Suspicious Lung Lesions Research Articles

Feasibility and Impact on Diagnosis of Peripheral Pulmonary Lesions under Real-Time Direct Vision by Iriscope®

Plain Language SummaryThis study explores a new tool called the Iriscope®, which helps doctors see lung lesions in real time during procedures. Lung lesions are areas in the lungs that may be affected by disease, including cancer. Early detection and accurate diagnosis are crucial for effective treatment. In our research, we tested the Iriscope® on 70 patients with suspicious lung lesions. The Iriscope® allowed doctors to see the lesions directly, helping them take precise samples for diagnosis. This tool provided a clear view of more than half of the lung lesions and helped accurately diagnose 92.5% of these cases. Common observations made using the Iriscope® included thicker mucosal linings, increased blood vessel presence, pale or gray tissue, blockages with mucus buildup, and uneven mucosal surfaces. These detailed images helped doctors understand the nature of the lesions better without using radiation or taking more time during procedures. Overall, the Iriscope® shows promise as a helpful addition to lung cancer diagnosis, offering real-time, detailed images that can lead to better patient outcomes.

Diagnostic potential of protein serum biomarkers for distinguishing small and non-small cell lung cancer in patients with suspicious lung lesions

Background Biomarkers play a role in identifying, managing, and predicting cancer outcomes. In lung cancer, they are used at various time points. Doubts remain regarding their accuracy for differential diagnosis and histological subtyping. A diagnostic test study was conducted. It included malignant lesions and controls with benign lesions. Before lung biopsy, all patients had the following biomarkers measured in serum (Pro-GRP,NSE,CYFRA21-1,SCC-Ag,CEA). Methods The predictive capacity of serum biomarkers was evaluated to discriminate between lung cancer and benign pathology. The accuracy was also assessed for distinguishing between SCLC and NSCLC and explored their ability to perform histological subtyping. Results 93 patients were included, 60 with lung cancer, 33 with benign pathology. Pro-GRP and NSE were elevated in SCLC compared with NSCLC or nonmalignant disease. The most accurate for differentiating between malignant and benign pathology were CEA and CYFRA21-1. Pro-GRP had a poor predictive capacity for distinguishing NSCLC from SCLC. However, combined with CEA and CYFRA21-1, performance improved. For SCLC, the diagnostic capacity of Pro-GRP increased by combining with biomarkers, such as NSE/CYFRA21–1. Conclusions Biomarkers lacked the sensitivity and specificity for independent differential diagnosis or histological subtyping. However, the observed patterns in biomarker levels associated with specific histological subtypes suggest potential utility in a multi-biomarker approach or in conjunction with other diagnostic tools. This insight could guide future research to improve diagnostic accuracy and personalized treatment strategies in lung cancer.

Optimized Deep Learning Algorithm for Predicting Pulmonary Nodules in CT Images

Lung cancer remains a significant global health challenge, demanding early detection for improved patient outcomes. In recent years, deep learning, notably Convolutional Neural Networks (CNNs), has emerged as a potent tool for lung cancer detection and diagnosis from medical imaging data. This research offers an extensive review of CNN-based approaches for lung cancer detection, highlighting their strengths, limitations, and potential clinical impact. The study discusses the methodology, covering data collection, preprocessing, model architecture selection, training, evaluation, and validation, alongside future directions and clinical implications. CNNs offer researchers and healthcare professionals avenues to augment early detection, personalized treatment planning, and ultimately, enhance patient care in lung cancer management. Through rigorous development and evaluation, CNN models trained on diverse datasets of chest X-rays or CT scans have demonstrated remarkable accuracy in identifying suspicious lung lesions indicative of cancer, often outperforming conventional methods. The proposed study utilizes the GoogleNet (Inception v1) CNN model to detect lung cancer. The performance of GoogleNet improved the accuracy of detection by approximately 4.29% compared to existing methods.

PET/CT-aided biopsy of lung lesions enhances diagnostic efficacy, especially for lesions >3cm.

