A retrospective analysis of simultaneous bilateral uniportal thoracoscopic surgeries for multiple primary bilateral pulmonary nodules.

BACKGROUND: There are no standard treatment options for bilateral multiple pulmonary nodules requiring resection. This study aimed to summarize the experience of simultaneous bilateral uniportal video-assisted thoracoscopic surgery for the treatment of bilateral multiple primary pulmonary nodules. METHODS: The clinical data of 65 cases of simultaneous bilateral uniportal thoracoscopic surgery for bilateral multiple primary pulmonary nodules treated were retrospectively analyzed. These cases were treated within The Ninth Medical Center of PLA General Hospital between January 2018 and November 2020. Parameters related to the surgery, perioperative aspects, surgical techniques, pathology results, and postoperative complications were examined. RESULTS: All surgeries were conducted through uniportal video-assisted thoracoscopic surgery, with no instances of intraoperative conversion to thoracotomy. Fifty-three patients further underwent CT-guided Hookwire localization for the localization of pulmonary nodules. A total of 189 nodules were resected using multiple surgical procedures, with a malignancy rate of 86.2%. The average operation time was 226 ± 77.4 min, the average thoracic drainage duration was 3.1 ± 1.5 days, the average 24 h pleural drainage was 385.9 ± 157.4 mL, the average postoperative hospital stay was 8.6 ± 2.4 days, and the average blood loss was 77.2 ± 33.8 mL. Post-surgery, all patients were transferred to the ward safely within 12 h. 15.38% of patients have prolonged drainage time, and 12.31% of patients experience complications such as lung infection, arrhythmia, and venous thrombosis. CONCLUSION: The selected cases undergoing simultaneous bilateral uniportal video-assisted thoracoscopic surgery for the management of bilateral multiple primary pulmonary nodules demonstrated favorable outcomes. Our observations indicate the safety and feasibility of this procedure, providing an individualized and precise treatment approach for affected patients.

A clinically applicable model more suitable for predicting malignancy or benignity of pulmonary ground glass nodules in women patients.

BACKGROUND: In recent years, clinicians often encounter patients with multiple pulmonary nodules in their clinical practices. As most of these ground glass nodules (GGNs) are small in volume and show no spicule sign, it is difficult to use Mayo Clinic Model to make early diagnosis of lung cancer accurately, especially in large numbers of nonsmoking women who have no tumor history. Other clinical models are disadvantaged by a relatively high false-positive or false-negative rate. Therefore, there is an urgent need to establish a new model of predicting malignancy or benignity of pulmonary GGNs for the sake of making accurate and early diagnosis of lung cancer. METHODS: Included in this study were GGNs surgically resected from patients who were admitted to Yiwu Central Hospital from January 2018 to March 2024, including both male and female patients, there is no gender specific issue. The nature of all these GGN tissues was confirmed pathologically. The case data were statistically analyzed to establish a mathematical prediction model, the prediction performance of which was verified by the pathological results. RESULTS: Altogether 261 GGN patients met the inclusion criteria. Using the results of logistic regression analysis, a mathematical prediction equation was established as follows: Malignant probability (mP) = ex/ (1 + ex); when mP was > 0.5, the GGN was considered as malignant, and when mP was ≤ 0.5, it was considered as benign. x= -2.46 + 1.032*gender + 1.85*mGGN + 1.40*VCS-0.0027*mean CT value of the nodule + 0.078*maximum diameter of the nodule, where e represents the natural logarithm; if the patient was a female, gender = 1 (otherwise = 0); if the pulmonary nodule was a mixed GGN, mGGN = 1 (otherwise = 0); if the pulmonary nodule had vascular convergence sign, VCS = 1 (otherwise = 0). The prediction performance of the mathematical prediction model was verified as follows: the negative prediction value was 0.97156 and the positive prediction value was 0.3800 in the model group versus 1 and 0.25 in the verification group. CONCLUSION: In this study, we identified female gender, mGGN, VCS, mean CT value and maximum nodule diameter as five key factors for predicting malignancy or benignity of pulmonary nodules, based on which we established a mathematical prediction model. This novel innovation may provide a useful auxiliary tool for predicting malignancy and benignity of pulmonary nodules, especially in women patients.

