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<p>While multiparametric MRI has revolutionized clinically significant prostate cancer (csPCa) detection, conventional apparent diffusion coefficient (ADC) maps suffer from a monoexponential model that conflate the various forms of diffusion in the tissue, leading to poor microstructural specificity and substantial inter-scanner variability. Restriction Spectrum Imaging (RSI) addresses these limitations with a multi-compartment biophysical model that separates the diffusion signal into four compartments, providing a more specific quantitative imaging biomarker, the Restriction Spectrum Imaging restriction score (RSIrs). Although RSIrs has demonstrated promising detection performance for csPCa, patient- and acquisition-related factors may influence its measured values and performance. Our retrospective analysis included 1,890 men (median age 70) from seven centers between 2018 and 2024. Our primary objective was to characterize the quantitative technical robustness of RSIrs using linear modeling. We assessed how age, race, ethnicity, prostate volume, medication use, and MRI acquisition parameters influenced prostate maximum RSIrs (RSIrs<sub>max</sub>) values. Secondary, we conducted a functional validation of RSIrs’ csPCa detection performance when accounting for any significant effects (if any). Non-csPCa patients in this analysis were (1) with confirmed benign or Grade Group 1 findings on biopsy or (2) with a non-suspicious mpMRI (PI-RADS 1 or 2) and a prostate-specific antigen density (PSAD) ≤ 0.15. Results revealed modest effects from age (1.8/year increase), prostate volume (-0.83/mL decrease), and acquisition methods (varying between − 63.14 to + 56.23). While these acquisition- and patient-level variations partially overlapped with change in RSIrs<sub>max</sub> due to Grade Group 2 csPCa, these variations were secondary to the primary signal variation due to csPCa. Adjusting for them did not improve csPCa detection performance (<i>p</i> &gt; 0.05). AUC of RSIrs<sub>max</sub> for patient-level csPCa detection was 0.77 [95% CI: 0.75–0.79] compared to 0.74 [0.72–0.76] after. RSIrs demonstrates robust csPCa detection performance regardless of modest signal variations from patient and acquisition factors, supporting its potential as a generalizable quantitative imaging biomarker for csPCa.</p>

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Systematic effects of patient factors and scanner/protocol factors on a Restriction Spectrum Imaging (RSI) quantitative MRI biomarker for prostate cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月16日

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  • Deondre D. Do,
  • Mariluz Rojo Domingo,
  • Christopher C. Conlin,
  • Ian Matthews,
  • Karoline Kallis,
  • Madison T. Baxter,
  • Courtney Ollison,
  • Yuze Song,
  • George Xu,
  • Allison Y. Zhong,
  • Aditya Bagrodia,
  • Tristan Barrett,
  • Matthew Cooperberg,
  • Felix Feng,
  • Michael E. Hahn,
  • Mukesh Harisinghani,
  • Gary M. Hollenberg,
  • Juan Javier-Desloges,
  • Sophia C. Kamran,
  • Christopher J. Kane,
  • Dimitri Kessler,
  • Joshua Kuperman,
  • Kang-Lung Lee,
  • Jonathan Levine,
  • Michael A. Liss,
  • Daniel J. A. Margolis,
  • Paul M. Murphy,
  • Nabih Nakrour,
  • Michael A. Ohliger,
  • Thomas Osinski,
  • Anthony James Pamatmat,
  • Isabella R. Pompa,
  • Rebecca Rakow-Penner,
  • Jacob L. Roberts,
  • Karan Santhosh,
  • Ahmed S. Shabaik,
  • David Song,
  • Clare M. Tempany,
  • Shaun Trecarten,
  • Natasha Wehrli,
  • Eric P. Weinberg,
  • Sean Woolen,
  • Anders M. Dale,
  • Tyler M. Seibert

摘要

While multiparametric MRI has revolutionized clinically significant prostate cancer (csPCa) detection, conventional apparent diffusion coefficient (ADC) maps suffer from a monoexponential model that conflate the various forms of diffusion in the tissue, leading to poor microstructural specificity and substantial inter-scanner variability. Restriction Spectrum Imaging (RSI) addresses these limitations with a multi-compartment biophysical model that separates the diffusion signal into four compartments, providing a more specific quantitative imaging biomarker, the Restriction Spectrum Imaging restriction score (RSIrs). Although RSIrs has demonstrated promising detection performance for csPCa, patient- and acquisition-related factors may influence its measured values and performance. Our retrospective analysis included 1,890 men (median age 70) from seven centers between 2018 and 2024. Our primary objective was to characterize the quantitative technical robustness of RSIrs using linear modeling. We assessed how age, race, ethnicity, prostate volume, medication use, and MRI acquisition parameters influenced prostate maximum RSIrs (RSIrsmax) values. Secondary, we conducted a functional validation of RSIrs’ csPCa detection performance when accounting for any significant effects (if any). Non-csPCa patients in this analysis were (1) with confirmed benign or Grade Group 1 findings on biopsy or (2) with a non-suspicious mpMRI (PI-RADS 1 or 2) and a prostate-specific antigen density (PSAD) ≤ 0.15. Results revealed modest effects from age (1.8/year increase), prostate volume (-0.83/mL decrease), and acquisition methods (varying between − 63.14 to + 56.23). While these acquisition- and patient-level variations partially overlapped with change in RSIrsmax due to Grade Group 2 csPCa, these variations were secondary to the primary signal variation due to csPCa. Adjusting for them did not improve csPCa detection performance (p > 0.05). AUC of RSIrsmax for patient-level csPCa detection was 0.77 [95% CI: 0.75–0.79] compared to 0.74 [0.72–0.76] after. RSIrs demonstrates robust csPCa detection performance regardless of modest signal variations from patient and acquisition factors, supporting its potential as a generalizable quantitative imaging biomarker for csPCa.