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Gaur S, Harmon S, Gupta RT, Margolis DJ, Lay N, Mehralivand S, Merino MJ, Wood BJ, Pinto PA, Shih JH, Choyke PL, Turkbey B. A Multireader Exploratory Evaluation of Individual Pulse Sequence Cancer Detection on Prostate Multiparametric Magnetic Resonance Imaging (MRI). Acad Radiol 2019; 26:5-14. [PMID: 29705281 PMCID: PMC6202287 DOI: 10.1016/j.acra.2018.03.024] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2018] [Revised: 03/19/2018] [Accepted: 03/24/2018] [Indexed: 01/07/2023]
Abstract
RATIONALE AND OBJECTIVES To determine independent contribution of each prostate multiparametric magnetic resonance imaging (mpMRI) sequence to cancer detection when read in isolation. MATERIALS AND METHODS Prostate mpMRI at 3-Tesla with endorectal coil from 45 patients (n = 30 prostatectomy cases, n = 15 controls with negative magnetic resonance imaging [MRI] or biopsy) were retrospectively interpreted. Sequences (T2-weighted [T2W] MRI, diffusion-weighted imaging [DWI], and dynamic contrast-enhanced [DCE] MRI; N = 135) were separately distributed to three radiologists at different institutions. Readers evaluated each sequence blinded to other mpMRI sequences. Findings were correlated to whole-mount pathology. Cancer detection sensitivity, positive predictive value for whole prostate (WP), transition zone, and peripheral zone were evaluated per sequence by reader, with reader concordance measured by index of specific agreement. Cancer detection rates (CDRs) were calculated for combinations of independently read sequences. RESULTS 44 patients were evaluable (cases median prostate-specific antigen 6.83 [ range 1.95-51.13] ng/mL, age 62 [45-71] years; controls prostate-specific antigen 6.85 [2.4-10.87] ng/mL, age 65.5 [47-71] years). Readers had highest sensitivity on DWI (59%) vs T2W MRI (48%) and DCE (23%) in WP. DWI-only positivity (DWI+/T2W-/DCE-) achieved highest CDR in WP (38%), compared to T2W-only (CDR 24%) and DCE-only (CDR 8%). DWI+/T2W+/DCE- achieved CDR 80%, an added benefit of 56.4% from T2W-only and of 42% from DWI-only (P < .0001). All three sequences interpreted independently positive gave highest CDR of 90%. Reader agreement was moderate (index of specific agreement: T2W = 54%, DWI = 58%, DCE = 33%). CONCLUSIONS When prostate mpMRI sequences are interpreted independently by multiple observers, DWI achieves highest sensitivity and CDR in transition zone and peripheral zone. T2W and DCE MRI both add value to detection; mpMRI achieves highest detection sensitivity when all three mpMRI sequences are positive.
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Affiliation(s)
- Sonia Gaur
- Molecular Imaging Program, National Cancer Institute, NIH, 10 Center Drive, Room B3B85, Bethesda, MD 20814, USA. ; ;
| | - Stephanie Harmon
- Clinical Research Directorate/Clinical Monitoring Research Program, Leidos Biomedical Research, Inc., National Cancer Institute, Campus at Frederick, 8560 Progress Drive, Frederick, MD 21707, USA.
| | - Rajan T. Gupta
- Duke University Medical Center, Duke Cancer Institute, Durham, NC 27710, USA.
| | - Daniel J. Margolis
- Weill Cornell Imaging, New York-Presbytarian Hospital, New York, NY 10021, USA.
| | - Nathan Lay
- Computer-Aided Diagnosis Laboratory, Clinical Center, NIH, 10 Center Drive, Bethesda, MD 20814, USA.
| | - Sherif Mehralivand
- Urologic Oncology Branch, National Cancer Institute, NIH, 10 Center Drive, Bethesda, MD 20814, USA. ;
| | - Maria J. Merino
- Department of Pathology, National Cancer Institute, NIH, 10 Center Drive, Bethesda, MD 20814, USA.
