Introduction: A negative computed tomography (CT) scan does not preclude an insulinoma, as small lesions frequently remain undetected on conventional imaging. This case highlights the indispensable role of endoscopic ultrasound (EUS)— not just for localizing occult tumors, but as a definitive, minimally invasive therapeutic alternative to high-risk surgical resection. Case: A 39-year-old female with underlying hypertension presented with a 5-month history of predominantly fasting hypoglycemia (glucose <3.0 mmol/L) and neuroglycopenic symptoms, fulfilling Whipple’s triad. A supervised 72-hour fast confirmed endogenous hyperinsulinemic hypoglycemia at 31 hours, with a nadir glucose of 1.4 mmol/L, insulin 116 pmol/L, and C-peptide 821 pmol/L. Notably, contrastenhanced CT of the pancreas was reported as normal. To overcome this, EUS was performed, successfully identifying a hidden 19 × 18 mm lesion in the head of the pancreas, intimately abutting the main pancreatic duct. Despite medical therapy with diazoxide and strict dietary modifications, her hypoglycemia remained refractory. Given the tumor’s proximity to the main pancreatic duct, surgical enucleation carried a prohibitively high risk of complications. Consequently, she underwent EUS-guided radiofrequency ablation (RFA). Immediate post-procedure outcomes demonstrated near-complete resolution of the hypoglycemic episodes. Diazoxide was subsequently stopped. Outpatient continuous glucose monitoring confirmed sustained normoglycemia and marked symptom resolution, with no procedure-related complications. Conclusion The absence of a pancreatic lesion on CT demands persistent clinical suspicion in cases of biochemically proven hypoglycemia. EUS remains paramount for detecting occult lesions missed by standard imaging. Importantly, EUSRFA serves as a highly effective, tissue-sparing alternative to surgical resection for insulinomas, especially when conventional surgery poses prohibitive anatomical risks.
Insulinoma ; Tomography, X-Ray Computed

Introduction: Insulinoma is a rare functioning pancreatic neuroendocrine tumor and the most common cause of endogenous hyperinsulinemic hypoglycemia. Although biochemical confirmation is usually straightforward, tumor localization may be difficult when lesions are small and not detected on conventional cross-sectional imaging. In such cases, endoscopic ultrasound (EUS) plays an important role in identifying occult lesions and facilitating definitive treatment. Case: A 52-year-old female was admitted in April 2025 with recurrent seizures secondary to hypoglycemia for 3 years, with increasing frequency over time. She fulfilled Whipple’s triad, with documented capillary glucose of 1.8 mmol/L during an episode and symptom resolution following glucose administration. A supervised prolonged fasting test confirmed endogenous hyperinsulinemic hypoglycemia, with plasma glucose 1.4 mmol/L, insulin 122 pmol/L, and C-peptide 1,010 pmol/L. Short Synacthen test demonstrated adequate adrenal reserve. Due to persistent hypoglycemia, she required high-dose diazoxide. Contrast-enhanced computed tomography abdomen did not reveal a pancreatic lesion but incidentally detected a right ovarian teratoma. She underwent total abdominal hysterectomy and bilateral salpingo-oophorectomy in June 2025, with histopathology confirming a mature cystic teratoma without malignancy. However, hypoglycemic episodes persisted. Further evaluation with EUS in July 2025 identified a highly vascular isoechoic 8 × 8 mm lesion in the pancreatic body. Fine-needle biopsy confirmed a well-differentiated neuroendocrine tumor (WHO grade 1) with Ki-67 index of 2%. She subsequently underwent EUSguided radiofrequency ablation in August 2025. Follow-up EUS in December 2025 showed post-ablation change, and her hypoglycemic episodes resolved completely, allowing diazoxide to be discontinued. Conclusion This case highlights the diagnostic challenge of occult insulinoma in the presence of negative conventional imaging. EUS was pivotal for tumor localization and tissue diagnosis, while EUS-guided radiofrequency ablation provided effective minimally invasive treatment in a carefully selected patient.
Insulinoma ; Tomography, X-Ray Computed

