quality scores were assessed by two independent readers for both (prep- and prep+) scans. DWI distortion was assessed quantitatively using the degree of anatomic mismatches between images obtained at different b values and the T2-weighted MRI. DWI artifact was qualitatively scored based on the presence of blurring, poor signal-to-noise, and artifact lines. The difference in rectal AP diameters between the two methods was tested by the paired Wilcoxon rank test. Stuart Maxell test was used in comparing rectal distention, DWI distortion, and artifact. Reader agreement was estimated by kappa statistics. p values < 0.05 were considered statistically significant. RESULTS Mean rectal AP diameter was significantly larger in prep- compared with prep+ scans (p = 0.002). Subjective scores demonstrated inter-reader variability. For instance, the rectal distention score was significantly lower in prep+ for reader 2 (p < 0.001) whereas it was not significant for reader 1 (p = 0.09). Reader 2 also found significant improvement in DWI distortion (p = 0.02) in prep+ scans. There was no significant difference between prep- and prep+ in DWI distortion and artifacts for reader 1 (p = 0.17 and p = 0.49, respectively), or DWI artifacts for reader 2 (p = 0.55). Kappa scores were moderate for rectal distension, but weak for DWI distortion, and artifacts. CONCLUSION Bowel preparation with enema prior to prostate MRI may diminish rectal gas but has modest effects on DWI distortion and overall image quality. The value of bowel prep is not conclusively validated in this study.
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Affiliation(s)
- Mehmet Coskun
- Department of Radiology, Health Science University Dr. Behçet Uz Child Disease and Surgery Training and Research Hospital, Izmir, Turkey
| | - Sherif Mehralivand
- Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Joanna H Shih
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Maria J Merino
- Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Bradford J Wood
- Center for Interventional Oncology, Clinical Center, National Institutes of Health, Bethesda, MD, USA
| | - Peter A Pinto
- Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Tristan Barrett
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
- CamPARI Clinic, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK
| | - Peter L Choyke
- Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Baris Turkbey
- Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
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Plodeck V, Radosa CG, Hübner HM, Baldus C, Borkowetz A, Thomas C, Kühn JP, Laniado M, Hoffmann RT, Platzek I. Rectal gas-induced susceptibility artefacts on prostate diffusion-weighted MRI with epi read-out at 3.0 T: does a preparatory micro-enema improve image quality? Abdom Radiol (NY) 2020; 45:4244-4251. [PMID: 32500236 PMCID: PMC8260527 DOI: 10.1007/s00261-020-02600-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 05/20/2020] [Accepted: 05/26/2020] [Indexed: 12/21/2022]
Abstract
PURPOSE To assess whether the application of a preparatory micro-enema reduces gas-induced susceptibility artefacts on diffusion-weighted MRI of the prostate. METHODS 114 consecutive patients who received multiparametric 3 T MRI of the prostate at our institution were retrospectively enrolled. 63 patients self-administered a preparatory micro-enema prior to imaging, and 51 patients underwent MRI without bowel preparation. Two blinded readers independently reviewed the diffusion-weighted sequences regarding gas-induced artefacts. The presence/severity of artefacts was scored ranging from 0 (no artefact) to 3 (severe artefact). A score ≥ 2 was considered a clinically relevant artefact. Maximum rectal width at the level of the prostate was correlated with the administration of a micro-enema. Scores were compared between the scans performed with and without bowel preparation using univariable and multivariable logistic regression, taking into account potential confounding factors (age and prostate volume). RESULTS Significantly less artefacts were found on diffusion-weighted sequences after the administration of a micro-enema shortly prior to MR imaging. Clinically relevant artefacts were found in 10% in the patient group after enema, in 41% without enema. If present, artefacts were also significantly less severe. Mean severity score was 0.3 (enema administered) and 1.2 (no enema), and odds ratio was 0.137 (p < 0.0001) in univariable ordinal logistic regression. Inter-observer agreement was excellent (κ 0.801). CONCLUSION The use of a preparatory micro-enema prior to 3 T multiparametric prostate MRI significantly reduces both the incidence and severity of gas-induced artefacts on diffusion-weighted sequences and thus improves image quality.