| | - Bradford J. Wood
- Center for Interventional Oncology, Clinical Center, NIH, 10 Center Drive, Bethesda, MD 20814, USA.
| | - Peter A. Pinto
- Urologic Oncology Branch, National Cancer Institute, NIH, 10 Center Drive, Bethesda, MD 20814, USA. ;
| | - Joanna H. Shih
- Biometric Research Branch, National Cancer Institute, NIH, 6130 Executive Plaza, Room 8132, Rockville, MD 20852, USA.
| | - Peter L. Choyke
- Molecular Imaging Program, National Cancer Institute, NIH, 10 Center Drive, Room B3B85, Bethesda, MD 20814, USA. ; ;
| | - Baris Turkbey
- Molecular Imaging Program, National Cancer Institute, NIH, 10 Center Drive, Room B3B85, Bethesda, MD 20814, USA. ; ;
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Hurrell SL, McGarry SD, Kaczmarowski A, Iczkowski KA, Jacobsohn K, Hohenwalter MD, Hall WA, See WA, Banerjee A, Charles DK, Nevalainen MT, Mackinnon AC, LaViolette PS. Optimized b-value selection for the discrimination of prostate cancer grades, including the cribriform pattern, using diffusion weighted imaging. J Med Imaging (Bellingham) 2017; 5:011004. [PMID: 29098169 PMCID: PMC5658575 DOI: 10.1117/1.jmi.5.1.011004] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Accepted: 09/21/2017] [Indexed: 01/21/2023] Open
Abstract
Multiparametric magnetic resonance imaging (MP-MRI), including diffusion-weighted imaging, is commonly used to diagnose prostate cancer. This radiology–pathology study correlates prostate cancer grade and morphology with common b-value combinations for calculating apparent diffusion coefficient (ADC). Thirty-nine patients undergoing radical prostatectomy were recruited for MP-MRI prior to surgery. Diffusion imaging was collected with seven b-values, and ADC was calculated. Excised prostates were sliced in the same orientation as the MRI using 3-D printed slicing jigs. Whole-mount slides were digitized and annotated by a pathologist. Annotated samples were aligned to the MRI, and ADC values were extracted from annotated peripheral zone (PZ) regions. A receiver operating characteristic (ROC) analysis was performed to determine accuracy of tissue type discrimination and optimal ADC b-value combination. ADC significantly discriminates Gleason (G) G4-5 cancer from G3 and other prostate tissue types. The optimal b-values for discriminating high from low-grade and noncancerous tissue in the PZ are 50 and 2000, followed closely by 100 to 2000 and 0 to 2000. Optimal ADC cut-offs are presented for dichotomized discrimination of tissue types according to each b-value combination. Selection of b-values affects the sensitivity and specificity of ADC for discrimination of prostate cancer.
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Affiliation(s)
- Sarah L Hurrell
- Medical College of Wisconsin, Department of Radiology, Milwaukee, Wisconsin, United States
| | - Sean D McGarry
- Medical College of Wisconsin, Department of Biophysics, Milwaukee, Wisconsin, United States
| | - Amy Kaczmarowski
- Medical College of Wisconsin, Department of Radiology, Milwaukee, Wisconsin, United States
| | - Kenneth A Iczkowski
- Medical College of Wisconsin, Department of Pathology, Milwaukee, Wisconsin, United States.,Medical College of Wisconsin, Department of Urology, Milwaukee, Wisconsin, United States
| | - Kenneth Jacobsohn
- Medical College of Wisconsin, Department of Urology, Milwaukee, Wisconsin, United States
| | - Mark D Hohenwalter
- Medical College of Wisconsin, Department of Radiology, Milwaukee, Wisconsin, United States
