Physically implausible signals as a quantitative quality assessment metric in prostate diffusion-weighted MR imaging.
Diffusion-weighted MRI
Multiparametric MRI
Prostate DWI
Quality assessment
Quantitative measurement
Journal
Abdominal radiology (New York)
ISSN: 2366-0058
Titre abrégé: Abdom Radiol (NY)
Pays: United States
ID NLM: 101674571
Informations de publication
Date de publication:
07 2022
07 2022
Historique:
received:
13
12
2021
accepted:
26
04
2022
revised:
20
04
2022
pubmed:
19
5
2022
medline:
28
6
2022
entrez:
18
5
2022
Statut:
ppublish
Résumé
To provide a quantitative assessment of diffusion-weighted MR images of the prostate through identification of PIDS which clearly represents artifacts in the data. We calculated the percentage and distribution of PIDS in prostate DWI and compare the amount of PIDS between mpMRI images obtained with and without an endorectal coil. This IRB approved retrospective study (from 03/03/2014 to 03/10/2020), included 40 patients scanned with endorectal coil (ERC) and 40 without ER coil (NERC). PIDS contains any voxel where: (1) the diffusion signal increases despite an increase in b-value; and/or (2) apparent diffusion coefficient (ADC) is more than 3.0 μm 80 patients (58 ± 8 years old, 80 men) were evaluated. The percentage of voxels exhibiting PIDS was 17.1 ± 8.1% for the ERC cohort and 22.2 ± 15.5% for the NERC cohort. PIDS for NERC versus ERC were not significantly different (p = 0.14). The apex and base showed similar percentages of PIDS in ERC (p = 0.30) and NERC (p = 0.86). The mid (13.8 ± 8.6%) in ERC showed lower values (p = 0.02) of PIDS compared to apex (19.9 ± 11.1%) and base (17.5 ± 8.3%). PIDS maps provide a spatially resolved quantitative quality assessment for prostate DWI. Average PIDS over the entire prostate were similar for the ERC and NERC cohorts, and did not differ significantly across prostate zones. However, for many of the patients, PIDS was focally much higher in specific prostate zones. PIDS assessment can guide Radiologist's evaluation of images and the development of improved DWI sequences.
Identifiants
pubmed: 35583823
doi: 10.1007/s00261-022-03542-0
pii: 10.1007/s00261-022-03542-0
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
2500-2508Subventions
Organisme : NIH HHS
ID : R01 CA227036
Pays : United States
Organisme : NIH HHS
ID : R01 CA17280
Pays : United States
Organisme : NIH HHS
ID : R01 CA227036
Pays : United States
Organisme : NIH HHS
ID : R01 CA17280
Pays : United States
Organisme : NCI NIH HHS
ID : R41 CA244056
Pays : United States
Organisme : NIH HHS
ID : S10 OD018448
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA014599
Pays : United States
Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Références
Schoots IG, Padhani AR. Delivering Clinical impacts of the MRI diagnostic pathway in prostate cancer diagnosis. Abdom Radiol. 2020;45(12):4012-4022. https://doi.org/10.1007/s00261-020-02547-x
doi: 10.1007/s00261-020-02547-x
Westphalen AC. Introduction to the special issue: Prostate Cancer Update. Abdom Radiol. 2020;45(12):3947-3947. https://doi.org/10.1007/s00261-020-02861-4
doi: 10.1007/s00261-020-02861-4
de Rooij M, Hamoen EHJ, Fütterer JJ, Barentsz JO, Rovers MM. Accuracy of Multiparametric MRI for Prostate Cancer Detection: A Meta-Analysis. American Journal of Roentgenology. 2014;202(2):343-351. https://doi.org/10.2214/AJR.13.11046
doi: 10.2214/AJR.13.11046
pubmed: 24450675
Giganti F, Allen C, Emberton M, Moore CM, Kasivisvanathan V, PRECISION study group. Prostate Imaging Quality (PI-QUAL): A New Quality Control Scoring System for Multiparametric Magnetic Resonance Imaging of the Prostate from the PRECISION trial. Eur Urol Oncol. 2020;3(5):615–619. https://doi.org/10.1016/j.euo.2020.06.007
Sadinski M, Medved M, Karademir I, et al. Short-term reproducibility of apparent diffusion coefficient estimated from diffusion-weighted MRI of the prostate. Abdom Imaging. 2015;40(7):2523-2528. https://doi.org/10.1007/s00261-015-0396-x
doi: 10.1007/s00261-015-0396-x
pubmed: 25805558
pmcid: 4918747
Hasegawa Y, Latour LL, Sotak CH, Dardzinski BJ, Fisher M. Temperature Dependent Change of Apparent Diffusion Coefficient of Water in Normal and Ischemic Brain of Rats. J Cereb Blood Flow Metab. 1994;14(3):383-390. https://doi.org/10.1038/jcbfm.1994.49
doi: 10.1038/jcbfm.1994.49
pubmed: 8163580
Sun C, Chatterjee A, Yousuf A, et al. Comparison of T2-Weighted Imaging, DWI, and Dynamic Contrast-Enhanced MRI for Calculation of Prostate Cancer Index Lesion Volume: Correlation With Whole-Mount Pathology. Published online 2019:6.