OBJECTIVES: Renal cell carcinoma (RCC) is a malignant renal tumor that poses a significant threat to patient health. Accurate preoperative pathological grading plays a crucial role in determining the appropriate treatment for this disease. Currently, deep learning technology has become an important method for pathological grading of RCC. However, existing methods primarily rely on single-phase computed tomography (CT) imaging for analysis and prediction, which has limitations such as missing small lesions, one-sided evaluation, and local focusing issues. Therefore, this study proposes a multi-modal deep learning algorithm that integrates multi-phase enhanced CT images with clinical variable data, aiming to provide a basis for predicting the pathological grading of RCC. METHODS: First, the algorithm took four-phase enhanced CT images from the plain scan, arterial phase, venous phase, and delayed phase, along with clinical variables, as inputs. Then, an embedding encoding module was used to extract heterogeneous information from the clinical variables, and a 3-dimensional (3D) ResNet50 model was employed to capture spatial information from the multi-phase enhanced CT image data. Finally, a Fusion module deeply integrated the feature information from clinical variables and each phase's CT image features, further utilizing a cross-self-attention mechanism to achieve multi-phase feature fusion. This approach comprehensively captures the deep semantic information from the patient data, fully leveraging the complementary advantages of multi-modal and multi-phase data. To validate the effectiveness of the proposed method, a total of 1 229 RCC patients were approved by ethics review were included to train the model. RESULTS: Experimental results demonstrated superior performance compared to traditional radiomics and state-of-the-art deep learning methods, achieving an accuracy of 83.87%, a recall rate of 95.04%, and an F1-score of 82.23%. CONCLUSIONS The proposed algorithm exhibits strong stability and sensitivity, significantly enhancing the predictive performance of RCC pathological grading. It offers a novel approach for accurate RCC diagnosis and personalized treatment planning.
Humans ; Carcinoma, Renal Cell/pathology* ; Deep Learning ; Kidney Neoplasms/diagnostic imaging* ; Tomography, X-Ray Computed/methods* ; Algorithms ; Neoplasm Grading ; Male ; Female ; Middle Aged

OBJECTIVES: Non-small cell lung cancer (NSCLC) is associated with poor prognosis, with 30% of patients diagnosed at an advanced stage. Mutations in the EGFR and KRAS genes are important prognostic factors for NSCLC, and targeted therapies can significantly improve survival in these patients. Although tissue biopsy remains the gold standard for detecting gene mutations, it has limitations, including invasiveness, sampling errors due to tumor heterogeneity, and poor reproducibility. This study aims to develop machine learning models based on radiomic features to predict EGFR and KRAS gene mutation status in NSCLC patients, thereby providing a reference for precision oncology. METHODS: Imaging and mutation data from eligible NSCLC patients were obtained from the publicly available Lung-PET-CT-Dx dataset in The Cancer Imaging Archive (TCIA). A three-dimensional-convolutional neural network (3D-CNN) was used to extract imaging features from the regions of interest (ROI). The LightGBM algorithm was employed to build classification models for predicting EGFR and KRAS gene mutation status. Model performance was evaluated using 5-fold cross-validation, with receiver operator characteristic (ROC) curves, area under the curve (AUC), accuracy, sensitivity, and specificity used for validation. RESULTS: The models effectively predicted EGFR and KRAS mutations in NSCLC patients, achieving an AUC of 0.95 for EGFR mutations and 0.90 for KRAS. The models also demonstrated high accuracy (EGFR 89.66%; KRAS 87.10%), sensitivity (EGFR 93.33%; KRAS 87.50%), and specificity (EGFR 85.71%; KRAS 86.67%). CONCLUSIONS A radiogenomics-machine learning predictive model can serve as a non-invasive tool for anticipating EGFR and KRAS gene mutation status in NSCLC patients.
Humans ; Carcinoma, Non-Small-Cell Lung/diagnostic imaging* ; Lung Neoplasms/diagnostic imaging* ; Mutation ; Proto-Oncogene Proteins p21(ras)/genetics* ; ErbB Receptors/genetics* ; Machine Learning ; Positron Emission Tomography Computed Tomography ; Female ; Male ; Neural Networks, Computer ; Middle Aged ; Aged

Prostate cancer is the second most common cancer in men, accounting for 14.1% of new cancer cases in 2020. The aggressiveness of prostate cancer is highly variable, depending on its grade and stage at the time of diagnosis. Despite recent advances in prostate cancer treatment, some patients still experience recurrence or even progression after undergoing radical treatment. Accurate initial staging and monitoring for recurrence determine patient management, which in turn affect patient prognosis and survival. Classical imaging has limitations in the diagnosis and treatment of prostate cancer, but the use of novel molecular probes has improved the detection rate, specificity, and accuracy of prostate cancer detection. Molecular probe-based imaging modalities allow the visualization and quantitative measurement of biological processes at the molecular and cellular levels in living systems. An increased understanding of tumor biology of prostate cancer and the discovery of new tumor biomarkers have allowed the exploration of additional molecular probe targets. The development of novel ligands and advances in nano-based delivery technologies have accelerated the research and development of molecular probes. Here, we summarize the use of molecular probes in positron emission tomography (PET), single-photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), optical imaging, and ultrasound imaging, and provide a brief overview of important target molecules in prostate cancer.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Molecular Probes ; Molecular Imaging/methods* ; Magnetic Resonance Imaging ; Positron-Emission Tomography ; Tomography, Emission-Computed, Single-Photon ; Ultrasonography ; Optical Imaging ; Biomarkers, Tumor ; Precision Medicine/methods*

