Quantitative MRI biomarker for classification of clinically significant prostate cancer: Calibration for reproducibility across echo times

被引:0
作者
Kallis, Karoline [1 ]
Conlin, Christopher C. [2 ]
Ollison, Courtney [1 ]
Hahn, Michael E. [2 ]
Rakow-Penner, Rebecca [2 ]
Dale, Anders M. [2 ,3 ,4 ]
Seibert, Tyler M. [1 ,2 ,5 ]
机构
[1] UC San Diego Hlth, Dept Radiat Med & Appl Sci, 3855 Hlth Sci Dr, La Jolla, CA 92093 USA
[2] UC San Diego Hlth, Dept Radiol, La Jolla, CA USA
[3] UC San Diego Hlth, Dept Neurosci, La Jolla, CA USA
[4] Univ Calif San Diego, Halicioglu Data Sci Inst, La Jolla, CA USA
[5] Univ Calif San Diego, Jacobs Sch Engn, Dept Bioengn, La Jolla, CA USA
来源
JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS | 2024年 / 25卷 / 11期
基金
美国国家卫生研究院;
关键词
calibration; diffusion-weighted imaging; echo time; prostate cancer; quantitative biomarker; restricted spectrum imaging restriction score; DIFFUSION; TISSUE; DIAGNOSIS; PERFUSION; DWI;
D O I
10.1002/acm2.14514
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: The purpose of the present study is to develop a calibration method to account for differences in echo times and facilitate use of RSIrs as a quantitative biomarker for the detection of csPCa. Methods: This study included 197 consecutive patients who underwent MRI and biopsy examination; 97 were diagnosed with csPCa (grade group >= 2). RSI data were acquired three times during the same session: twice at minimum TE similar to 75ms and once at TE=90ms (TEmin (1) , TEmin (2) , and TE90, respectively). A proposed calibration method, trained on patients without csPCa, estimated a linear scaling factor (f) for each of the four diffusion compartments (C) of the RSI signal model. A linear regression model was determined to match C-maps of TE90 to the reference C-maps of TEmin (1) within the interval ranging from 95 (th) to 99 (th) percentile of signal intensity within the prostate. RSIrs comparisons were made at 98 (th) percentile within each patient's prostate. We compared RSIrs from calibrated TE90 (RSIrs (TE90corr) ) and uncorrected TE90 (RSIrs (TE90) ) to RSIrs from reference TEmin (1) (RSIrs (TEmin1) ) and repeated TEmin (2) (RSIrs (TEmin2) ). Calibration performance was evaluated with sensitivity, specificity, area under the ROC curve, positive predicted value, negative predicted value, and F1-score. Results: Scaling factors for C (1) , C (2) , C (3) , and C (4) were estimated as 1.70, 1.38, 1.03, and 1.19, respectively. In non-csPCa cases, the 98 (th) percentile of RSIrs (TEmin2) and RSIrs (TEmin1) differed by 0.27 +/- 0.86SI (mean +/- standard deviation), whereas RSIrs (TE90) differed from RSIrs (TEmin1) by 1.81 +/- 1.20SI. After calibration, this bias was reduced to -0.41 +/- 1.20SI, representing a 78% reduction in absolute error. For patients with csPCa, the difference was 0.54 +/- 1.98SI between RSIrs (TEmin2) and RSIrs (TEmin1) and 2.28 +/- 2.06SI between RSIrs (TE90) and RSIrs (TEmin1) . After calibration, the mean difference decreased to -0.86SI, a 38% reduction in absolute error. At the Youden index for patient-level classification of csPCa (8.94SI), RSIrs (TEmin1) has a sensitivity of 66% and a specificity of 72%. Prior to calibration, RSIrs (TE90) at the same threshold tended to over-diagnose benign cases (sensitivity 44%, specificity 88%). Post-calibration, RSIrs (TE90corr) performs more similarly to the reference (sensitivity 71%, specificity 62%). Conclusion: The proposed linear calibration method produces similar quantitative biomarker values for acquisitions with different TE, reducing TE-induced error by 78% and 38% for non-csPCa and csPCa, respectively.
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页数:9
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共 26 条
  • [1] Correlation between ADC, ADC ratio, and Gleason Grade group in prostate cancer patients undergoing radical prostatectomy: Retrospective multicenter study with different MRI scanners
    Bengtsson, Johan
    Thimansson, Erik
    Baubeta, Erik
    Zackrisson, Sophia
    Sundgren, Pia Charlotte
    Bjartell, Anders
    Flondell-Site, Despina
    [J]. FRONTIERS IN ONCOLOGY, 2023, 13
  • [2] Restriction Spectrum Imaging: An Evolving Imaging Biomarker in Prostate MRI
    Brunsing, Ryan L.