CT-guided microcoil versus hook-wire localization of pulmonary nodule prior to video-assisted thoracoscopic surgery without fluoroscopic guidance.

BACKGROUND: Both microcoils and hook-wires are commonly utilized for preoperative pulmonary nodule localization due to their convenience, but it remains unclear which one should be prioritized for recommendation. AIMS: To compare the safety and efficacy of microcoils and hook-wires for pulmonary nodule localization. METHODS: From January 2021 to December 2021, 310 consecutive patients (113 males and 197 females) with 341 pulmonary nodules who underwent CT-guided microcoil or hook-wire localization prior to video-assisted thoracoscopic surgery (VATS) at our center were retrospectively included in this study. There were 161 patients in the microcoil group and 149 patients in the hook-wire group. The successful localization rate, complication rate, radiation exposure, and medical costs were compared between the two groups. RESULTS: A total of 341 pulmonary nodules were localized, with a success rate of 99% (180/184) in the microcoil group and 93% (146/157) in the hook-wire group, respectively. All patients successfully underwent VATS. Multivariate analysis revealed that hook-wire localization, shorter needle depth into the lung tissue and the longer waiting time from localization to VATS were the risk factors for the localization failure. The incidences of pneumothorax in the microcoil group and hook-wire group were 34.8% (56/161) and 34.9% (52/149), respectively (P = 0.983). The incidences of pneumorrhagia were 13% (24/184) and 46.5% (73/157), respectively (P = 0.000). Multivariate analysis revealed that hook-wire localization and greater depth of needle penetration into lung tissue were risk factors for pneumorrhagia. CONCLUSION: Microcoil localization of pulmonary nodules is superior to hook-wire localization in terms of efficacy and safety. This finding provides insight into priority and broader promotion of microcoil localization.

The Value of Topological Radiomics Analysis in Predicting Malignant Risk of Pulmonary Ground-Glass Nodules: A Multi-Center Study.

BACKGROUND: Early detection and accurate differentiation of malignant ground-glass nodules (GGNs) in lung CT scans are crucial for the effective treatment of lung adenocarcinoma. However, existing imaging diagnostic methods often struggle to distinguish between benign and malignant GGNs in the early stages. This study aims to predict the malignancy risk of GGNs observed in lung CT scans by applying two radiomics methods: topological data analysis and texture analysis. METHODS: A retrospective analysis was conducted on 3223 patients from two centers between January 2018 and June2023. The dataset was divided into training, testing, and validation sets to ensure robust model development and validation. We developed topological features applied to GGNs using radiomics analysis based on homology. This innovative approach emphasizes the integration of topological information, capturing complex geometric and spatial relationships within GGNs. By combining machine learning and deep learning algorithms, we established a predictive model that integrates clinical parameters, previous radiomics features, and topological radiomics features. RESULTS: Incorporating topological radiomics into our model significantly enhanced the ability to distinguish between benign and malignant GGNs. The topological radiomics model achieved areas under the curve (AUC) of 0.85 and 0.862 in two independent validation sets, outperforming previous radiomics models. Furthermore, this model demonstrated higher sensitivity compared to models based solely on clinical parameters, with sensitivities of 80.7% in validation set 1 and 82.3% in validation set 2. The most comprehensive model, which combined clinical parameters, previous radiomics features, and topological radiomics features, achieved the highest AUC value of 0.879 across all datasets. CONCLUSION: This study validates the potential of topological radiomics in improving the predictive performance for distinguishing between benign and malignant GGNs. By integrating topological features with previous radiomics and clinical parameters, our comprehensive model provides a more accurate and reliable basis for developing treatment strategies for patients with GGNs.

Analytical validation of the LungLB test: a 4-color fluorescence in-situ hybridization assay for the evaluation of indeterminate pulmonary nodules.

