The diagnostic value of CT-based radiomics nomogram for solitary indeterminate smoothly marginated solid pulmonary nodules.

Objectives: This study aimed to explore the value of radiomics nomogram based on computed tomography (CT) on the diagnosis of benign and malignant solitary indeterminate smoothly marginated solid pulmonary nodules (SMSPNs). Methods: This study retrospectively reviewed 205 cases with solitary indeterminate SMSPNs on CT, including 112 cases of benign nodules and 93 cases of malignant nodules. They were divided into training (n=143) and validation (n=62) cohorts based on different CT scanners. Radiomics features of the nodules were extracted from the lung window CT images. The variance threshold method, SelectKBest, and least absolute shrinkage and selection operator were used to select the key radiomics features to construct the rad-score. Through multivariate logistic regression analysis, a nomogram was built by combining rad-score, clinical factors, and CT features. The nomogram performance was evaluated by the area under the receiver operating characteristic curve (AUC). Results: A total of 19 radiomics features were selected to construct the rad-score, and the nomogram was constructed by the rad-score, one clinical factor (history of malignant tumor), and three CT features (including calcification, pleural retraction, and lobulation). The nomogram performed better than the radiomics model, clinical model, and experienced radiologists who specialized in thoracic radiology for nodule diagnosis. The AUC values of the nomogram were 0.942 in the training cohort and 0.933 in the validation cohort. The calibration curve and decision curve showed that the nomogram demonstrated good consistency and clinical applicability. Conclusion: The CT-based radiomics nomogram achieved high efficiency in the preoperative diagnosis of solitary indeterminate SMSPNs, and it is of great significance in guiding clinical decision-making.

A Fully Automated Deep-Learning Model for Predicting the Molecular Subtypes of Posterior Fossa Ependymomas Using T2-Weighted Images.

PURPOSE: We aimed to develop and validate a deep learning (DL) model to automatically segment posterior fossa ependymoma (PF-EPN) and predict its molecular subtypes [Group A (PFA) and Group B (PFB)] from preoperative MR images. EXPERIMENTAL DESIGN: We retrospectively identified 227 PF-EPNs (development and internal test sets) with available preoperative T2-weighted (T2w) MR images and molecular status to develop and test a 3D nnU-Net (referred to as T2-nnU-Net) for tumor segmentation and molecular subtype prediction. The network was externally tested using an external independent set [n = 40; subset-1 (n = 31) and subset-2 (n =9)] and prospectively enrolled cases [prospective validation set (n = 27)]. The Dice similarity coefficient was used to evaluate the segmentation performance. Receiver operating characteristic analysis for molecular subtype prediction was performed. RESULTS: For tumor segmentation, the T2-nnU-Net achieved a Dice score of 0.94 ± 0.02 in the internal test set. For molecular subtype prediction, the T2-nnU-Net achieved an AUC of 0.93 and accuracy of 0.89 in the internal test set, an AUC of 0.99 and accuracy of 0.93 in the external test set. In the prospective validation set, the model achieved an AUC of 0.93 and an accuracy of 0.89. The predictive performance of T2-nnU-Net was superior or comparable to that of demographic and multiple radiologic features (AUCs ranging from 0.87 to 0.95). CONCLUSIONS: A fully automated DL model was developed and validated to accurately segment PF-EPNs and predict molecular subtypes using only T2w MR images, which could help in clinical decision-making.

"Soap bubble" sign as an imaging marker for posterior fossa ependymoma Group B.

PURPOSE: To investigate the predictive value of the "soap bubble" sign on molecular subtypes (Group A [PFA] and Group B [PFB]) of posterior fossa ependymomas (PF-EPNs). METHODS: MRI scans of 227 PF-EPNs (internal retrospective discovery set) were evaluated by two independent neuroradiologists to assess the "soap bubble" sign, which was defined as clusters of cysts of various sizes that look like "soap bubbles" on T2-weighted images. Two independent cohorts (external validation set [n = 31] and prospective validation set [n = 27]) were collected to validate the "soap bubble" sign. RESULTS: Across three datasets, the "soap bubble" sign was observed in 21 PFB cases (7.4% [21/285] of PF-EPNs and 12.9% [21/163] of PFB); none in PFA. Analysis of the internal retrospective discovery set demonstrated substantial interrater agreement (1st Rating: κ = 0.71 [0.53-0.90], 2nd Rating: κ = 0.83 [0.68-0.98]) and intrarater agreement (Rater 1: κ = 0.73 [0.55-0.91], Rater 2: κ = 0.74 [0.55-0.92]) for the "soap bubble" sign; all 13 cases positive for the "soap bubble" sign were PFB (p = 0.002; positive predictive value [PPV] = 100%, negative predictive value [NPV] = 44%, sensitivity = 10%, specificity = 100%). The findings from the external validation set and the prospective validation set were similar, all cases positive for the "soap bubble" sign were PFB (p < 0.001; PPV = 100%). CONCLUSION: The "soap bubble" sign represents a highly specific imaging marker for the PFB molecular subtype of PF-EPNs.