    Schenker-Ahmed, Natalie M.
    White, Nathan S.
    Parsons, J. Kellogg
    Kane, Christopher
    Kuperman, Joshua
    Bartsch, Hauke
    Kader, Andrew Karim
    Rakow-Penner, Rebecca
    Seibert, Tyler M.
    Margolis, Daniel
    Raman, Steven S.
    McDonald, Carrie R.
    Farid, Nikdokht
    Kesari, Santosh
    Hansel, Donna
    Shabaik, Ahmed
    Dale, Anders M.
    Karow, David S.
    [J]. JOURNAL OF MAGNETIC RESONANCE IMAGING, 2017, 45 (02) : 323 - 336
  • [3] Comparison of intra- and inter-patient intensity standardization methods for multi-parametric whole-body MRI
    Ceranka, Jakub
    Lecouvet, Frederic
    Michoux, Nicolas
    de Mey, Johan
    Raeymaekers, Hubert
    Metens, Thierry
    Vandemeulebroucke, Jef
    [J]. BIOMEDICAL PHYSICS & ENGINEERING EXPRESS, 2023, 9 (03)
  • [4] Diagnosis of Prostate Cancer with Noninvasive Estimation of Prostate Tissue Composition by Using Hybrid Multidimensional MR Imaging: A Feasibility Study
    Chatterjee, Aritrick
    Bourne, Roger M.
    Wang, Shiyang
    Devaraj, Ajit
    Gallan, Alexander J.
    Antic, Tatjana
    Karczmar, Gregory S.
    Oto, Aytekin
    [J]. RADIOLOGY, 2018, 287 (03) : 864 - 873
  • [5] Changes in Epithelium, Stroma, and Lumen Space Correlate More Strongly with Gleason Pattern and Are Stronger Predictors of Prostate ADC Changes than Cellularity Metrics
    Chatterjee, Aritrick
    Watson, Geoffrey
    Myint, Esther
    Sved, Paul
    McEntee, Mark
    Bourne, Roger
    [J]. RADIOLOGY, 2015, 277 (03) : 751 - 762
  • [6] Improved Characterization of Diffusion in Normal and Cancerous Prostate Tissue Through Optimization of Multicompartmental Signal Models
    Conlin, Christopher C.
    Feng, Christine H.
    Rodriguez-Soto, Ana E.
    Karunamuni, Roshan A.
    Kuperman, Joshua M.
    Holland, Dominic
    Rakow-Penner, Rebecca
    Hahn, Michael E.
    Seibert, Tyler M.
    Dale, Anders M.
    [J]. JOURNAL OF MAGNETIC RESONANCE IMAGING, 2021, 53 (02) : 628 - 639
  • [7] Effects of echo time on IVIM quantifications of locally advanced breast cancer in clinical diffusion-weighted MRI at 3 T
    Egnell, Liv
    Jerome, Neil P.
    Andreassen, Maren M. S.
    Bathen, Tone F.
    Goa, Pal Erik
    [J]. NMR IN BIOMEDICINE, 2022, 35 (05)
  • [8] Voxel-level Classification of Prostate Cancer on Magnetic Resonance Imaging: Improving Accuracy Using Four-Compartment Restriction Spectrum Imaging
    Feng, Christine H.
    Conlin, Christopher C.
    Batra, Kanha
    Rodriguez-Soto, Ana E.
    Karunamuni, Roshan
    Simon, Aaron
    Kuperman, Joshua
    Rakow-Penner, Rebecca
    Hahn, Michael E.
    Dale, Anders M.
    Seibert, Tyler M.
    [J]. JOURNAL OF MAGNETIC RESONANCE IMAGING, 2021, 54 (03) : 975 - 984
  • [9] Efficient correction of inhomogeneous static magnetic field-induced distortion in Echo Planar Imaging
    Holland, Dominic
    Kuperman, Joshua M.
    Dale, Anders M.
    [J]. NEUROIMAGE, 2010, 50 (01) : 175 - 183
  • [10] Nonrigid Registration of Joint Histograms for Intensity Standardization in Magnetic Resonance Imaging
    Jaeger, Florian
    Hornegger, Joachim
    [J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 2009, 28 (01) : 137 - 150