BACKGROUND: Evaluation of indeterminate pulmonary nodules (IPNs) often creates a diagnostic conundrum which may delay the early detection of lung cancer. Rare circulating genetically abnormal cells (CGAC) have previously demonstrated utility as a biomarker for discriminating benign from malignant small IPNs in the LungLB assay. CGAC are identified using a unique 4-color fluorescence in-situ hybridization (FISH) assay and are thought to reflect early cell-based events in lung cancer pathogenesis and the anti-tumor immune response. LungLB is a prognostic tool that combines the CGAC biomarker and clinical features to aid in IPN evaluation by improving the stratification of patient risk of malignancy. METHODS: Herein we describe the analytical performance of the LungLB blood test. Analytical validation was performed according to Clinical and Laboratory Standards Institute (CLSI) guidelines with adaptations for rare cell-based assays. Multiple operators, reagent lots, and assay runs were tested to examine accuracy, precision, reproducibility, and interfering factors. RESULTS: The FISH probes used in the LungLB assay demonstrate 100% sensitivity and specificity for their intended chromosomal loci (3q29, 3p22.1, 10q22.3 and 10cen). LungLB demonstrates analytical sensitivity of 10 CGAC per 10,000 lymphocytes analyzed, 100% analytical specificity, and high linearity (R2 = 0.9971). Within run measurements across 100 samples demonstrated 96% reproducibility. Interfering factors normally found in blood (lipemia, biotin) and exposure to adverse temperatures (-20ºC or 37ºC) did not interfere with results. Sample stability was validated to 96 hours. CONCLUSION: The analytical performance of LungLB in this validation study successfully demonstrates it is robust and suitable for everyday clinical use.

Effects of tube voltage, radiation dose and adaptive statistical iterative reconstruction strength level on the detection and characterization of pulmonary nodules in ultra-low-dose chest CT.

OBJECTIVE: To explore the effects of tube voltage, radiation dose and adaptive statistical iterative reconstruction (ASiR-V) strength level on the detection and characterization of pulmonary nodules by an artificial intelligence (AI) software in ultra-low-dose chest CT (ULDCT). MATERIALS AND METHODS: An anthropomorphic thorax phantom containing 12 spherical simulated nodules (Diameter: 12 mm, 10 mm, 8 mm, 5 mm; CT value: -800HU, -630HU, 100HU) was scanned with three ULDCT protocols: Dose-1 (70kVp:0.11mSv, 100kVp:0.10mSv), Dose-2 (70kVp:0.34mSv, 100kVp:0.32mSv), Dose-3 (70kVp:0.53mSv, 100kVp:0.51mSv). All scanning protocols were repeated five times. CT images were reconstructed using four different strength levels of ASiR-V (0%=FBP, 30%, 50%, 70%ASiR-V) with a slice thickness of 1.25 mm. The characteristics of the physical nodules were used as reference standards. All images were analyzed using a commercially available AI software to identify nodules for calculating nodule detection rate (DR) and to obtain their long diameter and short diameter, which were used to calculate the deformation coefficient (DC) and size measurement deviation percentage (SP) of nodules. DR, DC and SP of different imaging groups were statistically compared. RESULTS: Image noise decreased with the increase of ASiR-V strength level, and the 70 kV images had lower noise under the same strength level (mean-value 70 kV: 40.14 ± 7.05 (dose 1), 27.55 ± 7.38 (dose 2), 23.88 ± 6.98 (dose 3); 100 kV: 42.36 ± 7.62 (dose 1); 30.78 ± 6.87 (dose 2); 26.49 ± 6.61 (dose 3)). Under the same dose level, there were no differences in DR between 70 kV and 100 kV (dose 1: 58.76% vs. 58.33%; dose 2: 73.33% vs. 70.83%; dose 3: 75.42% vs. 75.42%, all p > 0.05). The DR of GGNs increased significantly at dose 2 and higher (70 kV: 38.12% (dose 1), 60.63% (dose 2), 64.38% (dose 3); 100 kV: 37.50% (dose 1), 59.38% (dose 2), 66.25% (dose 3)). In general, the use of ASiR-V at higher strength levels (> 50%) and 100 kV provided better (lower) DC and SP. CONCLUSION: Detection rates are similar between 70 kV and 100 kV scans. The 70 kV images have better noise performance under the same ASiR-V level, while images of 100 kV and higher ASiR-V levels are better in preserving the nodule morphology (lower DC and SP); the dose levels above 0.33mSv provide high sensitivity for nodules detection, especially the simulated ground glass nodules.

GC-WIR : 3D global coordinate attention wide inverted ResNet network for pulmonary nodules classification.

