Characterization of prostate cancer with MR spectroscopic imaging and diffusion-weighted imaging at 3 Tesla

Yousef Mazaheri, Amita Shukla-Dave, Debra A. Goldman, Chaya S. Moskowitz, Toshikazu Takeda, Victor E. Reuter, Oguz Akin, Hedvig Hricak

Research output: Contribution to journalArticle

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Abstract

Purpose: To retrospectively measure metabolic ratios and apparent diffusion coefficient (ADC) values from 3-Tesla MR spectroscopic imaging (MRSI) and diffusion-weighted imaging (DWI) in benign and malignant peripheral zone (PZ) prostate tissue, assess the parameters’ associations with malignancy, and develop and test rules for classifying benign and malignant PZ tissue using whole-mount step-section pathology as the reference standard. Methods: This HIPAA-compliant, IRB-approved study included 67 men (median age, 61 years; range, 41–74 years) with biopsy-proven prostate cancer who underwent preoperative 3 T endorectal multiparametric MRI and had ≥1 PZ lesion >0.1 cm3 at whole-mount histopathology. In benign and malignant PZ regions identified from pathology, voxel-based choline/citrate, polyamines/choline, polyamines/creatine, and (choline + polyamines + creatine)/citrate ratios were averaged, as were ADC values. Patients were randomly split into training and test sets; rules for separating benign from malignant regions were generated with classification and regression tree (CART) analysis and assessed on the test set for sensitivity and specificity. Odds ratios (OR) were evaluated using generalized estimating equations. Results: CART analysis of all parameters identified only ADC and (choline + polyamines + creatine)/citrate as significant predictors of cancer. Sensitivity and specificity, respectively, were 0.81 and 0.82 with MRSI-derived, 0.98 and 0.51 with DWI-derived, and 0.79 and 0.90 with MRSI + DWI-derived classification rules. Areas under the curves (AUC) in the test set were 0.93 (0.87–0.97) with ADC, 0.82 (0.72–0.91) with MRSI, and 0.96 (0.92–0.99) with MRSI + ADC. Conclusion: We developed statistically-based rules for identifying PZ cancer using 3-Tesla MRSI, DWI, and MRSI + DWI and demonstrated the potential value of MRSI + DWI.

LanguageEnglish
Pages93-102
Number of pages10
JournalMagnetic Resonance Imaging
Volume55
DOIs
Publication statusPublished - 2019 Jan 1

Fingerprint

Prostatic Neoplasms
Imaging techniques
Polyamines
Choline
Creatine
Citric Acid
Pathology
Regression Analysis
Health Insurance Portability and Accountability Act
Sensitivity and Specificity
Neoplasms
Research Ethics Committees
Tissue
Biopsy
Area Under Curve
Prostate
Odds Ratio
Magnetic resonance imaging

Keywords

  • 3D = three-dimensional
  • ADC = apparent diffusion coefficient
  • DWI = diffusion-weighted imaging
  • MR spectroscopic imaging MRSI
  • PZ = peripheral zone
  • ROI = region of interest

ASJC Scopus subject areas

  • Biophysics
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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Characterization of prostate cancer with MR spectroscopic imaging and diffusion-weighted imaging at 3 Tesla. / Mazaheri, Yousef; Shukla-Dave, Amita; Goldman, Debra A.; Moskowitz, Chaya S.; Takeda, Toshikazu; Reuter, Victor E.; Akin, Oguz; Hricak, Hedvig.

In: Magnetic Resonance Imaging, Vol. 55, 01.01.2019, p. 93-102.