The purpose of this study was to compare the diagnostic efficacy of PET/CT-aided CT-guided and routine CT-guided transthoracic needle biopsy for lung lesions. A total of 458 patients with suspicious lung lesions were referred for CT-guided biopsy, with 227 patients assigned to the PET/CT group and 231 patients assigned to the CT group. The clinical characteristics and diagnostic yield were compared between the two groups. Furthermore, conducting subgroup analysis to evaluate the differences of diagnostic success or failure between the two groups. The sensitivity and diagnostic accuracy rate differed significantly (P = 0.035, P = 0.048). In the PET/CT group, the values were 95.7% and 96.3%, respectively, while in the CT group, they were 90.1% and 91.9%. When considering non-diagnostic cases, the overall diagnostic success rate increased markedly in PET/CT group (93.0% vs. 83.1%, P = 0.001). In our subgroup analysis, the PET/CT group demonstrated superiority in detecting lesions larger than 3 cm (OR, 4.81; 95CI%, 2.03 - 11.36), while showing a moderate effect in lesions smaller than 3 cm (OR, 1.09; 95CI%, 0.42 - 2.81). Significant effect modification was observed in large lesions in the PET/CT group (P for interaction = 0.023). 18F-FDG-PET/CT enhances the diagnostic efficacy of CT-guided transthoracic needle biopsy for lung lesions, and the incremental value can be modified by lesion size, particularly when the diameter is larger than 3 cm.

Two Birds with One Stone: Hepatocellular Carcinoma and Small Cell Lung Cancer Imaged with [18F]Fluorocholine Positron Emission Tomography/Computed Tomography.

We describe the case of a 67-year-old male patient with a moderately differentiated hepatocellular carcinoma (HCC) of the right liver lobe who underwent [18F]fluorocholine positron emission tomography/computed tomography (PET/CT) for staging due to a suspicious lung lesion at previous CT scan. [18F]fluorocholine PET/CT showed increased radiopharmaceutical uptake in a liver lesion corresponding to the known HCC. Furthermore, a right pulmonary hilar lesion suspicious for metastatic spread of HCC showed increased radiopharmaceutical uptake. Surprisingly, the histological assessment of the thoracic lesion demonstrated the presence of small cell lung cancer (SCLC). The patient underwent treatment with radiation therapy and chemotherapy for the SCLC and selective internal radiation therapy (SIRT) for the HCC. The patient died after one year due to progressive SCLC. This case demonstrates that coexisting tumors showing increased cell membrane turnover, including SCLC, can be detected by [18F]fluorocholine PET/CT. In our case, [18F]fluorocholine PET/CT findings influenced the patient management in terms of histological verification and different treatment of the detected lesions.

Incidental discovery of second primary malignancies in patients diagnosed with breast cancer: An institutional case series.

e12552 Background: National guidelines recommend tissue biopsy of suspected recurrent breast cancer, to confirm diagnosis and to characterize disease phenotype, receptor status, and molecular markers. Despite this, clinicians frequently rely on imaging alone to diagnose recurrent breast cancer; indeed, our group recently published data revealing that only half of patients in Washington state diagnosed with metastatic breast cancer between 2008 and 2017 underwent confirmatory biopsies for suspected metastatic disease on imaging. Here we present evidence of how this failure to fully evaluate suspected breast cancer recurrence could potentially lead to misdiagnosis. Methods: We surveyed our breast medical oncology faculty to identify patients treated at Fred Hutchinson Cancer Center (FHCC) from 2018 to 2022 in which a second primary carcinoma (not including non-melanoma skin cancers) was discovered as part of breast cancer workup and treatment. Results: We identified 10 cases of second primary diagnoses. Of these, the majority (7/10) were lung cancer; other diagnoses included neuroendocrine tumors (1), chronic lymphocytic leukemia (1), and thyroid cancer (1). In the case of lung cancers, patients were typically diagnosed during staging or CT evaluation for radiation or reconstruction, in which a pulmonary nodule raised suspicion for malignancy. In five cases, patients were treated with curative intent for both of their early-stage primary malignancies, and remain disease-free on endocrine therapy alone. In two cases, patients with biopsy-proven metastatic breast cancer were found to have new suspicious lung lesions, which on biopsy were found to represent lung adenocarcinoma; these patients were treated surgically for their lung cancer and continued long-term therapy for metastatic breast cancer. Conclusions: While imaging can raise strong suspicion for metastatic recurrence of breast cancer, the assumption that an apparently metastatic lesion 1) indeed represents metastasis and 2) represents metastatic spread of the known primary rather than another malignancy, risks treating both the primary tumor and the newly detected condition inappropriately. Biopsy is critical for confirmation of metastatic disease vs second primary or other etiology. As patients with metastatic breast cancer are surviving longer as our cancer-directed therapies improve, appropriate diagnostic measures for a suspicious non-breast malignancy are recommended for optimal care. Novel imaging modalities such as 18F-fluoroestradiol (FES) PET and others could be explored in discriminating between metastatic lesions and unrelated conditions.