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Affiliation(s)
- Verena Plodeck
- Institut und Poliklinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Carl Gustav Carus Dresden, Fetscherstrasse 74, 01307, Dresden, Deutschland.
| | - Christoph Georg Radosa
- Institut und Poliklinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Carl Gustav Carus Dresden, Fetscherstrasse 74, 01307, Dresden, Deutschland
| | - Hans-Martin Hübner
- Institut und Poliklinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Carl Gustav Carus Dresden, Fetscherstrasse 74, 01307, Dresden, Deutschland
| | - Christian Baldus
- Institut und Poliklinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Carl Gustav Carus Dresden, Fetscherstrasse 74, 01307, Dresden, Deutschland
| | - Angelika Borkowetz
- Klinik und Poliklinik für Urologie, Universitätsklinikum Carl Gustav Carus Dresden, Fetscherstrasse 74, 01307, Dresden, Deutschland
| | - Christian Thomas
- Klinik und Poliklinik für Urologie, Universitätsklinikum Carl Gustav Carus Dresden, Fetscherstrasse 74, 01307, Dresden, Deutschland
| | - Jens-Peter Kühn
- Institut und Poliklinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Carl Gustav Carus Dresden, Fetscherstrasse 74, 01307, Dresden, Deutschland
| | - Michael Laniado
- Institut und Poliklinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Carl Gustav Carus Dresden, Fetscherstrasse 74, 01307, Dresden, Deutschland
| | - Ralf-Thorsten Hoffmann
- Institut und Poliklinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Carl Gustav Carus Dresden, Fetscherstrasse 74, 01307, Dresden, Deutschland
| | - Ivan Platzek
- Institut und Poliklinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Carl Gustav Carus Dresden, Fetscherstrasse 74, 01307, Dresden, Deutschland
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Muglia VF, Vargas HA. Doctor, a patient is on the phone asking about the endorectal coil! Abdom Radiol (NY) 2020; 45:4003-4011. [PMID: 32300836 DOI: 10.1007/s00261-020-02528-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
The question referred to in the title of this article is a relatively common situation when performing prostate MRI in some healthcare settings. Moreover, the answer is not always straightforward. The decisions on type of receiver coil for prostate MRI and whether or not an endorectal coil (ERC) should be used is based on several factors. These relate to the patient (e.g., body habitus, presence of metallic devices in the pelvis), the focus of the exam (diagnosis, staging, recurrence), and characteristics of the MRI system (e.g., magnetic field strength and hardware components including coil design and number of elements/channels available in the surface coil). Historically, the combined use of an ERC and a surface coil was the optimal combination for maximizing the signal-to-noise ratio (SNR), particularly for low-strength magnetic fields (1.5T). However, there are several disadvantages associated with the use of an ERC, and several studies have advocated equivalent clinical performance of modern MRI systems for diagnosis and staging of prostate cancer (PCa), either with ERC or surface alone. Accordingly, there is a wide variation in the precise imaging technique across institutions. This article focuses on the most relevant aspects of the decision of whether to use an ERC for PCa MR imaging.
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Affiliation(s)
- Valdair Francisco Muglia
- Department of Medical Images, Radiation Therapy and Oncohematology, Ribeirao Preto Medical School, Hospital Clinicas, University of São Paulo, Av. Bandeirantes 3900, Campus Monte Alegre, Ribeirão Prêto, 14049-900, Brazil.
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Sushentsev N, Kaggie JD, Buonincontri G, Schulte RF, Graves MJ, Gnanapragasam VJ, Barrett T. The effect of gadolinium-based contrast agent administration on magnetic resonance fingerprinting-based T 1 relaxometry in patients with prostate cancer. Sci Rep 2020; 10:20475. [PMID: 33235229 PMCID: PMC7686305 DOI: 10.1038/s41598-020-77331-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 11/03/2020] [Indexed: 12/16/2022] Open
Abstract
Magnetic resonance fingerprinting (MRF) is a rapidly developing fast quantitative mapping technique able to produce multiple property maps with reduced sensitivity to motion. MRF has shown promise in improving the diagnosis of clinically significant prostate cancer but requires further validation as part of a prostate multiparametric (mp) MRI protocol. mpMRI protocol mandates the inclusion of dynamic contrast enhanced (DCE) imaging, known for its significant T1 shortening effect. MRF could be used to measure both pre- and post-contrast T1 values, but its utility must be assessed. In this proof-of-concept study, we sought to evaluate the variation in MRF T1 measurements post gadolinium-based contrast agent (GBCA) injection and the utility of such T1 measurements to differentiate peripheral and transition zone tumours from normal prostatic tissue. We found that the T1 variation in all tissues increased considerably post-GBCA following the expected significant T1 shortening effect, compromising the ability of MRF T1 to identify transition zone lesions. We, therefore, recommend performing MRF T1 prior to DCE imaging to maintain its benefit for improving detection of both peripheral and transition zone lesions while reducing additional scanning time. Demonstrating the effect of GBCA on MRF T1 relaxometry in patients also paves the way for future clinical studies investigating the added value of post-GBCA MRF in PCa, including its dynamic analysis as in DCE-MRF.