| | - William A Hall
- Medical College of Wisconsin, Department of Radiation Oncology, Milwaukee, Wisconsin, United States
| | - William A See
- Medical College of Wisconsin, Department of Urology, Milwaukee, Wisconsin, United States
| | - Anjishnu Banerjee
- Medical College of Wisconsin, Department of Biostatistics, Milwaukee, Wisconsin, United States
| | - David K Charles
- Medical College of Wisconsin, Department of Urology, Milwaukee, Wisconsin, United States
| | - Marja T Nevalainen
- Medical College of Wisconsin, Department of Pathology, Milwaukee, Wisconsin, United States.,Medical College of Wisconsin, Department of Pharmacology and Toxicology, Milwaukee, Wisconsin, United States
| | - Alexander C Mackinnon
- Medical College of Wisconsin, Department of Pathology, Milwaukee, Wisconsin, United States
| | - Peter S LaViolette
- Medical College of Wisconsin, Department of Radiology, Milwaukee, Wisconsin, United States.,Medical College of Wisconsin, Department of Biomedical Engineering, Milwaukee, Wisconsin, United States
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Cai K, Tain RW, Zhou XJ, Damen FC, Scotti AM, Hariharan H, Poptani H, Reddy R. Creatine CEST MRI for Differentiating Gliomas with Different Degrees of Aggressiveness. Mol Imaging Biol 2017; 19:225-232. [PMID: 27541025 PMCID: PMC5824619 DOI: 10.1007/s11307-016-0995-0] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
PURPOSE Creatine (Cr) is a major metabolite in the bioenergetic system. Measurement of Cr using conventional MR spectroscopy (MRS) suffers from low spatial resolution and relatively long acquisition times. Creatine chemical exchange saturation transfer (CrCEST) magnetic resonance imaging (MRI) is an emerging molecular imaging method for tissue Cr measurements. Our previous study showed that the CrCEST contrast, obtained through multicomponent Z-spectral fitting, was lower in tumors compared to normal brain, which further reduced with tumor progression. The current study was aimed to investigate if CrCEST MRI can also be useful for differentiating gliomas with different degrees of aggressiveness. PROCEDURES Intracranial 9L gliosarcoma and F98 glioma bearing rats with matched tumor size were scanned with a 9.4 T MRI scanner at two time points. CEST Z-spectra were collected using a customized sequence with a frequency-selective rectangular saturation pulse (B1 = 50 Hz, duration = 3 s) followed by a single-shot readout. Z spectral data were fitted pixel-wise with five Lorentzian functions, and maps of CrCEST peak amplitude, linewidth, and integral were produced. For comparison, single-voxel proton MR spectroscopy (1H-MRS) was performed to quantify and compare the total Cr concentration in the tumor. RESULTS CrCEST contrasts decreased with tumor progression from weeks 3 to 4 in both 9L and F98 phenotypes. More importantly, F98 tumors had significantly lower CrCEST integral compared to 9L tumors. On the other hand, integrals of other Z-spectral components were unable to differentiate both tumor progression and phenotype with limited sample size. CONCLUSIONS Given that F98 is a more aggressive tumor than 9L, this study suggests that CrCEST MRI may help differentiate gliomas with different aggressiveness.
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Affiliation(s)
- Kejia Cai
- Department of Radiology and the Center for MR Research, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA.
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA.