PURPOSE: Currently, deep learning methods for the classification of benign and malignant lung nodules encounter challenges encompassing intricate and unstable algorithmic models, limited data adaptability, and an abundance of model parameters.To tackle these concerns, this investigation introduces a novel approach: the 3D Global Coordinated Attention Wide Inverted ResNet Network (GC-WIR). This network aims to achieve precise classification of benign and malignant pulmonary nodules, leveraging its merits of heightened efficiency, parsimonious parameterization, and robust stability. METHODS: Within this framework, a 3D Global Coordinate Attention Mechanism (3D GCA) is designed to compute the features of the input images by converting 3D channel information and multi-dimensional positional cues. By encompassing both global channel details and spatial positional cues, this approach maintains a judicious balance between flexibility and computational efficiency. Furthermore, the GC-WIR architecture incorporates a 3D Wide Inverted Residual Network (3D WIRN), which augments feature computation by expanding input channels. This augmentation mitigates information loss during feature extraction, expedites model convergence, and concurrently enhances performance. The utilization of the inverted residual structure imbues the model with heightened stability. RESULTS: Empirical validation of the GC-WIR method is performed on the LUNA 16 dataset, yielding predictions that surpass those generated by previous models. This novel approach achieves an impressive accuracy rate of 94.32%, coupled with a specificity of 93.69%. Notably, the model's parameter count remains modest at 5.76M, affording optimal classification accuracy. CONCLUSION: Furthermore, experimental results unequivocally demonstrate that, even under stringent computational constraints, GC-WIR outperforms alternative deep learning methodologies, establishing a new benchmark in performance.

Value of ultrathin bronchoscope in improving the endobronchial ultrasound localization rate and diagnosing peripheral pulmonary nodules by cryobiopsy.

BACKGROUND: A 3.0-mm ultrathin bronchoscope (UTB) with a 1.7-mm working channel provides better accessibility to peripheral bronchi. A 4.0-mm thin bronchoscope with a larger 2.0-mm working channel facilitates the use of a guide sheath (GS), ensuring repeated sampling from the same location. The 1.1-mm ultrathin cryoprobe has a smaller diameter, overcoming the limitation of the size of biopsy instruments used with UTB. In this study, we compared the endobronchial ultrasound localization rate and diagnostic yield of peripheral lung lesions by cryobiopsy using UTB and thin bronchoscopy combined with GS. METHODS: We retrospectively evaluated 133 patients with peripheral pulmonary lesions with a diameter less than 30 mm who underwent bronchoscopy with either thin bronchoscope or UTB from May 2019 to May 2023. A 3.0-mm UTB combined with rEBUS was used in the UTB group, whereas a 4.0-mm thin bronchoscope combined with rEBUS and GS was used for the thin bronchoscope group. A 1.1-mm ultrathin cryoprobe was used for cryobiopsy in the two groups. RESULTS: Among the 133 patients, peripheral pulmonary nodules in 85 subjects were visualized using r-EBUS. The ultrasound localization rate was significantly higher in the UTB group than in the thin bronchoscope group (96.0% vs. 44.6%, respectively; P < 0.001). The diagnostic yield of cryobiopsy specimens from the UTB group was significantly higher compared to the thin bronchoscope group (54.0% vs. 30.1%, respectively; p = 0.006). Univariate analysis demonstrated that the cryobiopsy diagnostic yields of the UTB group were significantly higher for lesions ≤ 20 mm, benign lesions, upper lobe lesions, lesions located lateral one-third from the hilum, and lesions without bronchus sign. CONCLUSIONS: Ultrathin bronchoscopy combined with cryobiopsy has a superior ultrasound localization rate and diagnostic yield compared to a combination of cryobiopsy and thin bronchoscopy.

Evaluation of the invasiveness of pure ground-glass nodules based on dual-head ResNet technique.