Objective:To explore the value of high resolution computed tomography（HRCT） combined with Magnetic Resonance Imaging（MRI） in the diagnosis of inner ear malformation. Methods:HRCT and MRI data of 82 patients with inner ear malformations were analyzed retrospectively. HRCT MPR and CPR reconstruction of the inner ear structure, facial nerve canal and oblique sagittal MRI reconstruction of the internal auditory canal were performed. The inner ear malformations were classified, the conditions of facial nerve canal and cochlear nerve were evaluated. The association between inner ear malformation and cochlear nerve dysplasia were analyzed by Chi-square test with continuity correction. Results:Among the 82 patients with inner ear malformations,there were 49 cases of bilateral symmetry, 11 cases of bilateral asymmetry and 22 cases of unilateral inner ear malformations. Respectively, the most prevalent types were IP-Ⅱ（42.96%）, dilatation of atrium aqueduct（18.31%） and malformations of atrium and semicircular canal 19.72%. Out of 50 cases of cochlear malformations,only 3 were isolated cochlear malformations, and the rest were accompanied by other malformations of varying degrees. In the 67 ears examined by MRI, 26（38.81%） had cochlear nerve deficiency（CND）, and the incidence of CND varied with different types of inner ear malformations. Out of 142 ears, 28（19.72%） had abnormalities of the facial nerve canal. Conclusion:HRCT combined with MRI can accurately distinguish the types of inner ear malformation and effectively evaluate the facial nerve canal and cochlear nerve, and further provides the important finger and Guide value for the clinician to formulate the reasonable treatment and the operation plan.
Humans ; Ear, Inner/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Retrospective Studies ; Female ; Male ; Tomography, X-Ray Computed/methods* ; Child ; Adolescent ; Adult ; Child, Preschool ; Cochlear Nerve/diagnostic imaging* ; Facial Nerve/abnormalities* ; Cochlea/abnormalities* ; Infant ; Young Adult

Objective:To explore the diagnosis and minimal invasive treatment of neonatal pyriform sinus fistula. Methods:A retrospective analysis was conducted on the clinical data of newborns diagnosed with pyriform sinus fistula in the Children's Hospital, Zhejiang University School of Medicine from January 2016 to December 2023, including the diagnostic process and treatment methods. Results:There were 8 children, 2 males and 6 females, with 7 cases on the left side and 1 case on the right side. Six cases revealed a lump in the fetal neck during prenatal examination, and two cases were found to have a neck mass after birth. All cases presented with varying degrees of respiratory disorders. After admission, all patients underwent neck ultrasound and contrast-enhanced CT examination. Neck ultrasound showed cystic masses, with 3 of the cysts accompanied by septa, and an air-fluid level was observed in the cysts in 6 cases from contrast-enhanced CT. All patients underwent ultrasound-guided neck mass puncture and/or tube placement combined with endoscopic electrocauterization. The cystic fluid was found to be yellow and thin, with no signs of infection. The surgical operations were uneventful, and the follow-up time ranged from 12 to 72 months postoperatively. There were no complications such as hoarseness, and no recurrence cases were reported. Conclusion:Neonatal pyriform sinus fistula is often characterized by a large cystic mass in the neck combined with respiratory depression. The presence of an air-fluid level in the cyst from contrast-enhanced CT can be considered an important basis for early diagnosis of pyriform sinus fistula. Ultrasound-guided puncture combined with endoscopic electrocauterization is minimally invasive and safe, making it a suitable minimal invasive treatment for neonatal pyriform sinus fistula.
Humans ; Female ; Male ; Pyriform Sinus/surgery* ; Retrospective Studies ; Infant, Newborn ; Cautery/methods* ; Endoscopy ; Fistula/surgery* ; Punctures ; Tomography, X-Ray Computed

Objective:To investigate the application value of intraoperative sliding rail computed tomography （CT） in complicated and difficult cochlear implantation by analyzing the cases of complicated and difficult cochlear implantation. Methods:The clinical data of patients with complicated and difficult cochlear implantation assisted by sliding rail CT were retrospectively analyzed, the intraoperative complications and the number of electrode adjustments were summarized, and the patients were followed up. Results:A total of 51 subjects were included in this study, including 46 patients with inner ear malformation, 2 patients with cochlear ossification, there were 7 patients underwent secondary scanning to adjust the electrode and achieved satisfactory implantation position. Conclusion:Intraoperative CT scanning is a reliable adjunctive tool for determining the placement of complex cochlear implantation, and it improves the accuracy of difficult cochlear implantation surgeries.
Humans ; Cochlear Implantation/methods* ; Retrospective Studies ; Tomography, X-Ray Computed ; Cochlear Implants ; Male ; Female ; Child, Preschool ; Child ; Cochlea ; Electrodes, Implanted ; Infant

