Utility of quantitative measurement of T2 using restriction spectrum imaging for detection of clinically significant prostate cancer

Figures

• 

  Fig. 1. RSI signal contribution (Ci) and compartmental T2 (cT2) maps for two patients with csPCa. (A) Patient from cohort 1. (B) Patient from cohort 2. Compartmental T2 maps were computed for each RSI model compartment by measuring the T2 -weighted signal decay of the signal-contribution map for different TEs. The signal-contribution maps shown here were computed from the DWI acquisition with shorter TE. Whole-mount (WM) histopathology results were available for the patient from cohort 2 and illustrate the lesion contour in the prostate. For cohort 1, the contouring of the prostate zones and tumor lesions was performed using MIM software (MIM software version 7.2.6, Inc; Cleveland, OH, USA21). For cohort 2, automated prostate contours were obtained using an FDA-cleared commercial product (OnQ Prostate version 1.4, CorTechs.ai, San Diego, CA, USA23).

• 

  Fig. 2. Violin plots showing the distribution of median T2 values in the whole prostate for each of the four RSI model compartments. Within each cohort, compartmental T2 was significantly different between any two compartments (p < 0.05). (A) cohort 1 (n = 46). (B) cohort 2 (n = 195). Plots were created using MATLAB R2022a (MathWorks, Natick, MA, USA18). For cohort 1, the contouring of the prostate zones and tumor lesions was performed using MIM software (MIM software version 7.2.6, Inc; Cleveland, OH, USA21). For cohort 2, automated prostate contours were obtained using an FDA-cleared commercial product (OnQ Prostate version 1.4, CorTechs.ai, San Diego, CA, USA23).

• 

  Fig. 3. Violin plots showing the distribution of median compartmental T2 values from cohort 1 in both csPCa lesions and the surrounding prostate tissue. Each panel corresponds to one of the RSI diffusion compartments. csPCa lesions showed significantly higher compartmental T2 values in C1 (p-value < < 0.001) and C2 (p-value < < 0.001) than tissues outside of csPCa lesions. Compartmental T2 values of C3 were also significantly lower in csPCa lesions than outside csPCa lesions (p-value < < 0.001). A red star indicates a significant difference (p-value < 0.05) in compartmental T2 between csPCa lesions and the prostate tissue outside the lesions. WP: whole prostate. Plots were created using MATLAB R2022a (MathWorks, Natick, MA, USA18). For cohort 1, the contouring of the prostate zones and tumor lesions was performed using MIM software (MIM software version 7.2.6, Inc; Cleveland, OH, USA21).

• 

  Fig. 4. Violin plots comparing compartmental T2 within the whole prostate between patients with csPCa and those without. A red star indicates a significant difference (p-value < 0.05) in whole-prostate compartmental T2 between csPCa and non-csPCa patients. (A) cohort 1 (n = 46). (B) cohort 2 (n = 195). Plots were created using MATLAB R2022a (MathWorks, Natick, MA, USA18). For cohort 1, the contouring of the prostate zones and tumor lesions was performed using MIM software (MIM software version 7.2.6, Inc; Cleveland, OH, USA21). For cohort 2, automated prostate contours were obtained using an FDA-cleared commercial product (OnQ Prostate version 1.4, CorTechs.ai, San Diego, CA, USA23).

• 

  Fig. 5. RSI restriction score and multivariable model probability maps of the prostate for patients with csPCa. Top panel: Patient from cohort 1 with a lesion in the left peripheral zone. Bottom panel: Patient from cohort 2 with a lesion in the transition zone. The multivariable model uses compartmental T2 measurements from each voxel in addition to the RSI restriction score to determine the probability that it contains csPCa. For the patient from cohort 1, the contouring of the prostate zones and tumor lesions was performed using MIM software (MIM software version 7.2.6, Inc; Cleveland, OH, USA21). For patient from cohort 2, automated prostate contours were obtained using an FDA-cleared commercial product (OnQ Prostate version 1.4, CorTechs.ai, San Diego, CA, USA23).

• 

  Fig. 6. Patient-level diagnostic performance of maximum RSIrs, the LRM and maximum C1 (max C1) for cohorts 1 and 2. (A) For cohort 1, mean AUC values were 0.695 for maximum C1, 0.805 for RSIrs and 0.804 for the multivariable model. (B) For cohort 2, mean AUC values were 0.654 for maximum C1, 0.725 for RSIrs and 0.724 for the multivariable model. Plots were created using MATLAB R2022a (MathWorks, Natick, MA, USA18). For cohort 1, the contouring of the prostate zones and tumor lesions was performed using MIM software (MIM software version 7.2.6, Inc; Cleveland, OH, USA21). For cohort 2, automated prostate contours were obtained using an FDA-cleared commercial product (OnQ Prostate version 1.4, CorTechs.ai, San Diego, CA, USA23).