OBJECTIVE: To intelligently evaluate the invasiveness of pure ground-glass nodules with multiple classifications using deep learning. METHODS: pGGNs in 1136 patients were pathologically confirmed as lung precursor lesions [atypical adenomatous hyperplasia (AAH) and adenocarcinoma in situ (AIS)], minimally invasive adenocarcinoma (MIA), or invasive adenocarcinoma (IAC). Four different models [EfficientNet-b0 2D, dual-head ResNet_3D, a 3D model combining three features (3D_3F), and a 3D model combining 19 features (3D_19F)] were constructed to evaluate the invasiveness of pGGNs using the EfficientNet and ResNet networks. The Obuchowski index was used to evaluate the differences in diagnostic efficiency among the four models. RESULTS: The patients with pGGNs (360 men, 776 women; mean age, 54.63 ± 12.36 years) included 235 cases of AAH + AIS, 332 cases of MIA, and 569 cases of IAC. In the validation group, the areas under the curve in detecting the invasiveness of pGGNs as a three-category classification (AAH + AIS, MIA, IAC) were 0.8008, 0.8090, 0.8165, and 0.8158 for EfficientNet-b0 2D, dual-head ResNet_3D, 3D_3F, and 3D_19F, respectively, whereas the accuracies were 0.6422, 0.6158, 0.651, and 0.6364, respectively. The Obuchowski index revealed no significant differences in the diagnostic performance of the four models. CONCLUSIONS: The dual-head ResNet_3D_3F model had the highest diagnostic efficiency for evaluating the invasiveness of pGGNs in the four models.

Precision patient selection for improved detection of circulating genetically abnormal cells in pulmonary nodules.

Circulating genetically abnormal cells (CACs) have emerged as a promising biomarker for the early diagnosis of lung cancer, particularly in patients with pulmonary nodules. However, their performance may be suboptimal in certain patient populations. This study aimed to refine patient selection to improve the detection of CACs in pulmonary nodules. A retrospective analysis was conducted on 241 patients with pulmonary nodules who had undergone pathological diagnosis through surgical tissue specimens. Utilizing consensus clustering analysis, the patients were categorized into three distinct clusters. Cluster 1 was characterized by older age, larger nodule size, and a higher prevalence of hypertension and diabetes. Notably, the diagnostic efficacy of CACs in Cluster 1 surpassed that of the overall patient population (AUC: 0.855 vs. 0.689, P = 0.044). Moreover, for Cluster 1, an integrated diagnostic model was developed, incorporating CACs, sex, maximum nodule type, and maximum nodule size, resulting in a further improved AUC of 0.925 (95% CI 0.846-1.000). In conclusion, our study demonstrates that CACs detection shows better diagnostic performance in aiding the differentiation between benign and malignant nodules in older patients with larger pulmonary nodules and comorbidities such as diabetes and hypertension. Further research and validation are needed to explore how to better integrate CACs detection into clinical practice.

Comparison of electromagnetic navigation bronchoscopy localization and CT-guided percutaneous localization in resection of lung nodules: A protocol for systematic review and meta-analysis.

BACKGROUND: This study aimed to evaluate the efficacy and safety between electromagnetic navigational bronchoscopy (ENB) and computed tomography (CT)-guided percutaneous localization before resection of pulmonary nodules. METHODS: Pubmed, Embase, Web of Science, and the Cochrane Library databases were searched from January 1, 2000 to April 30, 2022, for relevant studies. Two reviewers conducted the search, selection, and extraction of data from eligible studies. The risk of bias was assessed using the Newcastle-Ottawa Scale. The primary outcome was the localization success rate, and the secondary outcomes were the pneumothorax incidence and localization time. The meta-analysis was performed by Review Manager 5.4. The protocol for the meta-analysis was registered on PROSPERO (Registration number: CRD42022345972). RESULTS: Five cohort studies comprising 441 patients (ENB group: 185, CT group: 256) were analyzed. Compared with the CT-guided group, the ENB-guided group was associated with lower pneumothorax incidence (relative ratio = 0.16, 95% confidence interval [CI]: 0.04-0.65, P = .01). No significant differences were found in location success rates (relative ratio = 1.01, 95% CI: 0.98-1.05, P = .38) and localization time (mean difference = 0.99, 95% CI: -5.73 to 7.71, P = .77) between the ENB group and CT group. CONCLUSION: Both ENB and CT-guided are valuable technologies in localizing lung nodules before video-assisted thoracoscopic surgery based on current investigations. ENB achieved a lower pneumothorax rate than the CT-guided group. In our opinion, there is no perfect method, and decision-making should be given the actual circumstances of each institute. Future prospective studies in the form of a randomized trial are needed to confirm their clinical value.

H-marker via bronchoscopy under LungPro navigation combined with cone-beam computed tomography for locating multiple pulmonary ground-glass nodules: A case report and literature review.

