Computed Tomography Screening Research Articles

Multiple primary lung cancer: Updates and perspectives.

Management of multiple primary lung cancer (MPLC) remains challenging, partly due to its increasing incidence, especially with the significant rise in cases of multiple lung nodules caused by low-dose computed tomography screening. Moreover, the indefinite pathogenesis, diagnostic criteria, and treatment selection add to the complexity. In recent years, there have been continuous efforts to dissect the molecular characteristics of MPLC and explore new diagnostic approaches as well as treatment modalities, which will be reviewed here, with a focus on newly emerging evidence and future perspectives, hope to provide new insights into the management of MPLC and serve as inspiration for future research related to MPLC.

Improving image quality of sparse-view lung tumor CT images with U-Net

BackgroundWe aimed to improve the image quality (IQ) of sparse-view computed tomography (CT) images using a U-Net for lung metastasis detection and determine the best tradeoff between number of views, IQ, and diagnostic confidence.MethodsCT images from 41 subjects aged 62.8 ± 10.6 years (mean ± standard deviation, 23 men), 34 with lung metastasis, 7 healthy, were retrospectively selected (2016–2018) and forward projected onto 2,048-view sinograms. Six corresponding sparse-view CT data subsets at varying levels of undersampling were reconstructed from sinograms using filtered backprojection with 16, 32, 64, 128, 256, and 512 views. A dual-frame U-Net was trained and evaluated for each subsampling level on 8,658 images from 22 diseased subjects. A representative image per scan was selected from 19 subjects (12 diseased, 7 healthy) for a single-blinded multireader study. These slices, for all levels of subsampling, with and without U-Net postprocessing, were presented to three readers. IQ and diagnostic confidence were ranked using predefined scales. Subjective nodule segmentation was evaluated using sensitivity and Dice similarity coefficient (DSC); clustered Wilcoxon signed-rank test was used.ResultsThe 64-projection sparse-view images resulted in 0.89 sensitivity and 0.81 DSC, while their counterparts, postprocessed with the U-Net, had improved metrics (0.94 sensitivity and 0.85 DSC) (p = 0.400). Fewer views led to insufficient IQ for diagnosis. For increased views, no substantial discrepancies were noted between sparse-view and postprocessed images.ConclusionsProjection views can be reduced from 2,048 to 64 while maintaining IQ and the confidence of the radiologists on a satisfactory level.Relevance statementOur reader study demonstrates the benefit of U-Net postprocessing for regular CT screenings of patients with lung metastasis to increase the IQ and diagnostic confidence while reducing the dose.Key points• Sparse-projection-view streak artifacts reduce the quality and usability of sparse-view CT images.• U-Net-based postprocessing removes sparse-view artifacts while maintaining diagnostically accurate IQ.• Postprocessed sparse-view CTs drastically increase radiologists’ confidence in diagnosing lung metastasis.Graphical

Enhancing diagnosis of benign lesions and lung cancer through ensemble text and breath analysis: a retrospective cohort study

Early diagnosis of lung cancer (LC) can significantly reduce its mortality rate. Considering the limitations of the high false positive rate and reliance on radiologists’ experience in computed tomography (CT)–based diagnosis, a multi-modal early LC screening model that combines radiology with other non-invasive, rapid detection methods is warranted. A high-resolution, multi-modal, and low-differentiation LC screening strategy named ensemble text and breath analysis (ETBA) is proposed that ensembles radiology report text analysis and breath analysis. In total, 231 samples (140 LC patients and 91 benign lesions [BL] patients) were screened using proton transfer reaction–time of flight–mass spectrometry and CT screening. Participants were randomly assigned to a training set and a validation set (4:1) with stratification. The report section of the radiology reports was used to train a text analysis (TA) model with a natural language processing algorithm. Twenty-two volatile organic compounds (VOCs) in the exhaled breath and the prediction results of the TA model were used as predictors to develop the ETBA model using an extreme gradient boosting algorithm. A breath analysis model was developed based on the 22 VOCs. The BA and TA models were compared with the ETBA model. The ETBA model achieved a sensitivity of 94.3%, a specificity of 77.3%, and an accuracy of 87.7% with the validation set. The radiologist diagnosis performance with the validation set had a sensitivity of 74.3%, a specificity of 59.1%, and an accuracy of 68.1%. High sensitivity and specificity were obtained by the ETBA model compared with radiologist diagnosis. The ETBA model has the potential to provide sensitivity and specificity in CT screening of LC. This approach is rapid, non-invasive, multi-dimensional, and accurate for LC and BL diagnosis.

