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Accuracy of Quantitative Chemical-Exchange-Saturation-Transfer Imaging for Grading Prostate Cancer and Predicting
Huan Chang1,2, Zhechuan Dai3, Hao Cheng1,2
1Department of Radiology, Beijing Hospital, National Center for Gerontology, National Clinical Research Center for Gerontology, The Key Laboratory of Geriatrics of NHC, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.
Background:
Preoperative quantitative chemical-exchange-saturation-transfer (CEST) imaging may help prostate cancer (PCa) grading and adverse pathological prediction, including positive surgical margin (PSM), perineural invasion (PNI), and extracapsular extension (EPE), which are important for clinical decision-making.
Purpose:
To assess quantitative CEST imaging in grading PCa and predicting PSM, PNI, and EPE.
Study Type:
Prospective.
Population:
Seventy-four male participants (74 ± 5 years) with 77 surgically diagnosed lesions.
Field Strength/Sequence:
3.0 T; turbo spin echo (TSE) T1-/T2-weighted imaging, echo-planar diffusion-weighted imaging, and frequency-stabilized TSE CEST imaging.
Assessment:
The nuclear-Overhauser-effect (NOE) and amide-proton-transfer (APT) signals were derived using four-pool Lorentzian fit. PCa was classified into low (Gleason score [GS] ≤ 3 + 4) and high (GS ≥ 4 + 3) grades according to radical prostatectomy pathology. Quantitative CEST signals and apparent diffusion coefficient (ADC) were assessed according to PCa grade and PSM/PNI/EPE status. The diagnostic performance was evaluated for individual imaging metrics and combined models incorporating significant imaging and clinical variables.
Statistical Tests:
Continuous variables were compared using the t-test or Mann-Whitney U-test. Diagnostic performance was evaluated by area under the receiver operating characteristic curve (AUC) and compared using the DeLong test. Ten-fold cross-validation was performed. p < 0.05 was significant.
Results:
NOE signals were significantly lower in high-grade PCa (CEST ratio [CESTR]_NOE: 0.004 ± 0.004 vs. 0.012 ± 0.013; AUC = 0.764). The combined model of CESTR_NOE, ADC, and biopsy GS yielded an apparent AUC of 0.934 and a 10-fold cross-validated AUC of 0.911. APT signals were significantly lower in PSM-positive (CESTR normalized with the reference value [CESTRnr]_APT: 0.044 ± 0.012 vs. 0.062 ± 0.018; AUC = 0.808) and PNI-positive lesions (CESTR_APT: 0.026 ± 0.007 vs. 0.030 ± 0.011; AUC = 0.669), while ADC showed limited performance (p = 0.329 for PSM, p = 0.373 for PNI).
Data Conclusion:
NOE signals improved PCa grading, and APT signals were associated with adverse pathological features, with relatively better diagnostic performance for PSM.
Evidence Level:
2.
Technical Efficacy:
Stage 2.
