A Left Pulmonary Artery Sling in an Asymptomatic Adult Patient, A Case Report and Review of Literature.

Pulmonary artery sling (PAS) is a rare congenital vascular anomaly. Ninety percent of patients with PAS have respiratory distress and need surgical correction. Asymptomatic adult presentation of PAS is rare. We report the case of a 56-year-old female with an asymptomatic left pulmonary artery sling.

Application of Indirect Signs of Magnetic Resonance Imaging (MRI) in Prenatal Diagnosis of Abnormally Invasive Placenta.

BACKGROUND The aim of this study was to assess the value of indirect MRI signs in the prenatal diagnosis of abnormally invasive placenta (AIP). MATERIAL AND METHODS This study involved the retrospective analysis of indirect signs of 109 patients with AIP and 59 patients without AIP. The numbers of cases of placenta increta, accreta, and percreta confirmed by surgical and pathological results were 54, 19, and 36, respectively. The indirect signs included the following: dark intraplacental bands in T2WI sequence, focal outward bulging of the placenta, abnormal placental vascularity, and heterogeneous placental signal intensity. RESULTS There were significant differences in dark intraplacental bands in T2WI sequence, focal outward bulging of the placenta, and abnormal placental vascularity between the AIP and the non-AIP groups. There was no significant difference in dark intraplacental bands in T2WI sequence between the placenta percreta and increta groups, but there was a significant difference between the other 2 AIP groups and the placenta accreta group. Focal outward bulging of the placenta was significantly different between the percreta group and the placenta accreta group, but there was no significant difference between the other 2 AIP groups and the placenta increta group. There were no significant differences in abnormal placental vascularity among the3 subtypes of AIP. CONCLUSIONS The indirect signs of dark intraplacental bands in T2WI sequence, focal outward bulging of the placenta, and abnormal placental vascularity are reliable signs of AIP. The indirect sign of dark intraplacental bands in T2WI sequence may be used to distinguish placental accreta from the other 2 subtypes of AIP.

T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma.

BACKGROUND: The study on predicting the differentiation grade of colorectal cancer (CRC) based on magnetic resonance imaging (MRI) has not been reported yet. Developing a non-invasive model to predict the differentiation grade of CRC is of great value. AIM: To develop and validate machine learning-based models for predicting the differentiation grade of CRC based on T2-weighted images (T2WI). METHODS: We retrospectively collected the preoperative imaging and clinical data of 315 patients with CRC who underwent surgery from March 2018 to July 2023. Patients were randomly assigned to a training cohort (n = 220) or a validation cohort (n = 95) at a 7:3 ratio. Lesions were delineated layer by layer on high-resolution T2WI. Least absolute shrinkage and selection operator regression was applied to screen for radiomic features. Radiomics and clinical models were constructed using the multilayer perceptron (MLP) algorithm. These radiomic features and clinically relevant variables (selected based on a significance level of P < 0.05 in the training set) were used to construct radiomics-clinical models. The performance of the three models (clinical, radiomic, and radiomic-clinical model) were evaluated using the area under the curve (AUC), calibration curve and decision curve analysis (DCA). RESULTS: After feature selection, eight radiomic features were retained from the initial 1781 features to construct the radiomic model. Eight different classifiers, including logistic regression, support vector machine, k-nearest neighbours, random forest, extreme trees, extreme gradient boosting, light gradient boosting machine, and MLP, were used to construct the model, with MLP demonstrating the best diagnostic performance. The AUC of the radiomic-clinical model was 0.862 (95%CI: 0.796-0.927) in the training cohort and 0.761 (95%CI: 0.635-0.887) in the validation cohort. The AUC for the radiomic model was 0.796 (95%CI: 0.723-0.869) in the training cohort and 0.735 (95%CI: 0.604-0.866) in the validation cohort. The clinical model achieved an AUC of 0.751 (95%CI: 0.661-0.842) in the training cohort and 0.676 (95%CI: 0.525-0.827) in the validation cohort. All three models demonstrated good accuracy. In the training cohort, the AUC of the radiomic-clinical model was significantly greater than that of the clinical model (P = 0.005) and the radiomic model (P = 0.016). DCA confirmed the clinical practicality of incorporating radiomic features into the diagnostic process. CONCLUSION: In this study, we successfully developed and validated a T2WI-based machine learning model as an auxiliary tool for the preoperative differentiation between well/moderately and poorly differentiated CRC. This novel approach may assist clinicians in personalizing treatment strategies for patients and improving treatment efficacy.

Enhancing lymph node metastasis prediction in adenocarcinoma of the esophagogastric junction: A study combining radiomic with clinical features.