Suspicious lung lesions for malignancy: the lesion-to-spinal cord signal intensity ratio in T2WI and DWI–MRI versus PET/CT; a prospective pathologic correlated study with accuracy and ROC analyses

BackgroundThe multi-detector computed tomography (MDCT) and tissue biopsy are the gold standards for the evaluation of lung malignancies. However, there is a wide range of pulmonary indeterminate lesions that could mimic lung cancer. Furthermore, the diagnosis of malignancy could be challenging if the lesion is small and early presenting by a part-solid or ground-glass nodule or if surrounded by parenchymal lung reaction with consolidation and atelectasis. The previous literature focused on the role of diffusion-weighted image–magnetic resonance imaging (DWI) and the apparent diffusion coefficient (ADC) mapping in the evaluation of lung malignancy. A novel quantitative T2 assessment is provided and tested in this study. Aim of the work: To evaluate the accuracy of specific non-invasive quantitative magnetic resonance imaging (MRI) parameters in the characterization of suspicious lung lesions and the discrimination between the malignant and benign nature. They included the lesion-to-spinal cord signal intensity ratio in T2-WI and DWI as well as the mean and minimum apparent diffusion coefficient (ADC) values. This is performed using a prospective pathologic correlated study with receiver-operating characteristics (ROC) analysis and comparison with positron emission tomography (PET-CT) accuracy results.ResultsThis study was prospectively performed during the period between June/2021 and June/2022. It was conducted on 43 suspicious lung lesions detected by MDCT. MRI and PET/CT examinations were performed for all patients, and the results were compared to the final diagnosis obtained after biopsy and pathological assessment, using the statistical tests of significance and P-value. Cutoff values were automatically calculated, and then, accuracy tests and ROC analyses were performed. Five expert radiologists and a single consulting pulmonologist participated in this study. The inter-rater reliability ranges between good and excellent with the intra-class correlation coefficient (ICC) ranging between 0.85 and 0.94. In T2-WI: The lesion-to-spinal cord signal intensity ratio was higher in the malignant group (1.35 ± 0.29) than in the benign group (0.88 ± 0.40), (P < 0.001). At the estimated cutoff value (> 1), the sensitivity was 96.43%, the specificity was 80.00%, and AUC = 0.86. In b500-DWI: The lesion-to-spinal cord signal intensity ratio was higher in the malignant group (0.70–1.35) than in the benign group (0.20–0.70) (P < 0.001). At the estimated cutoff value (> 0.7), the sensitivity was 71.43%, the specificity was 86.67%, and AUC = 0.86. The mean and minimum ADC values were lower in the malignant group (0.6–1.3 and 0.3–1.1 × 10–3 mm2/s) than the benign group (1–1.6 and 0.7–1.4 × 10–3 mm2/s), (P < 0.01 and < 0.001, respectively). At their estimated cutoff values (≤ 1.2 and ≤ 0.9 × 10–3 mm2/s, respectively), the sensitivity was (71.4 and 85.7%), specificity was (83.3 and 66.7%), respectively, and AUC = 0.77 for both. PET/CT had 96.4% sensitivity, 92.3% specificity, and AUC = 0.94.ConclusionsPET-CT remains the most specific and sensitive tool for the differentiation between benign and malignant lesions. The lesion-to-cord signal intensity ratios in T2WI and DWI-MRI and to a minor extent the mean and minimum ADC values are also considered good parameters for this differentiation based on their accurate statistical results, particularly if PET/CT was not available or feasible. The study added to the previous literature a novel quantitative T2WI assessment which proved a high sensitivity equal to PET/CT with a lower but a good specificity. The availability, expertise, time factor, and patients' tolerance remain challenging factors for MRI.