RATIONALE: Pulmonary ground-glass nodules (GGNs) pose challenges in intraoperative localization due to their primarily nonsolid composition. This report highlights a novel approach using H-marker deployment guided by LungPro navigation combined with cone-beam computed tomography (CBCT) for precise localization of multiple GGNs. PATIENT CONCERNS: A 55-year-old female patient presented at Sir-Run-Run-Shaw Hospital, Zhejiang University School of Medicine, in June 2021, requiring thoracoscopic surgery for the management of multiple GGNs in her right lung. She had a recent history of thoracoscopic wedge resection for a lesion in her lower left lung 3 months prior. DIAGNOSES: Computed tomography scans revealed the presence of 3 mixed GGNs in the right lung, with further confirmation identifying these as solitary pulmonary nodules, necessitating surgical intervention. INTERVENTIONS: The patient underwent thoracoscopic surgery, during which the multiple nodules in her right lung were precisely localized utilizing an H-marker implanted bronchoscopically under the guidance of LungPro navigation technology, with CBCT providing additional confirmation of nodule positioning. This innovative combination of technologies facilitated accurate targeting of the lesions. OUTCOMES: Postoperative histopathological analysis confirmed the nodules to be microinvasive adenocarcinomas. Radiographic examination with chest X-rays demonstrated satisfactory lung expansion, indicating effective lung function preservation following the procedure. Follow-up assessments have shown no evidence of tumor recurrence, suggesting successful treatment. LESSONS: The employment of H-marker implantation guided by the LungPro navigation system with CBCT confirmation presents a feasible and efficacious strategy for localizing multiple pulmonary GGNs. To further validate its clinical utility and safety, large-scale, multicenter, prospective studies are warranted. This approach holds promise in enhancing the precision and outcomes of surgeries involving GGNs.

Exploring experiences and coping strategies of the surveillance of indeterminate pulmonary nodules: a qualitative content analysis among participants in the SCAPIS trial.

OBJECTIVE: To elucidate experiences and coping strategies among adults in the surveillance of indeterminate pulmonary nodules detected with CT in the population-based Swedish CardioPulmonary bioImage Study (SCAPIS). DESIGN: A qualitative study of conventional content analysis. SETTINGS: The study was conducted at a university hospital in a southern region of Sweden. The SCAPIS setting is similar to the first round of a population-based lung cancer screening programme. PARTICIPANTS: Participants in SCAPIS who had experienced psychosocial consequences of the surveillance were eligible. Participants of both genders, current, former and non-smokers and of different follow-ups in the surveillance were included. Face-to-face semi-structured interviews with 19 participants were performed using an interview guide with open-ended questions. The participants were aged 56-68 years. Nine were women, 6 and 13 were non-smokers and smokers or former smokers, respectively, and all participants had undergone at least one follow-up of the lungs in the surveillance programme. RESULTS: The results depicted an emotional and mental journey for the participants from being distressed when informed about the need of surveillance, and realising their risks of getting sick if they did not take care of their own health, to eventually gathering the strength to cope with the situation, so the surveillance was finally valued with trust and satisfaction. The experiences and coping strategies in the surveillance programme developed a revelation of the value of health consciousness among the participants. CONCLUSION: The study results demonstrated that a surveillance programme of pulmonary nodules might develop health consciousness among people. Still, some individuals might experience psychosocial consequences of the surveillance of indeterminate nodules. Therefore, healthcare professionals should be facilitated to perform person-centred communication to support individuals under surveillance. Preventive care to engage individuals as partners in the management of their own health should receive more attention and needs to be explored.

The scoring system combined with radiomics and imaging features in predicting the malignant potential of incidental indeterminate small (<20 mm) solid pulmonary nodules.

