Lung Cancer Screening

Evaluation of an in-use chest CT protocol in lung cancer screening - A single institutional study

Background

Lung cancer is the most common cause of cancer-related death worldwide and therefore there has been a growing demand for low-dose computed tomography (LDCT) protocols.

Purpose

To investigate and evaluate the dose and image quality of patients undergoing lung cancer screening (LCS) using LDCT in Norway.

Materials and Methods

Retrospective dosimetry data, volumetric CT dose index (CTDIvol) and dose-length product (DLP), from 70 average-size and 70 large-size patients who underwent LDCT scan for LCS were included in the survey. Effective dose and size-specific dose were calculated for each examination and were compared with the American Association of Physicists in Medicine (AAPM) requirement. For a quantitative image quality analysis, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were determined for different regions in the chest with two iterative reconstruction techniques, iDose and Iterative Model Reconstruction. Differences in dose and image quality between average-size and large-size patients were evaluated by Independent sample t test, and Wilcoxon signed rank test within the same patient group.

Results

The independent sample t test revealed significant differences (p < .05) in dose values between average-size and large-size patients. Mean CTDIvol and DLP for average-size patients were 2.8 mGy and 115 mGy.cm, respectively, with appropriate increment for the large-size patients. Image quality (image noise, SNR, and CNR) did not significantly differ between patient groups when images were reconstructed with a model based iterative reconstruction algorithm.

Conclusion

The screening protocol assessed in this study resulted in CTDIvol values that were compliant with AAPM recommendation. No significant differences in objective image quality were found between patient groups.

Knowledge, Attitudes, and Practice Patterns of Lung Cancer Screening Among Physicians in Saudi Arabia

BACKGROUND

Lung cancer remains the primary cause of death connected to cancer on a worldwide scale. Obtaining a deep understanding of the knowledge, attitudes, and behavior patterns of doctors is essential for developing successful strategies to improve lung cancer screening. This study aims to identify the attitudes, beliefs, referral practices, and knowledge of lung cancer screening among physicians in Saudi Arabia.

METHODS

An online survey was conducted from July to December 2023 to investigate the attitudes, beliefs, referral practices, and knowledge of lung cancer screening, and adherence to lung cancer screening recommendations among physicians in Saudi Arabia. Internal medicine, family medicine, and pulmonology physicians of all levels (consultants, senior registrars, and residents) who are currently practicing medicine in Saudi Arabia formed the study population. This study employed a previously developed questionnaire. Binary logistic regression analysis was employed to identify factors that indicate a better degree of knowledge and a positive attitude toward lung cancer screening.

RESULTS

This study involved a total of 96 physicians. The study participants demonstrated a significant degree of understanding regarding lung cancer screening, with an average knowledge score of 5.8 (SD: 1.7) out of 8, equivalent to 72.5% of the highest possible score. The accuracy rate for knowledge items varied from 44.8% to 91.7%. The study participants had a moderately favorable attitude toward lung cancer screening, as shown by a mean attitude score of 14.4 (SD: 3.7) out of a maximum possible score of 30, which corresponds to 48.0% of the highest achievable score. Around 36.5% of the survey participants reported engaging in the practice of discussing the results of lung cancer screening with patients. The primary obstacles frequently cited were challenges in patient scheduling, insufficient time to discuss lung cancer screening during clinic appointments, and patient refusal, constituting 59.4%, 53.1%, and 53.1% of the identified barriers, respectively. Physicians in Saudi Arabia, particularly those employed in private hospitals, demonstrated a higher level of knowledge of lung cancer screening compared to others (p < 0.05). In contrast, individuals with 11-15 years of experience were shown to have a 78.0% lower likelihood of being educated about lung cancer screening compared to their counterparts (p < 0.05).

CONCLUSION

The study's results indicate that there is a need for the development of specialized educational initiatives aimed at Saudi Arabian physicians, particularly those with 11 to 15 years of experience who exhibit a limited understanding of lung cancer screening. Utilizing programs that provide continuing medical education would aid in their education. There is a need to facilitate communication between physicians and patients. It is critical to address the identified issues, such as streamlining the appointment scheduling process and ensuring patients have sufficient time during clinic visits. Furthermore, it is critical for the success of nationwide screening initiatives to foster collaboration between the public and private healthcare sectors.

Benign-malignant classification of pulmonary nodules by low-dose spiral computerized tomography and clinical data with machine learning in opportunistic screening

BACKGROUND

Many people were found with pulmonary nodules during physical examinations. It is of great practical significance to discriminate benign and malignant nodules by using data mining technology.

METHODS

The subjects' demographic data, baseline examination results, and annual follow-up low-dose spiral computerized tomography (LDCT) results were recorded. The findings from annual physical examinations of positive nodules, including highly suspicious nodules and clinically tentative benign nodules, was analyzed. The extreme gradient boosting (XGBoost) model was constructed and the Grid Search CV method was used to select the super parameters. External unit data were used as an external validation set to evaluate the generalization performance of the model.