Lung cancer screening: The pulmonologist, the thoracic surgeon and working together in a team.

Lung cancer screening: The pulmonologist, the thoracic surgeon and working together in a team.

Electrical Impedance Analysis for Lung Cancer: A Prospective, Multicenter, Blind Validation Study.

HypothesisPatients with cancer have different impedances or conductances than patients with benign normal tissue; thus, we can apply electrical impedance analysis (EIA) to identify patients with cancer.MethodTo evaluate EIA’s efficacy and safety profile in diagnosing pulmonary lesions, we conducted a prospective, multicenter study among patients with pulmonary lesions recruited from 4 clinical centers (Zhongshan Hospital Ethics Committee, Approval No. 2015-16R and 2017-035(3). They underwent EIA to obtain an Algorithm Composite Score or ‘Prolung Index,’ PI. The classification threshold of 29 was first tested in an analytical validation set of 144 patients and independently validated in a clinical validation set of 418 patients. The subject’s final diagnosis depended on histology and a 2-year follow-up.ResultsIn total, 418 patients completed the entire protocol for clinical validation, with 186 true positives, 145 true negatives, 52 false positives, and 35 false negatives. The sensitivity, specificity, and diagnostic yield were 84% (95% CI 79.3%-89.0%), 74% (95% CI 67.4%-79.8%), and 79% (95%CI 75.3%-83.1%), respectively, and did not differ according to age, sex, smoking history, body mass index, or lesion types. The sensitivity of small lesions was comparable to that of large lesions (p = 0.13). Four hundred eighty-four patients who underwent the analysis received a safety evaluation. No adverse events were considered to be related to the test.ConclusionElectrical impedance analysis is a safe and efficient tool for risk stratification of pulmonary lesions, especially for patients with a suspicious lung lesion.

The role of radiology in addressing the challenge of lung cancer after lung transplantation.

The importance of lung cancer as a complication of lung transplantation is increasingly recognised. It may become an important survival-limiting factor in lung transplant patients as management of other complications continues to improve and utilisation of extended criteria donors grows. Radiology can play a key role in tackling this issue at multiple stages in the transplantation pathway and follow-up process. Routine chest CT as part of pre-transplant recipient assessment (and donor assessment if available) can identify suspicious lung lesions with high sensitivity and detect chronic structural lung diseases such as pulmonary fibrosis associated with an increased risk of malignancy post-transplant. Pre-transplant CT also provides a comparison for later CT studies in the assessment of nodules or masses. The potential role of regular chest CT for lung cancer screening after transplantation is less certain due to limited available evidence on its efficacy. Radiologists should be cognisant of how the causes of pulmonary nodules in lung transplant patients may differ from the general population, vary with time since transplantation and require specific recommendations for further investigation/follow-up as general guidelines are not applicable. As part of the multidisciplinary team, radiology is involved in an aggressive diagnostic and therapeutic management approach for nodular lung lesions after transplant both through follow-up imaging and image-guided tissue sampling. This review provides a comprehensive overview of available clinical data and evidence on lung cancer in lung transplant recipients, and in particular an assessment of the current and potential roles of pre- and post-transplant imaging. KEY POINTS: • Lung cancer after lung transplantation may become an increasingly important survival-limiting factor as mortality from other complications declines. • There are a number of important roles for radiology in tackling the issue which include pre-transplant CT and supporting an aggressive multidisciplinary management strategy where lung nodules are detected in transplant patients. • The introduction of routine surveillance chest CT after transplant in addition to standard clinical follow-up as a means of lung cancer screening should be considered.