Tumour-pleura relationship on CT is a risk factor for occult lymph node metastasis in peripheral clinical stage IA solid adenocarcinoma.

OBJECTIVES: To investigate whether the tumour-pleura relationship on computed tomography (CT) is a risk factor for occult lymph node metastasis (OLNM) in peripheral clinical stage IA solid adenocarcinoma. METHODS: A total of 232 patients were included in the study. The tumour-pleura relationship was divided into four types: type 1, the tumour was unrelated to the pleura; type 2, the tumour was not in contact with the pleura, and one or more linear or striated pleural tags were visible; type 3, the tumour was not in contact with the pleura, and one or more linear or striated pleural tags with soft tissue component at the pleural end were visible; and type 4, the tumour was in contact with the pleura. Univariate and multivariate logistic regression analyses were used to identify the predictive factors, including the tumour-pleura relationship, clinical factors, conventional CT findings, and pathology-reported visceral pleural invasion, for OLNM. RESULTS: Type 3 and 4 tumour-pleura relationships were more likely to have visceral pleural invasion than type 1 and 2 tumour-pleura relationships (p < 0.001). Univariate and multivariate logistic regression analyses revealed that the type 3 or 4 tumour-pleura relationship (OR: 3.261, p = 0.026), carcinoembryonic antigen level (OR: 3.361, p = 0.006), cytokeratin 19 fragments level (OR: 2.539, p = 0.025), and mediastinal window tumour size (OR: 1.078, p = 0.020) were predictive factors for OLNM. CONCLUSIONS: The type 3 or 4 tumour-pleura relationship is correlated with a greater risk of OLNM in peripheral clinical stage IA solid adenocarcinoma. KEY POINTS: • The tumour-pleura relationship on CT is a risk factor for occult lymph node metastasis in peripheral clinical stage IA solid adenocarcinoma. • Other risk factors for OLNM include CEA level, CYFRA level, and mediastinal window tumour size. • Pathology-reported visceral pleural invasion is not a risk factor for OLNM.

CT-Based Radiomics Nomogram for Differentiation of Anterior Mediastinal Thymic Cyst From Thymic Epithelial Tumor.

OBJECTIVES: This study aimed to distinguish preoperatively anterior mediastinal thymic cysts from thymic epithelial tumors via a computed tomography (CT)-based radiomics nomogram. METHODS: This study analyzed 74 samples of thymic cysts and 116 samples of thymic epithelial tumors as confirmed by pathology examination that were collected from January 2014 to December 2020. Among the patients, 151 cases (scanned at CT 1) were selected as the training cohort, and 39 cases (scanned at CT 2 and 3) served as the validation cohort. Radiomics features were extracted from pre-contrast CT images. Key features were selected by SelectKBest and least absolute shrinkage and selection operator and then used to build a radiomics signature (Rad-score). The radiomics nomogram developed herein via multivariate logistic regression analysis incorporated clinical factors, conventional CT findings, and Rad-score. Its performance in distinguishing the samples of thymic cysts from those of thymic epithelial tumors was assessed via discrimination, calibration curve, and decision curve analysis (DCA). RESULTS: The radiomics nomogram, which incorporated 16 radiomics features and 3 conventional CT findings, including lesion edge, lobulation, and CT value, performed better than Rad-score, conventional CT model, and the clinical judgment by radiologists in distinguishing thymic cysts from thymic epithelial tumors. The area under the receiver operating characteristic (ROC) curve of the nomogram was 0.980 [95% confidence interval (CI), 0.963-0.993] in the training cohort and 0.992 (95% CI, 0.969-1.000) in the validation cohort. The calibration curve and the results of DCA indicated that the nomogram has good consistency and valuable clinical utility. CONCLUSION: The CT-based radiomics nomogram presented herein may serve as an effective and convenient tool for differentiating thymic cysts from thymic epithelial tumors. Thus, it may aid in clinical decision-making.

Differentiating Glioblastoma from Primary Central Nervous System Lymphoma: The Value of Shaping and Nonenhancing Peritumoral Hyperintense Gyral Lesion on FLAIR Imaging.