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Affiliation(s)
- Nikita Sushentsev
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
| | - Joshua D Kaggie
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
| | | | | | - Martin J Graves
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
| | - Vincent J Gnanapragasam
- Department of Urology, Addenbrooke's Hospital, Cambridge, UK
- Academic Urology Group, Department of Surgery and Oncology, University of Cambridge, Cambridge, UK
- Cambridge Urology Translational Research and Clinical Trials Office, University of Cambridge, Cambridge, UK
| | - Tristan Barrett
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK.
- CamPARI Prostate Cancer Group, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.
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PI-RADS Version 2.1: A Critical Review, From the AJR Special Series on Radiology Reporting and Data Systems. AJR Am J Roentgenol 2020; 216:20-32. [PMID: 32997518 DOI: 10.2214/ajr.20.24495] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
PI-RADS version 2.1 updates the technical parameters for multiparametric MRI (mpMRI) of the prostate and revises the imaging interpretation criteria while maintaining the framework introduced in version 2. These changes have been considered an improvement, although some issues remain unresolved, and new issues have emerged. Areas for improvement discussed in this review include the need for more detailed mpMRI protocols with optimization for 1.5-T and 3-T systems; lack of validation of revised transition zone interpretation criteria and need for clarifications of the revised DWI and dynamic contrast-enhanced imaging criteria and central zone (CZ) assessment; the need for systematic evaluation and reporting of background changes in signal intensity in the prostate that can negatively affect cancer detection; creation of a new category for lesions that do not fit into the PI-RADS assessment categories (i.e., PI-RADS M category); inclusion of quantitative parameters beyond size to evaluate lesion aggressiveness; adjustments to the structured report template, including standardized assessment of the risk of extraprostatic extension; development of parameters for image quality and performance control; and suggestions for expansion of the system to other indications (e.g., active surveillance and recurrence).
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Kaye EA, Aherne EA, Duzgol C, Häggström I, Kobler E, Mazaheri Y, Fung MM, Zhang Z, Otazo R, Vargas HA, Akin O. Accelerating Prostate Diffusion-weighted MRI Using a Guided Denoising Convolutional Neural Network: Retrospective Feasibility Study. Radiol Artif Intell 2020; 2:e200007. [PMID: 33033804 DOI: 10.1148/ryai.2020200007] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 04/29/2020] [Accepted: 05/06/2020] [Indexed: 02/02/2023]
Abstract
PURPOSE To investigate the feasibility of accelerating prostate diffusion-weighted imaging (DWI) by reducing the number of acquired averages and denoising the resulting image using a proposed guided denoising convolutional neural network (DnCNN). MATERIALS AND METHODS Raw data from the prostate DWI scans were retrospectively gathered between July 2018 and July 2019 from six single-vendor MRI scanners. There were 103 datasets used for training (median age, 64 years; interquartile range [IQR], 11), 15 for validation (median age, 68 years; IQR, 12), and 37 for testing (median age, 64 years; IQR, 12). High b-value diffusion-weighted (hb DW) data were reconstructed into noisy images using two averages and reference images using all 16 averages. A conventional DnCNN was modified into a guided DnCNN, which uses the low b-value DW image as a guidance input. Quantitative and qualitative reader evaluations were performed on the denoised hb DW images. A cumulative link mixed regression model was used to compare the readers' scores. The agreement between the apparent diffusion coefficient (ADC) maps (denoised vs reference) was analyzed using Bland-Altman analysis. RESULTS Compared with the original DnCNN, the guided DnCNN produced denoised hb DW images with higher peak signal-to-noise ratio (32.79 ± 3.64 [standard deviation] vs 33.74 ± 3.64), higher structural similarity index (0.92 ± 0.05 vs 0.93 ± 0.04), and lower normalized mean square error (3.9% ± 10 vs 1.6% ± 1.5) (P < .001 for all). Compared with the reference images, the denoised images received higher image quality scores from the readers (P < .0001). The ADC values based on the denoised hb DW images were in good agreement with the reference ADC values (mean ADC difference ranged from -0.04 to 0.02 × 10-3 mm2/sec). CONCLUSION Accelerating prostate DWI by reducing the number of acquired averages and denoising the resulting image using the proposed guided DnCNN is technically feasible. Supplemental material is available for this article. © RSNA, 2020.