OBJECTIVE: Develop a practical scoring system based on radiomics and imaging features, for predicting the malignant potential of incidental indeterminate small solid pulmonary nodules (IISSPNs) smaller than 20 mm. METHODS: A total of 360 patients with malignant IISSPNs (n = 213) and benign IISSPNs (n = 147) confirmed after surgery were retrospectively analyzed. The whole cohort was randomly divided into training and validation groups at a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) algorithm was used to debase the dimensions of radiomics features. Multivariate logistic analysis was performed to establish models. The receiver operating characteristic (ROC) curve, area under the curve (AUC), 95% confidence interval (CI), sensitivity and specificity of each model were recorded. Scoring system based on odds ratio was developed. RESULTS: Three radiomics features were selected for further model establishment. After multivariate logistic analysis, the combined model including Mean, age, emphysema, lobulated and size, reached highest AUC of 0.877 (95%CI: 0.830-0.915), accuracy rate of 83.3%, sensitivity of 85.3% and specificity of 80.2% in the training group, followed by radiomics model (AUC: 0.804) and imaging model (AUC: 0.773). A scoring system with a cutoff value greater than 4 points was developed. If the score was larger than 8 points, the possibility of diagnosing malignant IISSPNs could reach at least 92.7%. CONCLUSION: The combined model demonstrated good diagnostic performance in predicting the malignant potential of IISSPNs. A perfect accuracy rate of 100% can be achieved with a score exceeding 12 points in the user-friendly scoring system.

Impact of artificial intelligence assistance on pulmonary nodule detection and localization in chest CT: a comparative study among radiologists of varying experience levels.

The study aimed to evaluate the impact of AI assistance on pulmonary nodule detection rates among radiology residents and senior radiologists, along with assessing the effectiveness of two different commercialy available AI software systems in improving detection rates and LungRADS classification in chest CT. The study cohort included 198 participants with 221 pulmonary nodules. Residents' mean detection rate increased significantly from 64 to 77% with AI assist, while seniors' detection rate remained largely unchanged (85% vs. 86%). Residents showed significant improvement in segmental nodule localization with AI assistance, seniors did not. Software 2 slightly outperformed software 1 in increasing detection rates (67-77% vs. 80-86%), but neither significantly affected LungRADS classification. The study suggests that clinical experience mitigates the need for additional AI software, with the combination of CAD with residents being the most beneficial approach. Both software systems performed similarly, with software 2 showing a slightly higher but non-significant increase in detection rates.

Growth dynamics of lung nodules: implications for classification in lung cancer screening.

BACKGROUND: Lung nodules observed in cancer screening are believed to grow exponentially, and their associated volume doubling time (VDT) has been proposed for nodule classification. This retrospective study aimed to elucidate the growth dynamics of lung nodules and determine the best classification as either benign or malignant. METHODS: Data were analyzed from 180 participants (73.7% male) enrolled in the I-ELCAP screening program (140 primary lung cancer and 40 benign) with three or more annual CT examinations before resection. Attenuation, volume, mass and growth patterns (decelerated, linear, subexponential, exponential and accelerated) were assessed and compared as classification methods. RESULTS: Most lung cancers (83/140) and few benign nodules (11/40) exhibited an accelerated, faster than exponential, growth pattern. Half (50%) of the benign nodules versus 26.4% of the malignant ones displayed decelerated growth. Differences in growth patterns allowed nodule malignancy to be classified, the most effective individual variable being the increase in volume between two-year-interval scans (ROC-AUC = 0.871). The same metric on the first two follow-ups yielded an AUC value of 0.769. Further classification into solid, part-solid or non-solid, improved results (ROC-AUC of 0.813 in the first year and 0.897 in the second year). CONCLUSIONS: In our dataset, most lung cancers exhibited accelerated growth in contrast to their benign counterparts. A measure of volumetric growth allowed discrimination between benign and malignant nodules. Its classification power increased when adding information on nodule compactness. The combination of these two meaningful and easily obtained variables could be used to assess malignancy of lung cancer nodules.

Prevalence of pulmonary nodules detected incidentally on noncancer-related imaging: a review.

Pulmonary nodules are common incidental findings requiring surveillance. Follow-up recommendations vary depending on risk factors, size and solid or subsolid characteristics. This review aimed to evaluate the prevalence of clinically significant nodules detected on noncancer-dedicated imaging and the prevalence of part-solid and ground-glass nodules. We conducted a systematic search of literature and screened texts for eligibility. Clinically significant nodules were noncalcified nodules >4-6 mm. Prevalence estimates were calculated for all studies and risk of bias was assessed by one reviewer. Twenty-four studies were included, with a total of 30 887 participants, and 21 studies were cross-sectional in design. Twenty-two studies used computed tomography (CT) imaging with cardiac-related CT being the most frequent. Prevalence of significant nodules was highest in studies with large field of view of the chest and low size thresholds for reporting nodules. The prevalence of part-solid and ground-glass nodules was only described in two cardiac-related CT studies. The overall risk of bias was low in seven studies and moderate in 17 studies. While current literature frequently reports incidental nodules on cardiovascular-related CT, there is minimal reporting of subsolid characteristics. Unclear quantification of smoking history and heterogeneity of imaging protocol also limits reliable evaluation of nodule prevalence in nonscreening cohorts.