Chatterjee A, He D, Fan X, et al. Performance of Ultrafast DCE-MRI for Diagnosis of Prostate Cancer. Acad Radiol. 2018;25(3):349-358. https://doi.org/10.1016/j.acra.2017.10.004
doi: 10.1016/j.acra.2017.10.004
pubmed: 29167070
Rajan J, Poot D, Juntu J, Sijbers J. Noise measurement from magnitude MRI using local estimates of variance and skewness. Phys Med Biol. 2010;55(16):N441-449. https://doi.org/10.1088/0031-9155/55/16/N02
doi: 10.1088/0031-9155/55/16/N02
pubmed: 20679694
Drumheller DM. General expressions for Rician density and distribution functions. IEEE Transactions on Aerospace Electronic Systems. 1993;29:580-588. https://doi.org/10.1109/7.210098
doi: 10.1109/7.210098
Gudbjartsson H, Patz S. The Rician distribution of noisy MRI data. Magn Reson Med. 1995;34(6):910-914. https://doi.org/10.1002/mrm.1910340618
doi: 10.1002/mrm.1910340618
pubmed: 8598820
pmcid: 2254141
Saloner D. Flow and motion. Magn Reson Imaging Clin N Am. 1999;7(4):699-715.
doi: 10.1016/S1064-9689(21)00517-1
Hedley M, Yan H. Motion artifact suppression: a review of post-processing techniques. Magn Reson Imaging. 1992;10(4):627-635. https://doi.org/10.1016/0730-725x(92)90014-q
doi: 10.1016/0730-725x(92)90014-q
pubmed: 1501533
Clark JA, Kelly WM. Common artifacts encountered in magnetic resonance imaging. Radiol Clin North Am. 1988;26(5):893-920.
pubmed: 3420238
Mirowitz SA. MR imaging artifacts. Challenges and solutions. Magn Reson Imaging Clin N Am. 1999;7(4):717–732.
Rohde GK, Barnett AS, Basser PJ, Marenco S, Pierpaoli C. Comprehensive approach for correction of motion and distortion in diffusion-weighted MRI. Magn Reson Med. 2004;51(1):103-114. https://doi.org/10.1002/mrm.10677
doi: 10.1002/mrm.10677
pubmed: 14705050
Miao J, Huo D, Wilson DL. Quantitative image quality evaluation of MR images using perceptual difference models. Med Phys. 2008;35(6):2541-2553. https://doi.org/10.1118/1.2903207
doi: 10.1118/1.2903207
pubmed: 18649487
pmcid: 2673629
Maas MC, Fütterer JJ, Scheenen TWJ. Quantitative evaluation of computed high B value diffusion-weighted magnetic resonance imaging of the prostate. Invest Radiol. 2013;48(11):779-786. https://doi.org/10.1097/RLI.0b013e31829705bb
doi: 10.1097/RLI.0b013e31829705bb
pubmed: 23907102
Mortamet B, Bernstein MA, Jack CR, et al. Automatic quality assessment in structural brain magnetic resonance imaging. Magn Reson Med. 2009;62(2):365-372. https://doi.org/10.1002/mrm.21992
doi: 10.1002/mrm.21992
pubmed: 19526493
pmcid: 2780021
Barrett T, Lawrence EM, Priest AN, et al. Repeatability of diffusion-weighted MRI of the prostate using whole lesion ADC values, skew and histogram analysis. Eur J Radiol. 2019;110:22-29. https://doi.org/10.1016/j.ejrad.2018.11.014
doi: 10.1016/j.ejrad.2018.11.014
pubmed: 30599864
Padhani AR, Schoots IG, Turkbey B, Giannarini G, Barentsz JO. A multifaceted approach to quality in the MRI-directed biopsy pathway for prostate cancer diagnosis. Eur Radiol. Published online November 25, 2020. https://doi.org/10.1007/s00330-020-07527-9
Panagiotaki E, Chan RW, Dikaios N, et al. Microstructural characterization of normal and malignant human prostate tissue with vascular, extracellular, and restricted diffusion for cytometry in tumours magnetic resonance imaging. Invest Radiol. 2015;50(4):218-227. https://doi.org/10.1097/RLI.0000000000000115
doi: 10.1097/RLI.0000000000000115
pubmed: 25426656
Wang S, Peng Y, Medved M, et al. Hybrid multidimensional T(2) and diffusion-weighted MRI for prostate cancer detection. J Magn Reson Imaging. 2014;39(4):781-788. https://doi.org/10.1002/jmri.24212
doi: 10.1002/jmri.24212
pubmed: 23908146