RESULTS

A total of 135,503 physical examinees were enrolled. Baseline testing found that 27,636 (20.40%) participants had clinically tentative benign nodules and 611 (0.45%) participants had highly suspicious nodules. The proportion of highly suspicious nodules in participants with negative baseline was about 0.12%-0.46%, which was lower than the baseline level except the follow-up of >5 years. In the 27,636 participants with clinically tentative benign nodules, only in the first year of LDCT re-examination was the proportion of highly suspicious nodules (1.40%) significantly greater than that of baseline screening (0.45%) (p < 0.001), and the proportion of highly suspicious nodules was not different between the baseline screening and other follow-up years (p > 0.05). Furthermore, 322 cases with benign nodules and 196 patients with malignant nodules confirmed by surgery and pathology were compared. A model and the top 15 most important clinical variables were determined by XGBoost algorithm. The area under the curve (AUC) of the model was 0.76 [95% CI: 0.67-0.84], and the accuracy was 0.75. The sensitivity and specificity of the model under this threshold were 0.78 and 0.73, respectively. In the validation of model using external data, the AUC was 0.87 and the accuracy was 0.80. The sensitivity and specificity were 0.83 and 0.77, respectively.

CONCLUSIONS

It is important that pulmonary nodules could be more accurately identified at the first LDCT examination. A model with 15 variables which are routinely measured in the clinic could be helpful to distinguish benign and malignant nodules. It could help the radiological team issue a more accurate report; and it may guide the clinical team regarding LDCT follow-up.

Assessment and Efficacy of Low-Dose CT Screening and Primary Care Providers Perspective on Lung Cancer Screening: An Institutional Review

Lung cancer is the most common cause of death in both men and women. The United States Preventive Services Task Force (USPSTF) recommends annual lung screening with low-dose computed tomography (LDCT) chest for individuals aged 55-80 who have a 30 pack-year smoking history and currently smoke or have quit within the past 15 years. We reviewed the electronic medical records of patients visiting our outpatient clinic over a period of one year. We included all eligible individuals according to USPSTF guidelines for LDCT to identify screening rates at our institution. All primary care physicians, including residents and attendings, were given a prepared questionnaire to understand their beliefs and concerns with the implementation of this program. A total of 13,500 patients visited the outpatient clinic and 1178 were eligible for LDCT. Forty-five percent (45%) of patients received LDCT screening, which was higher than the national average of 2%-5%. A total of 50 primary care providers were included in the survey. The majority of the providers were aware of the USPSTF guidelines and believed that patients with multiple comorbidities and insurance issues were barriers in initiating LDCT screening. Lung cancer screening is an important component in cancer preventive strategies. Widespread awareness among the primary care providers and the public is extremely necessary for improving the use of LDCT.

Thoracalgia in a Patient with Determined Coronary Heart Disease. Is there Always a Relapse of Angina Pectoris?

This article presents a clinical case of a 62-year-old man with a long history of coronary heart disease and smoking, whose main complaint upon admission to the hospital was voice hoarseness and atypical pain syndrome in the chest. During a preliminary medical examination, attention was paid to the clinical picture, atypical for a coronary heart disease – voice hoarseness was identified as a manifestation of the recurrent nerve compression, or cardio-vocal syndrome. Given the lack of connection between the chest pain and physical exertion, a high index of a smoking person as well as signs of the recurrent nerve compression syndrome, a multi-spiral computer tomography with contrasting of the chest organs was performed (in line with official recommendations of the Russian Associations of Oncologists and Otolaryngologists). The results revealed a proliferative lesion of the mediastinum and multiple focal lesions of both lungs. A subsequent thoracoscopy and biopsy confirmed the mediastinal form of a lung cancer. Promptly initiated poly-chemotherapy allowed stabilizing the patient’s condition and significantly improving his prospects. In this context, the article discusses the complexity of a timely diagnosis of a primary lung cancer and emphasizes the need to focus on specific and unique features of the disease course as well as on a broader clinical picture. Tactics of a multidisciplinary approach allows making a diagnosis in a timely manner, significantly improving the effectiveness of therapy and patient’s survival prognosis.

Analysis of Computed Tomography Radiation Doses Used for Lung Cancer Screening Scans

IMPORTANCE

The American College of Radiology (ACR) has recognized the importance of minimizing radiation doses used for lung cancer screening (LCS) computed tomography (CT). However, without standard protocols, doses could still be unnecessarily high, reducing screening margin of benefit.

OBJECTIVE

To characterize LCS CT radiation doses and identify factors explaining variation.

DESIGN, SETTING, AND PARTICIPANTS

We prospectively collected LCS examination dose metrics, from 2016 to 2017, at US institutions in the University of California, San Francisco International Dose Registry. Institution-level factors were collected through baseline survey. Mixed-effects linear and logistic regression models were estimated using forward variable selection. Results are presented as percentage excess dose and odds ratios (ORs) with 95% confidence intervals (CIs). The analysis was conducted between 2018 and 2019.

