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Background: Chest computed tomography (CT) is a critical tool in the diagnosis of pulmonary cryptococcosis as approximately 30% of normal immunity individuals may not exhibit any significant symptoms or laboratory findings. Pulmonary cryptococcosis granuloma and lung adenocarcinoma can appear similar on noncontrast chest CT. This study evaluates the use of an integrated model that was developed based on radiomic features combined with demographic and radiological features to differentiate pulmonary cryptococcosis nodules from lung adenocarcinomas. Methods: Preoperative chest CT images for 215 patients with solid pulmonary nodules with histopathologically confirmed lung adenocarcinoma and cryptococcosis infection were collected from two clinical centers (108 cases in the training set and 107 cases in the test set divided by the different hospitals). Radiomics models were constructed based on nodular lesion volume (LV), 5-mm extended lesion volume (ELV), and perilesion volume (PLV). A demoradiological model was constructed using logistic regression based on demographic information (age, sex) and 12 radiological features (location, number, shape and specific imaging signs). Both models were used to build an integrated model, the performance of which was assessed using the test set. A junior and a senior radiologist evaluated the nodules. Receiver operating characteristic (ROC) curve analysis was conducted, and areas under the curve (AUCs), sensitivity (SEN), and specificity (SPE) of the models were calculated and compared. Results: Among the radiomics models, AUCs of the LV, ELV, and PLV were 0.558, 0.757, and 0.470, respectively. Age, lesion number, and lobular sign were identified as independent discriminative features providing an AUC of 0.77 in the demoradiological model (SEN 0.815, SPE 0.642). The integrated model achieved the highest AUC of 0.801 (SEN 0.759, SPE 0.755), which was significantly higher than that obtained by a junior radiologist (AUC =0.689, P=0.024) but showed no significant difference from that of the senior radiologist (AUC =0.784, P=0.388). Conclusions: An integrated model with radiomics and demoradiological features improves discrimination of cryptococcosis granulomas from solid adenocarcinomas on noncontrast CT. This model may be an effective strategy for machine complementation to discrimination by radiologists, and whole-lung automated recognition methods might dominate in the future.
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Background: A profound understanding of the type of right middle lobe (RML) vein return is crucial for thoracic surgeons to ensure safe anatomic lung resection. In this study, the type of venous return in the RML and its clinical significance were analyzed using the 3D computed tomography (3D-CT) reconstruction technique. Methods: This retrospective study analyzed the patients who underwent anatomical lobectomy or anatomical lung segment resection with preoperative 3D-CT reconstruction at the Department of Thoracic Oncology Surgery, Fujian Cancer Hospital from January 2020 to October 2022. The exclusion criteria were as follows: (I) blurred CT images and inadequate IQQA 3D reconstruction for clear visualization of bronchial and vascular subsegmental branches; (II) patients with a previous history of right middle lobectomy; (III) incomplete medical records. Results: This study included 608 eligible cases, 245 males (40.30%) and 363 females (59.70%), with an average age of 58.61 years. We identified four major types of RML venous return, including 407 cases (66.94%) of central vein type, 123 cases (20.23%) of isolated vein type, 11 cases (1.81%) of basal vein type, and 67 cases (11.02%) of combined vein type. Furthermore, the central venous type comprised four subtypes: 191 cases (27.3%) had one branch, 165 cases (27.14%) had two branches, 43 cases (7.07%) had three branches, and 8 cases (1.32%) had more than three branches. The combined venous type includes four subtypes: combination type A (n=37 cases, 6.09%), combination type B (n=7 cases, 1.15%), combination type C (n=21 cases, 3.45%), and combination type D (n=2 cases, 0.33%). Conclusions: Based on 3D-CT reconstruction, numerous types of venous return in the RML were found, highlighting the significance of 3D-CT reconstruction for thoracic surgeons. It plays a crucial role in understanding the type of RML venous return prior to surgery, providing invaluable information to ensure surgical safety and success.
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Ongoing technologic and therapeutic advancements in medicine are now testing the limits of conventional anatomic imaging techniques. The ability to image physiology, rather than simply anatomy, is critical in the management of multiple disease processes, especially in oncology. Nuclear medicine has assumed a leading role in detecting, diagnosing, staging and assessing treatment response of various pathologic entities, and appears well positioned to do so into the future. When combined with computed tomography (CT) or magnetic resonance imaging (MRI), positron emission tomography (PET) has become the sine quo non technique of evaluating most solid tumors especially in the thorax. PET/CT serves as a key imaging modality in the initial evaluation of pulmonary nodules, often obviating the need for more invasive testing. PET/CT is essential to staging and restaging in bronchogenic carcinoma and offers key physiologic information with regard to treatment response. A more recent development, PET/MRI, shows promise in several specific lung cancer applications as well. Additional recent advancements in the field have allowed PET to expand beyond imaging with 18F-flurodeoxyglucose (FDG) alone, now with the ability to specifically image certain types of cell surface receptors. In the thorax this predominantly includes 68Ga-DOTATATE which targets the somatostatin receptors abundantly expressed in neuroendocrine tumors, including bronchial carcinoid. This receptor targeted imaging technique permits targeting these tumors with therapeutic analogues such as 177Lu labeled DOTATATE. Overall, the proper utilization of PET in the thorax has the ability to directly impact and improve patient care.