BACKGROUND: This study describes a distinct magnetic resonance imaging (MRI) feature, placing emphasis on fluid-attenuation inversion recovery (FLAIR) and contrast-enhanced T1-weighted (T1C) images for the preoperative differentiation of glioblastoma (GBM) from primary central nervous system lymphoma (PCNSL). METHODS: The preoperative MRI findings of 116 pathologically confirmed glioblastoma (n = 72) and PCNSL (n = 44) were retrospectively reviewed. Two neuroimaging specialists analyzed the MRIs, and image analysis was focused on the presence or absence of a shaping and nonenhancing peritumoral hyperintense gyral lesion on FLAIR imaging (SNEPGF, i.e., hyperintense lesion in a shaping and nonenhancing peritumoral gyral area on FLAIR imaging). The gyral area adjacent to and within 3 cm of the enhanced tumor was defined as the peritumoral gyrus region. The FLAIR hyperintensity lesion were termed as the signal intensity ratio ≥30% compared with contralateral normal gray matter. Then, the differential diagnostic efficacy of SNEFPG sign for GBM and PCNSL was analyzed. RESULTS: The SNEPGF sign was found in 33 GBM cases (33 of 72, 45.8%), and the FLAIR signal intensity and apparent diffusion coefficient value of these area were lower than the peritumoral edema area (P < 0.0001). In 44 PCNSL cases, no SNEPGF sign was found. A slightly higher FLAIR signal intensity was seen in 9 PCNSLs, but uniform and marked enhancement was seen in these areas. The sensitivity, specificity, positive predictive value, and negative predictive value of the differential diagnosis of GBM and PCNSL with SNEPGF sign were 45.8%, 100%, 100%, and 53.0%, respectively. CONCLUSIONS: The SNEPGF sign is effective in identifying GBM from PCNSL, especially with high specificity.

The diagnostic value of TROP-2, SLP-2 and CD56 expression in papillary thyroid carcinoma.

OBJECTIVE: The study aimed to explore some novel diagnostic biomarkers for papillary thyroid carcinoma (PTC) by identifying the different expression of TROP-2, SLP-2 and CD56 in benign and malignant thyroid lesions. METHODS: We evaluated the mRNA expressions of TROP-2 and SLP-2 in fine needle aspirates (FNAs) which contained 10 PTCs and 10 benign follicular adenomas (FAs) using quantitative real-time PCR (qRT-PCR). Immunohistochemical (IHC) staining of TROP-2, SLP-2 and CD56 was also performed on postoperative samples of 30 PTCs and 29 FAs. Membranous or cytoplasmic staining in > 10% of cells was considered as positive. Diagnostic sensitivity, specificity, positive predictive value, negative predictive value (NPV) and diagnostic accuracy of these three biomarkers were carried out. We further analyzed the associations between the clinical features and the expressions of markers in PTCs. RESULTS: The mRNA expressions of both TROP-2 and SLP-2 were increased substantially in PTCs in comparison with those in FAs (P < 0.05). Similarly, IHC for these two proteins demonstrated higher positive staining in PTCs than in FAs (96.5% vs. 12.5% for TROP-2, 83.3% vs. 20.7% for SLP-2, P < 0.05). Conversely, CD56 expression was lost with 86.7% of PTCs. In identifying malignancy, TROP-2 was the most sensitive marker and CD56 was the most specific one. When the markers were combined, the sensitivity and NPV increased to 100% and had better diagnostic accuracy. However, no association was found between biomarker expressions and clinicopathological factors in PTCs. CONCLUSIONS: We found that TROP-2, SLP-2 and CD56 were effective diagnostic markers for PTC, especially when they were combined to use.

Evaluation of computed tomography vascular reconstruction for the localization diagnosis of perigastric mass.

BACKGROUND: The aim of this study was to evaluate the utility of computed tomography (CT) vascular reconstruction in the localization diagnosis of perigastric mass. METHODS: Fifty-eight patients with pathologically detected perigastric mass underwent abdominal dynamic contrast-enhanced CT. CT vascular reconstructions were produced from arterial phase data using volume rendering (VR), multiplanar reconstruction (MPR), and maximal intensity projection (MIP). Image analysis was focused on the relationship between the mass, perigastric arteries, and the gastric wall. Localization diagnosis values were compared between CT vascular reconstruction and dynamic-enhanced CT images. RESULTS: Among the 58 cases of perigastric mass, 41 cases originated from the stomach, 7 cases from the left liver lobe, 6 from the pancreas, 2 from lessor omental bursa, 1 from transverse mesocolon, and 1 from left adrenal gland. The accuracy of CT vascular reconstruction images in the localization diagnosis of perigastric mass was higher than that of dynamic-enhanced CT images (98.3% and 86.2%, respectively, P = .04). On the reference level, 35 (35/41) patients with stomach-originated masses showed the mass adjacent perigastric arteries pushed away from the stomach (arterial displacement sign), and 15 (15/17) patients with nonstomach-originated masses showed perigastric arteries between the mass and the stomach (arterial entrapment sign). The sensitivity, specificity, positive predictive value, and negative predictive value of the localization diagnosis of perigastric mass with arterial displacement sign were 85.4%, 100%, 100%, and 73.9%, respectively, and with arterial entrapment sign, 88.2%, 100%, 100%, and 95.3%, respectively. CONCLUSION: CT vascular reconstruction can clearly depict the relationship between perigastric mass and adjacent perigastric arteries, which may help us more accurately differentiate between stomach-originated and nonstomach-originated masses compared with original dynamic-enhanced CT images.