Clinical Implication of Borderline CT-Morphological Metastatic Spread in Bladder Cancer: What You See Is Not Always What You Got

Introduction: Palliative radical cystectomy (pRC) may be offered to selected bladder cancer (BC) patients with grievous local symptoms. However, there is only scarce information on perioperative complications and prognosis, especially in the case of metastatic spread. We intended to analyze morbidity and oncological outcome in this patient subgroup. Materials: Patients undergoing pRC because of BC with radiologic evidence of metastases were included in this retrospective study. Perioperative adverse events (AEs) were graded by the Clavien-Dindo Classification system. All patients underwent CT-based surveillance, and questionnaires were sent for survival follow-up in predefined intervals. Oncological outcome and predictive markers were assessed in univariate and multivariate analyses, using log-rank tests and Cox-regression analyses. Results: Between 2004 and 2016, 77 patients were identified. Median age at surgery was 70 years (IQR 66–77) and the median follow-up time was 12 months (IQR 4–44). Preoperative staging revealed pulmonary, hepatic, bone, peritoneal, and various other metastasis in 46/77 (60%), 14/77 (18%), 11/77 (14%), 5/77 (7%), and 11/77 (14%) cases, respectively. Most frequently observed symptoms at the time of pRC were severe gross hematuria (n = 41) and intense pain (n = 11). Most AEs were of minor grade (83%). The median length of stay was 20 days. Median CSS was 13 months with a 5-year CSS of 34%. Intriguingly and unsuspectedly, preoperatively suspicious lung lesions were confirmed during surveillance only in 33%, respectively. In multivariate analysis, intraoperative blood transfusions (HR = 2.25, 95% CI: 1.09–4.63, p = 0.028) were significantly associated with decreased CSS. The best outcome was observed in patients with only subpleural metastases (CSS 80 months, p = 0.039) and normal CRP- and Hb values. Conclusion: pRC can be performed with acceptable perioperative morbidity and mortality. Pulmonary lesions seem to have a risk of false-positive results and should be biopsied in all uncertain cases. Localization of lung metastases together with preoperative CRP- and Hb levels seem to play a prognostic role.

Postoperative computed tomography of insufflated lung specimens obtained by video-assisted thoracic surgery: detection and margin assessment of pulmonary nodules.

ObjectiveTo investigate the utility of computed tomography (CT) scans to detect and assess the margin status of pulmonary nodules that were insufflated after being resected by video-assisted thoracic surgery.Materials and MethodsThis was a novel multicenter study conducted at two national referral centers for thoracic diseases. Patients suspected of having lung cancer underwent video-assisted thoracic surgery for the resection of pulmonary nodules, which were submitted to postoperative CT. Measurements from the CT scans were compared with the results of the histopathological analysis.ResultsA total of 37 pulmonary nodules from 37 patients were evaluated. The mean age of the patients was 65 years (range, 36-84 years), and 27 (73%) were female. A CT analysis of insufflated specimens identified all 37 nodules, and 33 of those nodules were found to have tumor-free margins. The histopathological analysis revealed lung cancer in 30 of the nodules, all with tumor-free margins, and benign lesions in the seven remaining nodules.ConclusionPostoperative CT of insufflated suspicious lung lesions provides real-time detection of pulmonary nodules and satisfactory assessment of tumor margins. This initial study shows that CT of insufflated lung lesions can be a valuable tool at centers where intraoperative histopathological analysis is unavailable.

Magnetic resonance-guided repeat biopsy of suspicious malignant lung lesions after an initial negative computed tomography-guided Biopsy.