Objective:To explore the influencing factors related to olfactory dysfunction secondary to different types of chronic rhinosinusitis（CRS）. Methods:A retrospective analysis was conducted on 185 CRS patients treated at the Department of Otolaryngology-Head and Neck Surgery of Shanxi Provincial People's Hospital from July 2023 to July 2024. Based on the presence or absence of nasal polyps, CRS was divided into two groups: chronic rhinosinusitis with nasal polyps（CRSwNP） and chronic rhinosinusitis without nasal polyps（CRSsNP）. Further, based on whether olfactory dysfunction was present, the CRSwNP and CRSsNP groups were divided into subgroups with olfactory dysfunction and normal olfaction. General data, laboratory tests, and modified sinus CT scores were compared between the subgroups. Logistic regression analysis was conducted to identify independent influencing factors based on the results of univariate analysis combined with clinical significance, and two nomogram models were established. The area under the curve of the receiver operating characteristic（ROC） curve, calibration curves, and decision curve analysis were used to assess the diagnostic performance, calibration, and clinical utility of the predictive model. Results:The proportion of blood eosinophils, blood urea nitrogen, and total modified CT scores of the bilateral olfactory region were identified as independent influencing factors in the CRSwNP group; the proportion of blood monocytes and modified CT scores of the bilateral posterior region were independent influencing factors in the CRSsNP group. The nomogram prediction model showed good diagnostic performance, calibration, and clinical utility in both the CRSwNP and CRSsNP groups. Conclusion:Olfactory dysfunction in CRSwNP patients is closely related to the proportion of blood eosinophils, blood urea nitrogen, and total modified CT scores of the bilateral olfactory region, while olfactory dysfunction in CRSsNP patients is closely related to the proportion of blood monocytes and modified CT scores of the bilateral posterior region. Moreover, the predictive model established in this study demonstrates good clinical performance and can be used for early identification and risk prediction of olfactory dysfunction secondary to CRS.
Humans ; Sinusitis/complications* ; Chronic Disease ; Retrospective Studies ; Olfaction Disorders/etiology* ; Nasal Polyps/complications* ; Rhinitis/complications* ; Female ; Male ; Logistic Models ; Middle Aged ; Smell ; Adult ; ROC Curve ; Nomograms ; Eosinophils ; Tomography, X-Ray Computed

Objective:To explore the clinical, imaging, and pathological features of glottic squamous cell carcinoma of the larynx and their relationship with prognosis. Methods:A retrospective analysis was conducted on the clinical, imaging, and pathological data of 130 patients with glottic squamous cell carcinoma of the larynx who were treated at the First People's Hospital of Yinchuan and the General Hospital of Ningxia Medical University from January 2018 to March 2023. Imaging examinations （CT and MRI） were used to evaluate the lesion boundary clarity, density, enhancement nature, and enhancement degree. Postoperative pathological examination was used to determine the pathological nature, immunohistochemistry, etc. Statistical methods such as χ² test, Spearman correlation analysis, multivariate logistic regression analysis, and Kaplan-Meier method were used to analyze the data. Results:Among the 130 patients, 127 were male and 3 were female, with an average age of （61.92±9.595） years. There was a correlation between clinical, imaging, and pathological features. Multivariate analysis showed that heterogeneous MRI density （OR=12.414;P=0.019） and squamous cell carcinoma as a subtype were correlated. The initial symptom of non-hoarseness （HR=6.045;P=0.010） and unclear MRI boundary （HR=12.559; P=0.029） were independent risk factors for poor prognosis in patients with glottic squamous cell carcinoma of the larynx. Conclusion:There is a correlation between the clinical, imaging, and pathological features of patients with glottic squamous cell carcinoma of the larynx, and they can affect prognosis. The initial symptom of non-hoarseness and unclear MRI boundary of the tumor are independent risk factors for poor prognosis.
Humans ; Laryngeal Neoplasms/diagnosis* ; Prognosis ; Male ; Female ; Retrospective Studies ; Middle Aged ; Carcinoma, Squamous Cell/diagnosis* ; Magnetic Resonance Imaging ; Glottis/pathology* ; Tomography, X-Ray Computed ; Aged