Purpose
To develop a support vector machine (SVM) classifier using CT texture-based analysis in differentiating focal-type autoimmune pancreatitis (AIP) and pancreatic duct carcinoma (PD), and to assess the radiologists’ diagnostic performance with or without SVM.
Materials and methods
This retrospective study included 50 patients (20 patients with focal-type AIP and 30 patients with PD) who underwent dynamic contrast-enhanced CT. Sixty-two CT texture-based features were extracted from 2D images of the arterial and portal phase CTs. We conducted data compression and feature selections using principal component analysis (PCA) and produced the SVM classifier. Four readers participated in this observer performance study and the statistical significance of differences with and without the SVM was assessed by receiver operating characteristic (ROC) analysis.
Results
The SVM performance indicated a high performance in differentiating focal-type AIP and PD (AUC = 0.920). The AUC for all 4 readers increased significantly from 0.827 to 0.911 when using the SVM outputs (p = 0.010). The AUC for inexperienced readers increased significantly from 0.781 to 0.905 when using the SVM outputs (p = 0.310). The AUC for experienced readers increased from 0.875 to 0.912 when using the SVM outputs, however, there was no significant difference (p = 0.018).
Conclusion
The use of SVM classifier using CT texture-based features improved the diagnostic performance for differentiating focal-type AIP and PD on CT.
Zero echo time (ZTE) sequence is recent advanced magnetic resonance technique that utilizes ultrafast readouts to capture signals from short‐T2 tissues. This sequence enables T2‐ and T2* weighted imaging of tissues with short intrinsic relaxation times by using an extremely short TE, and are increasingly used in the musculoskeletal system. We review the imaging physics of these sequences, practical limitations, and image reconstruction, and then discuss the clinical utilities in various disorders of the musculoskeletal system. ZTE can be readily incorporated into the clinical workflow, and is a promising technique to avoid unnecessary radiation exposure, cost, and time‐consuming by computed tomography in some cases.Level of Evidence4Technical EfficacyStage 1
Endometrioid carcinoma is the most common histological type of concurrent synchronous cancers of the uterus and ovary. Here we report a case of synchronous seromucinous carcinoma of the ovary and mucinous carcinoma of the endometrium with a literature review. A 51-year-old multiparous female complained of irregular bleeding and shortness of breath. Computed tomography revealed a large pelvic mass that consisted of cystic and solid components, a tumor of the endometrium, and a large amount of pleural effusion. An endometrial biopsy indicated adenocarcinoma, and adenocarcinoma cells were found in the pleural fluid. The patient with advanced ovarian cancer or endometrial cancer with massive pleural effusion received three courses of neoadjuvant chemotherapy (NAC) with paclitaxel and carboplatin followed by interval debulking surgery (IDS). The NAC was effective, and IDS was performed with no gross residual lesions. The post-operative diagnosis was seromucinous carcinoma of the ovary in FIGO (2014) stage IVA (ypT3cNxM1a) and mucinous carcinoma of the endometrium in FIGO (2008) stage IA (ypT1aNXM0). Three courses of postoperative TC therapy were performed, and maintenance therapy with Bevacizumab is ongoing. The patient is well without evidence of recurrence, sixteen months after surgery.
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