Splenic Embolism in Infective Endocarditis: A Systematic Review of the Literature with an Emphasis on Radiological and Histopathological Diagnoses.

Infective endocarditis (IE) is characterised by fever, heart murmurs, and emboli. Splenic emboli are frequent in left-sided IE. A systematic review of the literature published on splenic embolism (SE) between 2000 and 2023 was conducted. Search strategies in electronic databases identified 2751 studies published between 1 January 2000 and 4 October 2023, of which 29 were finally included. The results showed that the imaging tests predominantly used to detect embolisms were computed tomography (CT), magnetic resonance imaging, positron emission tomography (PET)/CT, single-photon emission computed tomography/CT, ultrasound, and contrast-enhanced ultrasound. More recent studies typically used 18F-FDG PET-CT. The proportion of SE ranged from 1.4% to 71.7%. Only seven studies performed systematic conventional CT screening for intra-abdominal emboli, and the weighted mean frequency of SE was 22% (range: 8-34.8%). 18F-FDG PET-CT was performed systematically in seven studies, and splenic uptake was found in a weighted mean of 4.5%. There was a lack of uniformity in the published literature regarding the frequency and management of splenic embolisation. CT scans were the most frequently used method, until recently, when 18F-FDG PET-CT scans began to predominate. More data are necessary regarding the frequency of SE, especially focusing on their impact on IE management and prognosis.

Interpretation of global lung cancer statistics

Lung cancer remains one of the leading cause of global cancer-related mortality, posing a significant burden of disease. Tobacco exposure stands as the foremost risk factor for lung cancer. Since the 1960, global efforts have gradually been implemented to control tobacco exposure, consequently reducing tobacco exposure levels within populations. This shift in exposure levels may have altered the epidemiological characteristics of lung cancer globally. This study aims to describe global lung cancer incidence data across five dimensions: age, gender, region, stage at diagnosis, and survival status, using global cancer registry data and relevant research findings. The objective is to elucidate the current epidemiological features of lung cancer worldwide, providing a scientific basis for lung cancer prevention and control. Furthermore, this study offers corresponding measures and recommendations for lung cancer prevention and control, aligning with the three-tiered cancer prevention strategy. Findings indicate that the incidence and mortality burden of lung cancer is significantly higher among the elderly population (aged 65 years and above) compared to the working-age population (aged 15-64 years). The aged-standardized incidence rate of lung cancer remains higher in males than in females, but the overall aged-standardized incidence rate of lung cancer in males shows a declining trend, while that in females shows an increasing trend. Regions with high and very high human development index (HDI) exhibit a substantially higher incidence and mortality burden of lung cancer compared to regions with low and very low HDI. Japan ranks highest in the diagnosis of stage Ⅰ lung cancer, with a diagnosis rate of 38.6%. Its age-standardized 5-year net survival rate is relatively high at 32.9%. Despite improvements in the survival status of lung cancer in certain countries like China and Japan, the overall prognosis for lung cancer remains pessimistic. Given the current epidemiological characteristics of lung cancer, reinforcing tobacco control measures and reducing female-specific lung cancer risk factors stand as significant goals for primary prevention. Promoting low-dose computed tomography screening for high-risk population, minimizing false-positive rates in lung cancer screening, and promoting medical system reforms and standardized treatment constitute principal measures for secondary and tertiary lung cancer prevention, respectively.

A Retrospective Analysis: Investigating Factors Linked to High Lung-RADS Scores in a Nonsmoking, Non-Family History Population.