Research output: Contribution to journalArticle

Mazaheri, Yousef ; Shukla-Dave, Amita ; Goldman, Debra A. ; Moskowitz, Chaya S. ; Takeda, Toshikazu ; Reuter, Victor E. ; Akin, Oguz ; Hricak, Hedvig. / Characterization of prostate cancer with MR spectroscopic imaging and diffusion-weighted imaging at 3 Tesla. In: Magnetic Resonance Imaging. 2019 ; Vol. 55. pp. 93-102.
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abstract = "Purpose: To retrospectively measure metabolic ratios and apparent diffusion coefficient (ADC) values from 3-Tesla MR spectroscopic imaging (MRSI) and diffusion-weighted imaging (DWI) in benign and malignant peripheral zone (PZ) prostate tissue, assess the parameters’ associations with malignancy, and develop and test rules for classifying benign and malignant PZ tissue using whole-mount step-section pathology as the reference standard. Methods: This HIPAA-compliant, IRB-approved study included 67 men (median age, 61 years; range, 41–74 years) with biopsy-proven prostate cancer who underwent preoperative 3 T endorectal multiparametric MRI and had ≥1 PZ lesion >0.1 cm3 at whole-mount histopathology. In benign and malignant PZ regions identified from pathology, voxel-based choline/citrate, polyamines/choline, polyamines/creatine, and (choline + polyamines + creatine)/citrate ratios were averaged, as were ADC values. Patients were randomly split into training and test sets; rules for separating benign from malignant regions were generated with classification and regression tree (CART) analysis and assessed on the test set for sensitivity and specificity. Odds ratios (OR) were evaluated using generalized estimating equations. Results: CART analysis of all parameters identified only ADC and (choline + polyamines + creatine)/citrate as significant predictors of cancer. Sensitivity and specificity, respectively, were 0.81 and 0.82 with MRSI-derived, 0.98 and 0.51 with DWI-derived, and 0.79 and 0.90 with MRSI + DWI-derived classification rules. Areas under the curves (AUC) in the test set were 0.93 (0.87–0.97) with ADC, 0.82 (0.72–0.91) with MRSI, and 0.96 (0.92–0.99) with MRSI + ADC. Conclusion: We developed statistically-based rules for identifying PZ cancer using 3-Tesla MRSI, DWI, and MRSI + DWI and demonstrated the potential value of MRSI + DWI.",
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AU - Shukla-Dave, Amita

AU - Goldman, Debra A.

AU - Moskowitz, Chaya S.

AU - Takeda, Toshikazu

AU - Reuter, Victor E.

AU - Akin, Oguz

AU - Hricak, Hedvig

PY - 2019/1/1

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N2 - Purpose: To retrospectively measure metabolic ratios and apparent diffusion coefficient (ADC) values from 3-Tesla MR spectroscopic imaging (MRSI) and diffusion-weighted imaging (DWI) in benign and malignant peripheral zone (PZ) prostate tissue, assess the parameters’ associations with malignancy, and develop and test rules for classifying benign and malignant PZ tissue using whole-mount step-section pathology as the reference standard. Methods: This HIPAA-compliant, IRB-approved study included 67 men (median age, 61 years; range, 41–74 years) with biopsy-proven prostate cancer who underwent preoperative 3 T endorectal multiparametric MRI and had ≥1 PZ lesion >0.1 cm3 at whole-mount histopathology. In benign and malignant PZ regions identified from pathology, voxel-based choline/citrate, polyamines/choline, polyamines/creatine, and (choline + polyamines + creatine)/citrate ratios were averaged, as were ADC values. Patients were randomly split into training and test sets; rules for separating benign from malignant regions were generated with classification and regression tree (CART) analysis and assessed on the test set for sensitivity and specificity. Odds ratios (OR) were evaluated using generalized estimating equations. Results: CART analysis of all parameters identified only ADC and (choline + polyamines + creatine)/citrate as significant predictors of cancer. Sensitivity and specificity, respectively, were 0.81 and 0.82 with MRSI-derived, 0.98 and 0.51 with DWI-derived, and 0.79 and 0.90 with MRSI + DWI-derived classification rules. Areas under the curves (AUC) in the test set were 0.93 (0.87–0.97) with ADC, 0.82 (0.72–0.91) with MRSI, and 0.96 (0.92–0.99) with MRSI + ADC. Conclusion: We developed statistically-based rules for identifying PZ cancer using 3-Tesla MRSI, DWI, and MRSI + DWI and demonstrated the potential value of MRSI + DWI.

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KW - 3D = three-dimensional

KW - ADC = apparent diffusion coefficient

KW - DWI = diffusion-weighted imaging

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KW - PZ = peripheral zone

KW - ROI = region of interest

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