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- Title
Diffusion–relaxation correlation spectrum imaging for predicting tumor consistency and gross total resection in patients with pituitary adenomas: a preliminary study.
- Authors
Su, Chun-Qiu; Wang, Bin-Bin; Tang, Wen-Tian; Tao, Chao; Zhao, Peng; Pan, Min-Hong; Hong, Xun-Ning; Hu, Wen-Tao; Dai, Yong-Ming; Shi, Hai-Bin; Lu, Shan-Shan
- Abstract
Objective: To evaluate the ability of diffusion–relaxation correlation spectrum imaging (DR-CSI) to predict the consistency and extent of resection (EOR) of pituitary adenomas (PAs). Methods: Forty-four patients with PAs were prospectively enrolled. Tumor consistency was evaluated at surgery as either soft or hard, followed by histological assessment. In vivo DR-CSI was performed and spectra were segmented following to a peak-based strategy into four compartments, designated A (low ADC), B (mediate ADC, short T2), C (mediate ADC, long T2), and D (high ADC). The corresponding volume fractions ( f A , f B , f C , f D ) along with the ADC and T2 values were calculated and assessed using univariable analysis for discrimination between hard and soft PAs. Predictors of EOR > 95% were analyzed using logistic regression model and receiver-operating-characteristic analysis. Results: Tumor consistency was classified as soft (n = 28) or hard (n = 16). Hard PAs presented higher f B (p = 0.001) and lower f C (p = 0.013) than soft PAs, while no significant difference was found in other parameters. f B significantly correlated with the level of collagen content (r = 0.448, p = 0.002). Knosp grade (odds ratio [OR], 0.299; 95% confidence interval [CI], 0.124–0.716; p = 0.007) and f B (OR, 0.834, per 1% increase; 95% CI, 0.731–0.951; p = 0.007) were independently associated with EOR > 95%. A prediction model based on these variables yielded an AUC of 0.934 (sensitivity, 90.9%; specificity, 90.9%), outperforming the Knosp grade alone (AUC, 0.785; p < 0.05). Conclusion: DR-CSI may serve as a promising tool to predict the consistency and EOR of PAs. Clinical relevance statement: DR-CSI provides an imaging dimension for characterizing tissue microstructure of PAs and may serve as a promising tool to predict the tumor consistency and extent of resection in patients with PAs. Key Points: • DR-CSI provides an imaging dimension for characterizing tissue microstructure of PAs by visualizing the volume fraction and corresponding spatial distribution of four compartments ( f A , f B , f C , f D ). • f B correlated with the level of collagen content and may be the best DR-CSI parameter for discrimination between hard and soft PAs. • The combination of Knosp grade and f B achieved an AUC of 0.934 for predicting the total or near-total resection, outperforming the Knosp grade alone (AUC, 0.785).
- Subjects
PITUITARY tumors; REGRESSION analysis; LOGISTIC regression analysis; FORECASTING; ODDS ratio
- Publication
European Radiology, 2023, Vol 33, Issue 10, p6993
- ISSN
0938-7994
- Publication type
Article
- DOI
10.1007/s00330-023-09694-x