| | - Rong-Wen Tain
- Department of Radiology and the Center for MR Research, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Xiaohong Joe Zhou
- Department of Radiology and the Center for MR Research, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
| | - Frederick C Damen
- Department of Radiology and the Center for MR Research, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Alessandro M Scotti
- Department of Radiology and the Center for MR Research, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
| | - Hari Hariharan
- The Center for Magnetic Resonance and Optical Imaging, Department of Radiology, School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Harish Poptani
- Centre for Preclinical Imaging, University of Liverpool, Liverpool, UK
| | - Ravinder Reddy
- The Center for Magnetic Resonance and Optical Imaging, Department of Radiology, School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Yu AC, Badve C, Ponsky LE, Pahwa S, Dastmalchian S, Rogers M, Jiang Y, Margevicius S, Schluchter M, Tabayoyong W, Abouassaly R, McGivney D, Griswold MA, Gulani V. Development of a Combined MR Fingerprinting and Diffusion Examination for Prostate Cancer. Radiology 2017; 283:729-738. [PMID: 28187264 DOI: 10.1148/radiol.2017161599] [Citation(s) in RCA: 108] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Purpose To develop and evaluate an examination consisting of magnetic resonance (MR) fingerprinting-based T1, T2, and standard apparent diffusion coefficient (ADC) mapping for multiparametric characterization of prostate disease. Materials and Methods This institutional review board-approved, HIPAA-compliant retrospective study of prospectively collected data included 140 patients suspected of having prostate cancer. T1 and T2 mapping was performed with fast imaging with steady-state precession-based MR fingerprinting with ADC mapping. Regions of interest were drawn by two independent readers in peripheral zone lesions and normal-appearing peripheral zone (NPZ) tissue identified on clinical images. T1, T2, and ADC were recorded for each region. Histopathologic correlation was based on systematic transrectal biopsy or cognitively targeted biopsy results, if available. Generalized estimating equations logistic regression was used to assess T1, T2, and ADC in the differentiation of (a) cancer versus NPZ, (b) cancer versus prostatitis, (c) prostatitis versus NPZ, and (d) high- or intermediate-grade tumors versus low-grade tumors. Analysis was performed for all lesions and repeated in a targeted biopsy subset. Discriminating ability was evaluated by using the area under the receiver operating characteristic curve (AUC). Results In this study, 109 lesions were analyzed, including 39 with cognitively targeted sampling. T1, T2, and ADC from cancer (mean, 1628 msec ± 344, 73 msec ± 27, and 0.773 × 10-3 mm2/sec ± 0.331, respectively) were significantly lower than those from NPZ (mean, 2247 msec ± 450, 169 msec ± 61, and 1.711 × 10-3 mm2/sec ± 0.269) (P < .0001 for each) and together produced the best separation between these groups (AUC = 0.99). ADC and T2 together produced the highest AUC of 0.83 for separating high- or intermediate-grade tumors from low-grade cancers. T1, T2, and ADC in prostatitis (mean, 1707 msec ± 377, 79 msec ± 37, and 0.911 × 10-3 mm2/sec ± 0.239) were significantly lower than those in NPZ (P < .0005 for each). Interreader agreement was excellent, with an intraclass correlation coefficient greater than 0.75 for both T1 and T2 measurements. Conclusion This study describes the development of a rapid MR fingerprinting- and diffusion-based examination for quantitative characterization of prostatic tissue. © RSNA, 2017 Online supplemental material is available for this article.
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Affiliation(s)
- Alice C Yu
- From the School of Medicine (A.C.Y., M.R.), Department of Radiology (C.B., S.P., S.D., M.A.G., V.G.), Department of Urology (L.E.P., W.T., R.A., V.G.), Department of Biomedical Engineering (Y.J., M.A.G., V.G.), Department of Epidemiology and Biostatistics (S.M., M.S.), and Department of Mathematics (D.M.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106
| | - Chaitra Badve
- From the School of Medicine (A.C.Y., M.R.), Department of Radiology (C.B., S.P., S.D., M.A.G., V.G.), Department of Urology (L.E.P., W.T., R.A., V.G.), Department of Biomedical Engineering (Y.J., M.A.G., V.G.), Department of Epidemiology and Biostatistics (S.M., M.S.), and Department of Mathematics (D.M.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106
| | - Lee E Ponsky