BACKGROUND: The incidence of adenocarcinoma of the esophagogastric junction (AEJ) is increasing, and with poor prognosis. Lymph node status (LNs) is particularly important for planning treatment and evaluating the prognosis of patients with AEJ. However, the use of radiomic based on enhanced computed tomography (CT) to predict the preoperative lymph node metastasis (PLNM) status of the AEJ has yet to be reported. PURPOSE: We sought to investigate the value of radiomic features based on enhanced CT in the accurate prediction of PLNM in patients with AEJ. METHODS: Clinical features and enhanced CT data of 235 patients with AEJ from October 2017 to May 2023 were retrospectively analyzed. The data were randomly assigned to the training cohort (n = 164) or the external testing cohort (n = 71) at a ratio of 7:3. A CT-report model, clinical model, radiomic model, and radiomic-clinical combined model were developed to predict PLNM in patients with AEJ. Univariate and multivariate logistic regression were used to screen for independent clinical risk factors. Least absolute shrinkage and selection operator (LASSO) regression was used to select the radiomic features. Finally, a nomogram for the preoperative prediction of PLNM in AEJ was constructed by combining Radiomics-score and clinical risk factors. The models were evaluated by area under the receiver operating characteristic curve (AUC-ROC), calibration curve, and decision curve analyses. RESULTS: A total of 181 patients (181/235, 77.02%) had LNM. In the testing cohort, the AUC of the radiomic-clinical model was 0.863 [95% confidence interval (CI) = 0.738-0.957], and the radiomic model (0.816; 95% CI = 0.681-0.929), clinical model (0.792; 95% CI = 0.677-0.888), and CT-report model (0.755; 95% CI = 0.647-0.840). CONCLUSION: The radiomic-clinical model is a feasible method for predicting PLNM in patients with AEJ, helping to guide clinical decision-making and personalized treatment planning.

Application value of preoperative dual-source computed tomography in assessing the rupture site of thoracic aortic dissection.

OBJECTIVE: To investigate the application value of dual-source computed tomography (DSCT) in preoperative assessment the rupture site of an thoracic aortic dissection (TAD). METHODS: A retrospective analysis of preoperative DSCT, multislice computed tomography (MSCT), and transthoracic echocardiography (TTE) results of 150 patients with suspected TAD in our hospital was conducted, and the intraoperative findings or interventional treatment results were used as the diagnostic gold standard. RESULTS: Of all 150 suspected TAD patients, 123 patients were confirmed to have TAD. The rupture site of TAD was in the ascending aorta in 46 patients, in the aortic arch in 13 patients, and in the descending aorta in 64 patients. The sensitivity of DSCT, MSCT, and TTE for locating the rupture site of the TAD was 100%, 93.5%, and 89.5%, respectively, and the specificity was 100%, 88.9%, and 81.5%. The differences were statistically significant. The distance between the actual rupture site and the one diagnosed by DSCT, MSCT, and TTE was 1.9 ± 1.2 mm, 5.1 ± 2.7 mm, and 7.8 ± 3.5 mm, respectively; the latter two were significantly worse than DSCT. The size of the rupture site diagnosed by DSCT, MSCT, and TTE was 1.5 ± 0.8 cm, 1.7 ± 0.9 cm, and 1.9 ± 1.0 cm, respectively. The size of the rupture site diagnosed by DSCT was not significantly different from the actual size of 1.4 ± 0.7 cm, while those by MSCT and TTE were. CONCLUSION: DSCT has high sensitivity and specificity in diagnosing the rupture site of TAD and can clearly locate the rupture site. It can be a preferred imaging method for TAD.

Myxofibrosarcoma of the scalp with difficult preoperative diagnosis: A case report and review of the literature.

BACKGROUND: A myxofibrosarcoma (MFS) is a malignant fibroblastic tumor that tends to occur in the lower and upper extremities. The reported incidence of head and neck MFSs is extremely rare. We report a 46-year-old male with "a neoplasm in the scalp" who was hospitalized and diagnosed with an MFS (highly malignant with massive necrotic lesions) based on histologic and immunohistochemistry evaluations. The magnetic resonance imaging manifestations did not demonstrate the "tail sign" mentioned in several studies, which resulted in a great challenge to establish an imaging diagnosis. The treatment plan is closely associated with the anatomic location and histologic grade, and more importantly, aggressive surgery and adjuvant radiotherapy may be helpful. Hence, we report the case and share some valuable information about the disease. CASE SUMMARY: A 46-year-old male with "a neoplasm in the scalp for 6 mo" was hospitalized. Initially, the tumor was about the size of a soybean, without algesia or ulceration. The patient ignored the growth, did not seek treatment, and thus, did not receive treatment. Recently, the tumor increased to the size of an egg; there was no bleeding or algesia. His family history was unremarkable. No abnormalities were found upon laboratory testing, including routine hematologic, biochemistry, and tumor markers. Computed tomography showed an ovoid mass (6.25 cm × 3.29 cm × 3.09 cm in size) in the left frontal scalp with low density intermingled with equidense strips in adjacent areas of the scalp. Magnetic resonance imaging revealed a lesion with an irregular surface and an approximate size of 3.55 cm × 6.34 cm in the left frontal region, with clear boundaries and visible separation. Adjacent areas of the skull were damaged and the dura mater was involved. Contrast enhancement showed an uneven enhancement pattern. Surgery was performed and postoperative adjuvant radiotherapy was administered to avoid recurrence or metastasis. The post-operative pathologic diagnosis confirmed an MFS. A repeat computed tomography scan showed no local recurrence or distant metastasis 19 mo post-operatively. CONCLUSION: The case reported herein of MFS was demonstrated in an extremely rare location on the scalp and had atypical magnetic resonance imaging findings, which serves as a reminder to radiologists of the possibility of this diagnosis to assist in clinical treatment. Given the special anatomic location and the high malignant potential of this rare tumor, combined surgical and adjuvant radiotherapy should be considered to avoid local recurrence and distant metastasis. The significance of regular follow-up is strongly recommended to improve the long-term survival rate.