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Affiliation(s)
- Elena A Kaye
- Departments of Medical Physics (E.A.K., I.H., Y.M., R.O.), Radiology (E.A.A., C.D., R.O., H.A.V., O.A.), and Epidemiology and Biostatistics (Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room S1212B, New York, NY 10065; Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria (E.K.); and MR Applications & Workflow Team, GE Healthcare, Chicago, Ill (M.M.F.)
| | - Emily A Aherne
- Departments of Medical Physics (E.A.K., I.H., Y.M., R.O.), Radiology (E.A.A., C.D., R.O., H.A.V., O.A.), and Epidemiology and Biostatistics (Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room S1212B, New York, NY 10065; Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria (E.K.); and MR Applications & Workflow Team, GE Healthcare, Chicago, Ill (M.M.F.)
| | - Cihan Duzgol
- Departments of Medical Physics (E.A.K., I.H., Y.M., R.O.), Radiology (E.A.A., C.D., R.O., H.A.V., O.A.), and Epidemiology and Biostatistics (Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room S1212B, New York, NY 10065; Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria (E.K.); and MR Applications & Workflow Team, GE Healthcare, Chicago, Ill (M.M.F.)
| | - Ida Häggström
- Departments of Medical Physics (E.A.K., I.H., Y.M., R.O.), Radiology (E.A.A., C.D., R.O., H.A.V., O.A.), and Epidemiology and Biostatistics (Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room S1212B, New York, NY 10065; Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria (E.K.); and MR Applications & Workflow Team, GE Healthcare, Chicago, Ill (M.M.F.)
| | - Erich Kobler
- Departments of Medical Physics (E.A.K., I.H., Y.M., R.O.), Radiology (E.A.A., C.D., R.O., H.A.V., O.A.), and Epidemiology and Biostatistics (Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room S1212B, New York, NY 10065; Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria (E.K.); and MR Applications & Workflow Team, GE Healthcare, Chicago, Ill (M.M.F.)
| | - Yousef Mazaheri
- Departments of Medical Physics (E.A.K., I.H., Y.M., R.O.), Radiology (E.A.A., C.D., R.O., H.A.V., O.A.), and Epidemiology and Biostatistics (Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room S1212B, New York, NY 10065; Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria (E.K.); and MR Applications & Workflow Team, GE Healthcare, Chicago, Ill (M.M.F.)
| | - Maggie M Fung
- Departments of Medical Physics (E.A.K., I.H., Y.M., R.O.), Radiology (E.A.A., C.D., R.O., H.A.V., O.A.), and Epidemiology and Biostatistics (Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room S1212B, New York, NY 10065; Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria (E.K.); and MR Applications & Workflow Team, GE Healthcare, Chicago, Ill (M.M.F.)
| | - Zhigang Zhang
- Departments of Medical Physics (E.A.K., I.H., Y.M., R.O.), Radiology (E.A.A., C.D., R.O., H.A.V., O.A.), and Epidemiology and Biostatistics (Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room S1212B, New York, NY 10065; Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria (E.K.); and MR Applications & Workflow Team, GE Healthcare, Chicago, Ill (M.M.F.)
| | - Ricardo Otazo
- Departments of Medical Physics (E.A.K., I.H., Y.M., R.O.), Radiology (E.A.A., C.D., R.O., H.A.V., O.A.), and Epidemiology and Biostatistics (Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room S1212B, New York, NY 10065; Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria (E.K.); and MR Applications & Workflow Team, GE Healthcare, Chicago, Ill (M.M.F.)
| | - Hebert A Vargas
- Departments of Medical Physics (E.A.K., I.H., Y.M., R.O.), Radiology (E.A.A., C.D., R.O., H.A.V., O.A.), and Epidemiology and Biostatistics (Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room S1212B, New York, NY 10065; Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria (E.K.); and MR Applications & Workflow Team, GE Healthcare, Chicago, Ill (M.M.F.)
| | - Oguz Akin
- Departments of Medical Physics (E.A.K., I.H., Y.M., R.O.), Radiology (E.A.A., C.D., R.O., H.A.V., O.A.), and Epidemiology and Biostatistics (Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Room S1212B, New York, NY 10065; Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria (E.K.); and MR Applications & Workflow Team, GE Healthcare, Chicago, Ill (M.M.F.)