This study sought to establish the diagnostic utility of performing a second biopsy using an magnetic resonance (MR)-guided percutaneous transthoracic needle biopsy (PTNB) approach in patients with suspicious malignant lung lesions that had already undergone an initial negative computed tomography (CT)-guided biopsy. This study evaluated 31 patients with suspicious lung lesions (18 males, 13 females; mean age: 62.1 ± 11.3 years) that had previously undergone CT-guided PTNB with negative pathological findings January 2015-November 2020. A final histopathological diagnosis was made based on resected lung lesion specimens or, when resection was not conducted, on clinical diagnosis following a ≥6-month follow-up. The diagnostic accuracy of MR-guided secondary lung biopsy was determined by comparing the lung biopsy results for each patient to their final diagnosis. 1.0T open MR-guided secondary lung biopsy was performed for 31 lesions (20 central, 11 peripheral; mean size, 5.3 ± 2.0 cm). The pathological results revealed 20/31 (64.5%) lesions to be malignant (14 adenocarcinoma, 4 squamous cell carcinoma, and 2 small-cell lung cancer) as detected by 1.0T open MR-guided PTNB and confirmed by surgical pathology and clinical follow-up. There were three instances of biopsy-induced complications including hemorrhage in 6.5% of the patients (2/31) and pneumothorax in 3.2% of the patients (1/31). No patients experienced severe complications. For individuals with clinically suspicious lung lesions that initially received negative CT-guided PTNB findings, 1.0T open MR-guided secondary lung biopsy is a safe and effective secondary diagnostic approach.

Epigenetic imprinting alterations as effective diagnostic biomarkers for early-stage lung cancer and small pulmonary nodules

BackgroundEarly lung cancer detection remains a clinical challenge for standard diagnostic biopsies due to insufficient tumor morphological evidence. As epigenetic alterations precede morphological changes, expression alterations of certain imprinted genes could serve as actionable diagnostic biomarkers for malignant lung lesions.ResultsUsing the previously established quantitative chromogenic imprinted gene in situ hybridization (QCIGISH) method, elevated aberrant allelic expression of imprinted genes GNAS, GRB10, SNRPN and HM13 was observed in lung cancers over benign lesions and normal controls, which were pathologically confirmed among histologically stained normal, paracancerous and malignant tissue sections. Based on the differential imprinting signatures, a diagnostic grading model was built on 246 formalin-fixed and paraffin-embedded (FFPE) surgically resected lung tissue specimens, tested against 30 lung cytology and small biopsy specimens, and blindly validated in an independent cohort of 155 patients. The QCIGISH diagnostic model demonstrated 99.1% sensitivity (95% CI 97.5–100.0%) and 92.1% specificity (95% CI 83.5–100.0%) in the blinded validation set. Of particular importance, QCIGISH achieved 97.1% sensitivity (95% CI 91.6–100.0%) for carcinoma in situ to stage IB cancers with 100% sensitivity and 91.7% specificity (95% CI 76.0–100.0%) noted for pulmonary nodules with diameters ≤ 2 cm.ConclusionsOur findings demonstrated the diagnostic value of epigenetic imprinting alterations as highly accurate translational biomarkers for a more definitive diagnosis of suspicious lung lesions.

Malignancy Prediction Capacity and Possible Prediction Model of Circulating Tumor Cells for Suspicious Pulmonary Lesions.

More and more undetermined lung lesions are being identified in routine lung cancer screening. The aim of this study was to try to establish a malignancy prediction model according to the tumor presentations. From January 2017 to December 2018, 50 consecutive patients who were identified with suspicious lung lesions were enrolled into this study. Medical records were reviewed and tumor macroscopic and microscopic presentations were collected for analysis. Circulating tumor cells (CTC) were found to differ between benign and malignant lesions (p = 0.03) and also constituted the highest area under the receiver operation curve other than tumor presentations (p = 0.001). Since tumor size showed the highest sensitivity and CTC revealed the best specificity, a malignancy prediction model was proposed. Akaike information criterion (A.I.C.) of the combined malignancy prediction model was 26.73, which was lower than for tumor size or CTCs alone. Logistic regression revealed that the combined malignancy prediction model showed marginal statistical trends (p = 0.0518). In addition, the 95% confidence interval of combined malignancy prediction model showed less wide range than tumor size ≥ 0.7 cm alone. The calculated probability of malignancy in patients with tumor size ≥ 0.7 cm and CTC > 3 was 97.9%. By contrast, the probability of malignancy in patients whose tumor size was < 0.7 cm, and CTC ≤ 3 was 22.5%. A combined malignancy prediction model involving tumor size followed by the CTC count may provide additional information to assist decision making. For patients who present with tumor size ≥ 0.7 cm and CTC counts > 3, aggressive management should be considered, since the calculated probability of malignancy was 97.9%.

