Bibliographic Details
| Title: |
Histogram analysis of diffusion-weighted magnetic resonance imaging as a biomarker to predict LNM in T3 stage rectal carcinoma |
| Authors: |
Yang Zhou, Rui Yang, Yuan Wang, Meng Zhou, Xueyan Zhou, JiQing Xing, Xinxin Wang, Chunhui Zhang |
| Source: |
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-10 (2021) |
| Publisher Information: |
BMC, 2021. |
| Publication Year: |
2021 |
| Collection: |
LCC:Medical technology |
| Subject Terms: |
Rectal cancer, LNM, Multi-parametric magnetic resonance imaging, Histogram, Nomogram, Medical technology, R855-855.5 |
| More Details: |
Abstract Background Preoperative identification of rectal cancer lymph node status is crucial for patient prognosis and treatment decisions. Rectal magnetic resonance imaging (MRI) plays an essential role in the preoperative staging of rectal cancer, but its ability to predict lymph node metastasis (LNM) is insufficient. This study explored the value of histogram features of primary lesions on multi-parametric MRI for predicting LNM of stage T3 rectal carcinoma. Methods We retrospectively analyzed 175 patients with stage T3 rectal cancer who underwent preoperative MRI, including diffusion-weighted imaging (DWI) before surgery. 62 patients were included in the LNM group, and 113 patients were included in the non-LNM group. Texture features were calculated from histograms derived from T2 weighted imaging (T2WI), DWI, ADC, and T2 maps. Stepwise logistic regression analysis was used to screen independent predictors of LNM from clinical features, imaging features, and histogram features. Predictive performance was evaluated by receiver operating characteristic (ROC) curve analysis. Finally, a nomogram was established for predicting the risk of LNM. Results The clinical, imaging and histogram features were analyzed by stepwise logistic regression. Preoperative carbohydrate antigen 199 level (p = 0.009), MRN stage (p |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1471-2342 |
| Relation: |
https://doaj.org/toc/1471-2342 |
| DOI: |
10.1186/s12880-021-00706-0 |
| Access URL: |
https://doaj.org/article/60415aec794745b3805204f84b4a08a1 |
| Accession Number: |
edsdoj.60415aec794745b3805204f84b4a08a1 |
| Database: |
Directory of Open Access Journals |
