Abdominal radiology (New York) · 2026
Decision tree models combining Bi-parametric vesical imaging reporting and data system and apparent diffusion coefficient metrics for predicting muscle-invasive bladder cancer.
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Sugawara Daichi, Hatakeyama Kento, Konno Motoko, Tozawa Tomoki, Sato Tomochika, Murata Toshiki, Murasawa Emika, Narita Shintaro, Nanjo Hiroshi, Habuchi Tomonori, Mori Naoko
Аннотация
PURPOSE: To compare whole-lesion apparent diffusion coefficient (ADC) histogram analysis with representative ADC value for assessing muscle invasion in bladder cancer, and to build a decision tree model that combines bi-parametric Vesical Imaging Reporting and Data System (bp VI-RADS) with ADC values.
METHODS: This retrospective study included 82 patients with bladder cancer who underwent 3T MRI and transurethral resection. The bp VI-RADS was scored using T2-weighted and diffusion-weighted imaging, and ADC maps. For histogram analysis, tumors were segmented on all ADC slices to obtain ADC percentiles. For a representative ADC, three regions of interest were placed in visually lowest ADC areas and averaged to obtain the minimum mean ADC. ADC parameters were compared between muscle invasive (MIBC) and non-muscle invasive (NMIBC) disease. Diagnostic performance was assessed using receiver operating characteristic curve analysis with area under the curve (AUC), and combination models were constructed using logistic regression and decision tree analysis.
RESULTS: Among histogram-derived parameters, the 25th percentile ADC achieved the highest AUC, and the minimum mean ADC was strongly correlated with it. As single parameters, bp VI-RADS, the 25th percentile and the minimum mean ADC showed similar accuracy (0.74-0.76). Logistic regression models combining bp VI-RADS with the 25th percentile or the minimum mean ADC achieved higher accuracy (0.88 and 0.87). Decision tree models using bp VI-RADS and ADC reached accuracy of 0.82 and 0.80. In both decision tree models, ADC provided additional stratification primarily for bp VI-RADS 4 lesions, using cutoffs of 1,183 × 10⁻6 mm²/s (25th percentile ADC) and 1,100 × 10⁻6 mm²/s (minimum mean ADC).
CONCLUSION: The 25th percentile and the minimum mean ADC showed similar diagnostic performance for predicting muscle invasion. A decision tree combining bp VI-RADS with ADC measurements may provide an interpretable and clinically applicable approach, particularly for bp VI-RADS 4 lesions.
METHODS: This retrospective study included 82 patients with bladder cancer who underwent 3T MRI and transurethral resection. The bp VI-RADS was scored using T2-weighted and diffusion-weighted imaging, and ADC maps. For histogram analysis, tumors were segmented on all ADC slices to obtain ADC percentiles. For a representative ADC, three regions of interest were placed in visually lowest ADC areas and averaged to obtain the minimum mean ADC. ADC parameters were compared between muscle invasive (MIBC) and non-muscle invasive (NMIBC) disease. Diagnostic performance was assessed using receiver operating characteristic curve analysis with area under the curve (AUC), and combination models were constructed using logistic regression and decision tree analysis.
RESULTS: Among histogram-derived parameters, the 25th percentile ADC achieved the highest AUC, and the minimum mean ADC was strongly correlated with it. As single parameters, bp VI-RADS, the 25th percentile and the minimum mean ADC showed similar accuracy (0.74-0.76). Logistic regression models combining bp VI-RADS with the 25th percentile or the minimum mean ADC achieved higher accuracy (0.88 and 0.87). Decision tree models using bp VI-RADS and ADC reached accuracy of 0.82 and 0.80. In both decision tree models, ADC provided additional stratification primarily for bp VI-RADS 4 lesions, using cutoffs of 1,183 × 10⁻6 mm²/s (25th percentile ADC) and 1,100 × 10⁻6 mm²/s (minimum mean ADC).
CONCLUSION: The 25th percentile and the minimum mean ADC showed similar diagnostic performance for predicting muscle invasion. A decision tree combining bp VI-RADS with ADC measurements may provide an interpretable and clinically applicable approach, particularly for bp VI-RADS 4 lesions.
Предметные рубрики MeSH
HumansUrinary Bladder NeoplasmsDecision TreesFemaleRetrospective StudiesNeoplasm InvasivenessMaleAgedDiffusion Magnetic Resonance ImagingMiddle AgedTransurethral Resection of BladderAged, 80 and overNon-Muscle Invasive Bladder NeoplasmsImage Interpretation, Computer-AssistedPredictive Value of TestsMagnetic Resonance Imaging