OUTCOMES OF CT FLUOROSCOPY GUIDED FINE-NEEDLE ASPIRATION CYTOLOGY AND CORE NEEDLE BIOPSIES IN SOLITARY LUNG LESIONS

Introduction: The frequent and widespread use of imaging in clinical practice, particularly CT, has led to a steep increase in incidental ndings of asymptomatic solitary pulmonary nodules. In this situation, histocytopathological analysis is needed to conrm the diagnosis by CTguided biopsy / FNAC. So, the researcher purposively, designed this study. The aim of this study was to assess the outcomes of CT-Guided Fine-Needle Aspiration Cytology and Core Needle Biopsies of Solitary Lung Lesions. CT-uoroscopy guidance helps in this process by accurate needle positioning thus increase the success rate. Materials and Methods: This was a retrospective study conducted at the Department of Radiology &amp; Imaging in Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh, during January 2017 to January 2019.Atotal of 270 patients who were referred to the Department of Radiology&amp; Imaging for the evaluation of suspicious solitary lung lesions after the detection of a solitary pulmonary nodule in X-ray or CT scan, were included in this study. The results of CT uoroscopy–guided biopsy and FNAC for the included patients were analyzed to determine the diagnostic accuracy, complication rates, and independent risk factors for diagnostic failure and severe pneumothorax in this study. The factors related to the patients' solitary lesions, and procedures were evaluated by univariate analyses using the twosided Student t test for numeric values and Chi-squared test for categorical values where p&lt;0.05 considered as signicant. Statistical analysis were performed using SPSS, version-23.0.Results: Diagnostic accuracy rate was 95.86%, failure was 4.14%, the overall sensitivity was 92.96%, specicity was 85.23% and the statistically signicant risk factors wereage (p=0.001), sex(p=0.001), smoking stats(p=0.001) emphysema(p=0.001),benign lesions(p=0.001),positioning of the patient for the procedure(p=0.001),location of the lesion(p=0.001) lesion size(p=0.001) pneumothorax (p=0.001) and length from the pleura to the lesion of 1.5 cm or greater,(p=0.001).Pneumothorax requiring drainage occurred in 1.48% of patients. The potential risk factors for pneumothorax requiring drainage were age of 73 years, the presence of emphysema, lesion size ≤ 2.0 cm and length from pleura to lesion of ≥ 1.5 cm. The major complications were being observed pneumothorax 15(5.63%), haemoptysis16 (6.01%), and hemothorax 03(1.12%).Conclusion: CT-Fluoroscopy Guided Fine-Needle Aspiration Cytology and biopsy has a high diagnostic accuracy; complication rates were acceptable and comparable to those of previous studies.

43P Incidentally discovered suspicious lung lesions in hospitalized patients during the COVID-19 pandemic in Georgia

Background: Since the start of the COVID-19 pandemic, chest CT has been broadly used for diagnosing and monitoring Covid-19 pneumonia in hospitalized patients in Georgia. Pulmonary lesions are common incidental findings, but the information about the rate of their incidental detection in our country is lacking. The purpose of this study was to examine recent trends in incidental pulmonary lesion identification in hospitalized patients in Georgia and to find out if the percentage of accidentally discovered pulmonary lesions on CT scans would be different in patients with confirmed COVID-19 disease versus in patients who were COVID-19 free.

Full core technology versus notch sampling technology: evaluation of the diagnostic accuracy and the risk of a pneumothorax after transthoracic needle biopsy of suspicious lung lesions.