- From the School of Medicine (A.C.Y., M.R.), Department of Radiology (C.B., S.P., S.D., M.A.G., V.G.), Department of Urology (L.E.P., W.T., R.A., V.G.), Department of Biomedical Engineering (Y.J., M.A.G., V.G.), Department of Epidemiology and Biostatistics (S.M., M.S.), and Department of Mathematics (D.M.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106
| | - Shivani Pahwa
- From the School of Medicine (A.C.Y., M.R.), Department of Radiology (C.B., S.P., S.D., M.A.G., V.G.), Department of Urology (L.E.P., W.T., R.A., V.G.), Department of Biomedical Engineering (Y.J., M.A.G., V.G.), Department of Epidemiology and Biostatistics (S.M., M.S.), and Department of Mathematics (D.M.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106
| | - Sara Dastmalchian
- From the School of Medicine (A.C.Y., M.R.), Department of Radiology (C.B., S.P., S.D., M.A.G., V.G.), Department of Urology (L.E.P., W.T., R.A., V.G.), Department of Biomedical Engineering (Y.J., M.A.G., V.G.), Department of Epidemiology and Biostatistics (S.M., M.S.), and Department of Mathematics (D.M.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106
| | - Matthew Rogers
- From the School of Medicine (A.C.Y., M.R.), Department of Radiology (C.B., S.P., S.D., M.A.G., V.G.), Department of Urology (L.E.P., W.T., R.A., V.G.), Department of Biomedical Engineering (Y.J., M.A.G., V.G.), Department of Epidemiology and Biostatistics (S.M., M.S.), and Department of Mathematics (D.M.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106
| | - Yun Jiang
- From the School of Medicine (A.C.Y., M.R.), Department of Radiology (C.B., S.P., S.D., M.A.G., V.G.), Department of Urology (L.E.P., W.T., R.A., V.G.), Department of Biomedical Engineering (Y.J., M.A.G., V.G.), Department of Epidemiology and Biostatistics (S.M., M.S.), and Department of Mathematics (D.M.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106
| | - Seunghee Margevicius
- From the School of Medicine (A.C.Y., M.R.), Department of Radiology (C.B., S.P., S.D., M.A.G., V.G.), Department of Urology (L.E.P., W.T., R.A., V.G.), Department of Biomedical Engineering (Y.J., M.A.G., V.G.), Department of Epidemiology and Biostatistics (S.M., M.S.), and Department of Mathematics (D.M.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106
| | - Mark Schluchter
- From the School of Medicine (A.C.Y., M.R.), Department of Radiology (C.B., S.P., S.D., M.A.G., V.G.), Department of Urology (L.E.P., W.T., R.A., V.G.), Department of Biomedical Engineering (Y.J., M.A.G., V.G.), Department of Epidemiology and Biostatistics (S.M., M.S.), and Department of Mathematics (D.M.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106
| | - William Tabayoyong
- From the School of Medicine (A.C.Y., M.R.), Department of Radiology (C.B., S.P., S.D., M.A.G., V.G.), Department of Urology (L.E.P., W.T., R.A., V.G.), Department of Biomedical Engineering (Y.J., M.A.G., V.G.), Department of Epidemiology and Biostatistics (S.M., M.S.), and Department of Mathematics (D.M.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106
| | - Robert Abouassaly
- From the School of Medicine (A.C.Y., M.R.), Department of Radiology (C.B., S.P., S.D., M.A.G., V.G.), Department of Urology (L.E.P., W.T., R.A., V.G.), Department of Biomedical Engineering (Y.J., M.A.G., V.G.), Department of Epidemiology and Biostatistics (S.M., M.S.), and Department of Mathematics (D.M.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106
| | - Debra McGivney
- From the School of Medicine (A.C.Y., M.R.), Department of Radiology (C.B., S.P., S.D., M.A.G., V.G.), Department of Urology (L.E.P., W.T., R.A., V.G.), Department of Biomedical Engineering (Y.J., M.A.G., V.G.), Department of Epidemiology and Biostatistics (S.M., M.S.), and Department of Mathematics (D.M.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106
| | - Mark A Griswold
- From the School of Medicine (A.C.Y., M.R.), Department of Radiology (C.B., S.P., S.D., M.A.G., V.G.), Department of Urology (L.E.P., W.T., R.A., V.G.), Department of Biomedical Engineering (Y.J., M.A.G., V.G.), Department of Epidemiology and Biostatistics (S.M., M.S.), and Department of Mathematics (D.M.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106
| | - Vikas Gulani
- From the School of Medicine (A.C.Y., M.R.), Department of Radiology (C.B., S.P., S.D., M.A.G., V.G.), Department of Urology (L.E.P., W.T., R.A., V.G.), Department of Biomedical Engineering (Y.J., M.A.G., V.G.), Department of Epidemiology and Biostatistics (S.M., M.S.), and Department of Mathematics (D.M.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106
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