Expert consensus on the multidisciplinary diagnosis and treatment of multiple ground glass nodule-like lung cancer (2024 Edition).

ABSTRACT: This expert consensus reviews current literature and provides clinical practice guidelines for the diagnosis and treatment of multiple ground glass nodule-like lung cancer. The main contents of this review include the following: ① follow-up strategies, ② differential diagnosis, ③ diagnosis and staging, ④ treatment methods, and ⑤ post-treatment follow-up.

Non-invasive diagnosis of pulmonary nodules by circulating tumor DNA methylation: A prospective multicenter study.

BACKGROUND: With the popularization of computed tomography, more and more pulmonary nodules (PNs) are being detected. Risk stratification of PNs is essential for detecting early-stage lung cancer while minimizing the overdiagnosis of benign nodules. This study aimed to develop a circulating tumor DNA (ctDNA) methylation-based, non-invasive model for the risk stratification of PNs. METHODS: A blood-based assay ("LUNG-TRAC") was designed to include novel lung cancer ctDNA methylation markers identified from in-house reduced representative bisulfite sequencing data and known markers from the literature. A stratification model was trained based on 183 ctDNA samples derived from patients with benign or malignant PNs and validated in 62 patients. LUNG-TRAC was further single-blindly tested in a single- and multi-center cohort. RESULTS: The LUNG-TRAC model achieved an area under the curve (AUC) of 0.810 (sensitivity = 74.4 % and specificity = 73.7 %) in the validation set. Two test sets were used to evaluate the performance of LUNG-TRAC, with an AUC of 0.815 in the single-center test (N = 61; sensitivity = 67.5 % and specificity = 76.2 %) and 0.761 in the multi-center test (N = 95; sensitivity = 50.7 % and specificity = 80.8 %). The clinical utility of LUNG-TRAC was further assessed by comparing it to two established risk stratification models: the Mayo Clinic and Veteran Administration models. It outperformed both in the validation and the single-center test sets. CONCLUSION: The LUNG-TRAC model demonstrated accuracy and consistency in stratifying PNs for the risk of malignancy, suggesting its utility as a non-invasive diagnostic aid for early-stage peripheral lung cancer. CLINICAL TRIAL REGISTRATION: www. CLINICALTRIALS: gov (NCT03989219).

Peritumoral radiomics increases the efficiency of classification of pure ground-glass lung nodules: a multicenter study.

PURPOSE: We aimed to evaluate the efficiency of computed tomography (CT) radiomic features extracted from gross tumor volume (GTV) and peritumoral volumes (PTV) of 5, 10, and 15 mm to identify the tumor grades corresponding to the new histological grading system proposed in 2020 by the Pathology Committee of the International Association for the Study of Lung Cancer (IASLC). METHODS: A total of 151 lung adenocarcinomas manifesting as pure ground-glass lung nodules (pGGNs) were included in this randomized multicenter retrospective study. Four radiomic models were constructed from GTV and GTV + 5/10/15-mm PTV, respectively, and compared. The diagnostic performance of the different models was evaluated using receiver operating characteristic curve analysis RESULTS: The pGGNs were classified into grade 1 (117), 2 (34), and 3 (0), according to the IASLC grading system. In all four radiomic models, pGGNs of grade 2 had significantly higher radiomic scores than those of grade 1 (P < 0.05). The AUC of the GTV and GTV + 5/10/15-mm PTV were 0.869, 0.910, 0.951, and 0.872 in the training cohort and 0.700, 0.715, 0.745, and 0.724 in the validation cohort, respectively. CONCLUSIONS: The radiomic features we extracted from the GTV and PTV of pGGNs could effectively be used to differentiate grade-1 and grade-2 tumors. In particular, the radiomic features from the PTV increased the efficiency of the diagnostic model, with GTV + 10 mm PTV exhibiting the highest efficacy.