Percutaneous needle biopsy of the lung (PCBL) under image guidance has become a safe and effective minimal invasive method to obtain a specimen related histological diagnosis of pulmonary lesions. To evaluate the diagnostic yield and safety of two different coaxial biopsy technologies: full core and notch sampling technology. The former allowing the removal of full punch cylinders and the latter using a cutting-edge mechanism. A retrospective analysis of 48 consecutive PCBL procedures has been carried out for this prognostic study, involving patients with a documented pulmonary nodule or mass lesion on previous computed tomography (CT) scans. The study population included 38 men and 10 women (mean age = 67 years). Of these 48 patients who underwent a procedure with a co-axial cutting system, 24 have been performed with notch sampling technology and 24 with full core technology. Out of the 48 biopsy procedures, 46 yielded specimens were adequate for histopathological evaluation, consistent with a technical success rate of 96%. The most common induced image-guided biopsy complication was a pneumothorax, occurring in 14 patients (35%). Seven patients with a pneumothorax were attributed to the full core technology and seven to the notch sampling technology (odds ratio = 1, 95% confidence interval = 0.28-3.51, P = 1). In the setting of full core versus notch sampling percutaneous CT-guided coaxial needle biopsy of the lung, no significant difference in the diagnostic accuracy and the incidence of pneumothoraces could be shown, while both technologies have an excellent diagnostic performance.

Advances of Electromagnetic Navigation Bronchoscopy for Peripheral Pulmonary Lesions

随着计算机断层扫描的筛查应用普及，越来越多的外周肺部病变被发现，外周肺病变的诊断和治疗是目前临床较为棘手的问题之一。电磁导航支气管镜以电磁定位技术为基础，经支气管到达外周肺部病变进行活检或治疗，为肺部可疑病灶提供了新的微创诊治方法。本文将综述电磁导航支气管镜在外周肺病变诊治中的临床应用现状及进展。

Peripheral blood leukocytes-related early diagnosis for lung cancer.

e21020 Background: Early diagnosis of lung cancer is critically important to reduce disease severity and improve overall survival. For patients with suspicious lung lesions, a definitive diagnosis of malignant cancer currently requires surgical biopsy. Newer, minimally invasive biopsy procedures often fail to provide adequate specimens for accurate tumor subtyping or staging which is necessary to inform appropriate use of molecular targeted therapies and immune checkpoint inhibitors. Thus newer approaches to diagnosis and staging in early lung cancer are needed. Methods: In order to address this need, peripheral blood samples from 99 individuals with clinically evident pulmonary nodules (benign and malignant), as well as ten healthy persons, were obtained. Average RNA sequencing (RNAseq) data from these samples were integrated into an artificial intelligence (AI) model in order to perform a pathway flux analysis at the system level. The AI model utilized the biological knowledge derived from the literature and publicly available databases and possessed four layers with following relationship: (1) gene→ (2) RNA→ (3) protein/complex/compound → (4) pathway. The last layer (pathway) was connected back to the first layer (gene) via diverse feedback mechanisms. Based on these results, an immune index system, IM-Index, was defined and tested for early lung cancer diagnosis and staging. Results: The leukocyte-based IM-Index correctly identified the malignancy status of lung cancer patients with high accuracy (specificity 93.5%, sensitivity 70.5%), and was able to differentiate between the three accepted phases of the cancer immunoediting concept (i.e., elimination, equilibrium, escape) (odds ratio: 1.17 [95% CI: 1.1-1.25, p&lt; 0.001). Further, the IM-Index clearly differentiated between adenocarcinoma and squamous cell carcinoma (OR: 1.2 [95% CI 1.14-1.35, p = 0.019]). In addition, tumor- and host-specific signaling pathways and metabolic profiles were identified that fully distinguished between tumor and host immunity (p &lt; 0.05). Conclusions: Taken together, these findings suggest that our rapid, non-invasive peripheral blood leukocyte-based AI approach may be useful for early definitive cancer diagnosis and staging.