Jiacheng Song1, Qiming Hu2, Junwen Huang1, Zhanlong Ma1, Ting Chen1. 1. 1 Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China. 2. 2 Department of Obstetrics & Gynecology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China.
Abstract
BACKGROUND: Detecting normal-sized metastatic pelvic lymph nodes (LNs) in cervical cancers, although difficult, is of vital importance. PURPOSE: To investigate the value of diffusion-weighted-imaging (DWI), tumor size, and LN shape in predicting metastases in normal-sized pelvic LNs in cervical cancers. MATERIAL AND METHODS: Pathology confirmed cervical cancer patients with complete magnetic resonance imaging (MRI) were documented from 2011 to 2016. A total of 121 cervical cancer patients showed small pelvic LNs (<5 mm) and 92 showed normal-sized (5-10 mm) pelvic LNs (39 patients with 55 nodes that were histologically metastatic, 53 patients with 71 nodes that were histologically benign). Preoperative clinical and MRI variables were analyzed and compared between the metastatic and benign groups. RESULTS: LN apparent diffusion coefficient (ADC) values and short-to-long axis ratios were not significantly different between metastatic and benign normal-sized LNs (0.98 ± 0.15 × 10-3 vs. 1.00 ± 0.18 × 10-3 mm2/s, P = 0.45; 0.65 ± 0.16 vs. 0.64 ± 0.16, P = 0.60, respectively). Tumor ADC value of the metastatic LNs was significantly lower than the benign LNs (0.98 ± 0.12 × 10-3 vs. 1.07 ± 0.21 × 10-3 mm2/s, P = 0.01). Tumor size (height) was significantly higher in the metastatic LN group (27.59 ± 9.18 mm vs. 21.36 ± 10.40 mm, P < 0.00). Spiculated border rate was higher in the metastatic LN group (9 [16.4%] vs. 3 [4.2%], P = 0.03). Tumor (height) combined with tumor ADC value showed the highest area under the curve of 0.702 ( P < 0.00) in detecting metastatic pelvic nodes, with a sensitivity of 59.1% and specificity of 78.8%. CONCLUSIONS: Tumor DWI combined with tumor height were superior to LN DWI and shape in predicting the metastatic state of normal-sized pelvic LNs in cervical cancer patients.
BACKGROUND: Detecting normal-sized metastatic pelvic lymph nodes (LNs) in cervical cancers, although difficult, is of vital importance. PURPOSE: To investigate the value of diffusion-weighted-imaging (DWI), tumor size, and LN shape in predicting metastases in normal-sized pelvic LNs in cervical cancers. MATERIAL AND METHODS: Pathology confirmed cervical cancerpatients with complete magnetic resonance imaging (MRI) were documented from 2011 to 2016. A total of 121 cervical cancerpatients showed small pelvic LNs (<5 mm) and 92 showed normal-sized (5-10 mm) pelvic LNs (39 patients with 55 nodes that were histologically metastatic, 53 patients with 71 nodes that were histologically benign). Preoperative clinical and MRI variables were analyzed and compared between the metastatic and benign groups. RESULTS: LN apparent diffusion coefficient (ADC) values and short-to-long axis ratios were not significantly different between metastatic and benign normal-sized LNs (0.98 ± 0.15 × 10-3 vs. 1.00 ± 0.18 × 10-3 mm2/s, P = 0.45; 0.65 ± 0.16 vs. 0.64 ± 0.16, P = 0.60, respectively). Tumor ADC value of the metastatic LNs was significantly lower than the benign LNs (0.98 ± 0.12 × 10-3 vs. 1.07 ± 0.21 × 10-3 mm2/s, P = 0.01). Tumor size (height) was significantly higher in the metastatic LN group (27.59 ± 9.18 mm vs. 21.36 ± 10.40 mm, P < 0.00). Spiculated border rate was higher in the metastatic LN group (9 [16.4%] vs. 3 [4.2%], P = 0.03). Tumor (height) combined with tumor ADC value showed the highest area under the curve of 0.702 ( P < 0.00) in detecting metastatic pelvic nodes, with a sensitivity of 59.1% and specificity of 78.8%. CONCLUSIONS:Tumor DWI combined with tumor height were superior to LN DWI and shape in predicting the metastatic state of normal-sized pelvic LNs in cervical cancerpatients.
Entities:
Keywords:
Diffusion-weighted magnetic resonance imaging; cervical cancer; lymph node; metastasis
Authors: Njål Lura; Kari S Wagner-Larsen; David Forsse; Jone Trovik; Mari K Halle; Bjørn I Bertelsen; Øyvind Salvesen; Kathrine Woie; Camilla Krakstad; Ingfrid S Haldorsen Journal: Insights Imaging Date: 2022-06-17