MAIN OUTCOMES AND MEASURES

Log-transformed measures of (1) mean volume CT dose index (CTDIvol, mGy), reflecting the average radiation dose per slice; (2) mean effective dose (ED, mSv), reflecting the total dose received and estimated future cancer risk; (3) proportion of CT scans using radiation doses above ACR benchmarks (CTDIvol >3 mGy, ED >1 mSv); and (4) proportion of CT scans using radiation doses above 75th percentile of registry doses (CTDIvol >2.7 mGy, ED >1.4 mSv).

RESULTS

Data were collected for 12 529 patients undergoing LCS CT scans performed at 72 institutions. Overall, 7232 participants (58%) were men, and the median age was 65 years (interquartile range [IQR], 60-70). Of 72 institutions, 15 (21%) had median CTDIvol and 47 (65%) had median ED above ACR guidelines. Institutions allowing any radiologists to establish protocols had 44% higher mean CTDIvol (mean dose difference [MDD], 44%; 95% CI, 19%-69%) and 27% higher mean ED (MDD, 27%; 95% CI, 5%-50%) vs those limiting who established protocols. Institutions allowing any radiologist to establish protocols had higher odds of examinations exceeding ACR CTDIvol guidelines (OR, 12.0; 95% CI, 2.0-71.4), and 75th percentile of registry CTDIvol (OR, 19.0; 95% CI, 1.9-186.7) or ED (OR, 8.5; 95% CI, 1.7-42.9). Having lead radiologists establish protocols resulted in lower odds of doses exceeding ACR ED guidelines (OR, 0.01; 95% CI, 0.001-0.1). Employing external vs internal medical physicists was associated with increased odds of exceeding ACR CTDIvol guidelines (OR, 6.1; 95% CI, 1.8-20.8). Having medical physicists establish protocols was associated with decreased odds of exceeding 75th percentile of registry CTDIvol (OR, 0.09; 95% CI, 0.01-0.59). Institutions reporting protocol updates as needed had 27% higher mean CTDIvol (MDD, 27%; 95% CI, 8%-45%).

CONCLUSIONS AND RELEVANCE

Facilities varied in LCS CT radiation dose distributions. Institutions limiting protocol creation to lead radiologists and having internal medical physicists had lower doses.

A feasibility study of pulmonary nodule detection by ultralow-dose CT with adaptive statistical iterative reconstruction-V technique

PURPOSE

To evaluate the clinical value of ultralow-dose CT (ULDCT) with adaptive statistical iterative reconstruction-V (ASiR-V) in the detection of pulmonary nodules in a Chinese population.

METHOD

One hundred eighty-eight patients (16.41 ≤ BMI ≤ 29.87 kg/m²) with pulmonary nodules detected on low-dose chest CT (LDCT) underwent local ULDCT at the center of the chosen nodule with a scan length of 3 cm. LDCT was performed using the Assist kV (120/100 kV)/Smart mA mode and at 120 kV/2.8 mAs for ULDCT. After scanning, CT images were reconstructed with ASiR-V 50%. For both scans, nodule diameters were measured and reference standards were established for the presence and types of lung nodules found on LDCT. The sensitivity of ULDCT was compared against the standard, and logistic regression analysis was used to determine the independent predictors for nodule detection.

RESULTS

Compared with LDCT (0.93 ± 0.32 mSv), a 89.7% dose decrease was seen with ULDCT, for which the calculated effective dose was 0.096 ± 0.006 mSv (P < 0.001). LDCT showed 188 nodules, including 123 solid and 65 subsolid nodules. The overall sensitivity for nodule detection in ULDCT was 90.4% (170/188), and 98.2% (54/55) for nodules ≥ 6 mm. In multivariate analysis, nodule types and diameters were independent predictors of sensitivity (P < 0.05). However, patients' BMI had no effect on nodule detection (P > 0.05).

CONCLUSIONS

ULDCT can be used in the management of pulmonary nodules for people with BMI ≤ 30 kg/m² at 10% radiation dose of LDCT.

Magnetic Resonance Spectroscopy-based Metabolomic Biomarkers for Typing, Staging, and Survival Estimation of Early-Stage Human Lung Cancer

Low-dose CT has shown promise in detecting early stage lung cancer. However, concerns about the adverse health effects of radiation and high cost prevent its use as a population-wide screening tool. Effective and feasible screening methods to triage suspicious patients to CT are needed. We investigated human lung cancer metabolomics from 93 paired tissue-serum samples with magnetic resonance spectroscopy and identified tissue and serum metabolomic markers that can differentiate cancer types and stages. Most interestingly, we identified serum metabolomic profiles that can predict patient overall survival for all cases (p = 0.0076), and more importantly for Stage I cases alone (n = 58, p = 0.0100), a prediction which is significant for treatment strategies but currently cannot be achieved by any clinical method. Prolonged survival is associated with relative overexpression of glutamine, valine, and glycine, and relative suppression of glutamate and lipids in serum.