A myeloid sarcoma involving the small intestine, kidneys, mesentery, and mesenteric lymph nodes: A case report and literature review.

RATIONALE: Myeloid sarcomas (MSs) are rare malignant hematological tumors. They most commonly occur in patients with acute or chronic myeloid leukemia. A de novo MS with no evidence of blood system disease is rare, but may represent the first sign of a systemic illness that precedes a full-blown disease. Herein, we report the computed tomography (CT) findings of an extremely rare case of a nonleukemic MS that progressed to acute myelogenous leukemia (AML) and simultaneously involved the small intestine, kidneys, mesentery, and mesenteric lymph nodes. Moreover, we provide CT findings before and after AML chemotherapy, which have not been reported previously. PATIENT CONCERNS: A 25-year-old man with intermittent upper abdominal pain for 6 months was admitted to the hospital on November 28, 2015. Initial CT showed concentric wall thickening of the jejunum with an adjacent mesenteric soft tissue mass and mesenteric lymph nodes enlargement. Both kidneys were involved as indicated by the presence of well-defined mildly dilated lesions. During the laparoscopic surgery, the small intestinal tumor, mesenteric soft tissue mass, and mesenteric lymph nodes were removed. DIAGNOSES: The pathological diagnosis was an MS. INTERVENTIONS: The patient refused systemic chemotherapy and was rehospitalized with persistently aggravated abdominal distension on February 17, 2016. Follow-up CT showed diffuse small bowel wall thickening, widespread infiltration of the peritoneum, omentum, and mesentery, mesenteric lymph node enlargement, and large amounts of ascites fluid. The lesions in both kidneys were substantially larger and more numerous than on initial CT. Then the patient was treated with conventional AML chemotherapy. OUTCOMES: The patient achieved complete hematological remission on bone marrow examination. Follow-up CT in September 4, 2016, showed none of the abnormalities seen on initial CT. Currently, the patient is in complete remission. LESSONS: If the radiological examination shows lesions at multiple sites, and these lesions are soft tissue masses with homogenous enhancement, MS should be considered in the differential diagnosis, and an aspiration biopsy should be performed to provide a definitive pathological diagnosis. If MS is diagnosed, systemic chemotherapy is crucial to recovery; otherwise, the disease may progress rapidly. Medical imaging is helpful for diagnosing MS and for monitoring treatment response.

[Applications of blood oxygenation level dependent-functional magnetic resonance imaging, diffusion tensor imaging and intraoperative neurophysiology monitoring in secondary epileptic surgery in M1 area].

OBJECTIVE: To explore the applications of blood oxygenation level dependent-functional magnetic resonance imaging (BOLD-fMRI), diffusion tensor imaging (DTI) and cortical somatosensory evoked potentials (Co-SEP), motor evoked potentials (MEP) and electrocorticogram (ECoG) in secondary epileptic surgery of primary motor area (M1). METHODS: In 19 patients, preoperative BOLD-fMRI were performed to display the relationship between active zone, fiber bundle and epileptogenic lesions. Besides, Co-SEP, MEP and ECoG were also carried out intra-operatively to direct the resection of epileptogenic lesion and epileptogenic focus. At the same time, the nervous functions were protected as much as possible. Then fMRI was performed again to ensure that the post-operative nervous function was excellent. RESULTS: In preoperative BOLD-fMRI and DTI examinations, active zone and fiber bundle could be seen at the edge of lesions (n = 12); range reduced, become deformed or removed (n = 6); glioma epileptogenic lesion was close-up with M1 (n = 1). The central sulcus was confirmed by Co-SEP in all cases. And two cases were inconsistent with anatomical location; Stimulating precentral gyrus, MEP were elicited post-operatively from orbicularis oris, muscle of thenar, hypothenar muscle or flexor digitorum brevis. Under the monitoring of ECoG, spike-wave was monitored in all cases. Of these, epileptogenic focus was in M1 (n = 15). After treatment, spike-wave were reduced significantly or disappeared. At a post-operative follow-up of 6 - 12 months, seizure improvement has achieved Engel III level or above (n = 18). On re-examinations of BOLD-fMRI and DTI, active zone became bigger than before and fiber bundle was symmetric with opposite side. Two of 19 cases had transient motor aphasia incompletely or hemiparesis. No permanent neurological dysfunction occurred. There was no relapse in cases of glioma. CONCLUSION: BOLD-fMRI and Co-SEP, MEP and ECoG are complementary in M1 of secondary epilepsy surgery. It is effective to preserve nervous functions and enhance the quality of life for patients with epilepsy.