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Mason BR, Eastham JA, Davis BJ, Mynderse LA, Pugh TJ, Lee RJ, Ippolito JE. Current Status of MRI and PET in the NCCN Guidelines for Prostate Cancer. J Natl Compr Canc Netw 2020; 17:506-513. [PMID: 31085758 DOI: 10.6004/jnccn.2019.7306] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Accepted: 03/29/2019] [Indexed: 11/17/2022]
Abstract
Prostate cancer (PCa) represents a significant source of morbidity and mortality for men in the United States, with approximately 1 in 9 being diagnosed with PCa in their lifetime. The role of imaging in the evaluation of men with PCa has evolved and currently plays a central role in diagnosis, treatment planning, and evaluation of recurrence. Appropriate use of multiparametric MRI (mpMRI) and MRI-guided transrectal ultrasound (MR-TRUS) biopsy increases the detection of clinically significant PCa while decreasing the detection of clinically insignificant PCa. This process may help patients with clinically insignificant PCa avoid the adverse effects of unnecessary therapy. In the setting of a known PCa, patients with low-grade disease can be observed using active surveillance, which often includes a combination of prostate-specific antigen (PSA) testing, serial mpMRI, and, if indicated, follow-up systematic and targeted TRUS-guided tissue sampling. mpMRI can provide important information in the posttreatment setting, but PET/CT is creating a paradigm shift in imaging standards for patients with locally recurrent and metastatic PCa. This article examines the strengths and limitations of mpMRI for initial PCa diagnosis, active surveillance, recurrent disease evaluation, and image-guided biopsies, and the use of PET/CT imaging in men with recurrent PCa. The goal of this review is to provide a rational basis for current NCCN Clinical Practice Guidelines in Oncology for PCa as they pertain to the use of these advanced imaging modalities.
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Affiliation(s)
- Brandon R Mason
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - James A Eastham
- Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | | | | | - Thomas J Pugh
- Department of Radiation Oncology, University of Colorado, Denver, Colorado; and
| | - Richard J Lee
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Joseph E Ippolito
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
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Abstract
Multiparametric MRI (mpMRI) of the prostate has evolved to be an integral component for the diagnosis, risk stratification, staging, and targeting of prostate cancer. However, anatomic and histologic mimics of prostate cancer on mpMRI exist. Anatomic feature that mimic prostate cancer on mpMRI include anterior fibromuscular stroma, normal central zone, periprostatic venous plexus, and thickened surgical capsule (transition zone pseudocapsule). Benign conditions such as post-biopsy hemorrhage, prostatitis or inflammation, focal prostate atrophy, benign prostatic hyperplasia nodules, and prostatic calcifications can also mimic prostate cancer on mpMRI. Technical challenges and other pitfalls such as image distortion, motion artifacts, and endorectal coil placements can also limit the efficacy of mpMRI. Knowledge of prostate anatomy, location of the lesion and its imaging features on different sequences, and being familiar with the common pitfalls are critical for the radiologists who interpret mpMRI. Therefore, this article reviews the pitfalls (anatomic structures and technical challenges) and benign lesions or abnormalities that may mimic prostate cancer on mpMRI and how to interpret them.
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50
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What You Need to Know Before Reading Multiparametric MRI for Prostate Cancer. AJR Am J Roentgenol 2020; 214:1211-1219. [PMID: 32255689 DOI: 10.2214/ajr.19.22751] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE. Multiparametric MRI (mpMRI) has become the main imaging modality for the detection, localization, and local staging of prostate cancer over the past decade. For radiologists to achieve consistent and reproducible reporting of prostate mpMRI, a comprehensive evaluation of the gland including detailed knowledge of anatomy, pathology, and clinical data is required. This article familiarizes radiologists with common pitfalls and conditions that affect mpMRI performance during readouts. CONCLUSION. Consistent, accurate, and reproducible reporting of prostate mpMRI is vital. Additionally, radiologists should be aware of common diagnostic pitfalls that can hinder mpMRI performance.
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