Low-dose computed tomography screening for lung cancer is currently targeted at heavy smokers or those with a family history of lung cancer. This study aimed to identify risk factors for lung cancer in individuals who do not meet the current lung cancer screening criteria as stipulated by the Taiwan Health Promotion Agency's low-dose computed tomography (LDCT) screening policy. A cohort analysis was conducted on 12,542 asymptomatic healthy subjects aged 20-80 years old who voluntarily underwent LDCT scans from January 2016 to December 2021. Logistic regression demonstrated that several factors, including age over 55 years, female gender, a body mass index (BMI) less than 23, a previous history of respiratory diseases such as tuberculosis or obstructive respiratory diseases (chronic obstructive pulmonary disease [COPD], asthma), and previous respiratory symptoms such as cough or dyspnea, were associated with high-risk lung radiology scores according to LDCT scans. These findings indicate that risk-based assessments using primary data and questionnaires to identify risk factors other than heavy smoking and a family history of lung cancer may improve the efficiency of lung cancer screening.

Uptake and 4-week quit rates from an opt-out co-located smoking cessation service delivered alongside community-based low-dose computed tomography screening within the Yorkshire Lung Screening Trial.

Up to 50% of those attending for low-dose computed tomography screening for lung cancer continue to smoke and co-delivery of smoking cessation services alongside screening may maximise clinical benefit. Here we present data from an opt-out co-located smoking cessation service delivered alongside the Yorkshire Lung Screening Trial (YLST). Eligible YLST participants were offered an immediate consultation with a smoking cessation practitioner (SCP) at their screening visit with ongoing smoking cessation support over subsequent weeks. Of 2150 eligible participants, 1905 (89%) accepted the offer of an SCP consultation during their initial visit, with 1609 (75%) receiving ongoing smoking cessation support over subsequent weeks. Uptake of ongoing support was not associated with age, ethnicity, deprivation or educational level in multivariable analyses, although men were less likely to engage (adjusted OR (ORadj) 0.71, 95% CI 0.56-0.89). Uptake was higher in those with higher nicotine dependency, motivation to stop smoking and self-efficacy for quitting. Overall, 323 participants self-reported quitting at 4 weeks (15.0% of the eligible population); 266 were validated by exhaled carbon monoxide (12.4%). Multivariable analyses of eligible smokers suggested 4-week quitting was more likely in men (ORadj 1.43, 95% CI 1.11-1.84), those with higher motivation to quit and previous quit attempts, while those with a stronger smoking habit in terms of cigarettes per day were less likely to quit. There was high uptake for co-located opt-out smoking cessation support across a wide range of participant demographics. Protected funding for integrated smoking cessation services should be considered to maximise programme equity and benefit.

A rare case of dysplastic cerebellar gangliocytoma - Lhermitte Duclos Disease

Lhermitte–Duclos disease (LDD), also known as dysplastic cerebellar gangliocytoma, is an uncommon hamartomatous lesion found in the cerebellar cortex. First described by French physicians Lhermitte and Duclos in 1920, this condition involves enlarged cerebellar folia containing abnormal ganglion cells. Clinical manifestations typically include headaches, visual disturbances, and cerebellar dysfunction. While imaging techniques like computed tomography (CT) scans may indicate the presence of mass lesions, magnetic resonance imaging (MRI) is crucial for accurate delineation of the lesion's boundaries and characterization of tissue involvement. Surgical intervention, typically in the form of respective surgery, remains the cornerstone of treatment for LDD. Despite advancements in imaging technologies and surgical techniques, the management of LDD remains fraught with complexities. The prognosis can be variable, and in some cases, despite appropriate therapeutic interventions guided by MRI-assisted surgical planning and confirmation through CT screening, the outcome may be unfavorable, as observed in this instance with the demise of the 50-year-old male patient. Further research and a deeper understanding of the pathophysiology underlying LDD are imperative to enhance diagnostic accuracy, refine treatment modalities, and potentially improve patient outcomes. This case underscores the challenges in managing this rare neurological condition and highlights the need for continued exploration into more effective therapeutic avenues.

Abstract 6075: Most cancer deaths are unaddressed by current screening paradigms

Abstract Cancer is the leading cause of death at ages ≤80 in the US. To understand the burden of cancer death potentially addressable by new or improved screening approaches, we estimated the proportion of US cancer deaths without recommended guideline-based screening, especially after accounting for lung cancer screening eligibility and adherence. Using 2018-2019 mortality data from the National Center for Health Statistics and published estimates of the proportion of screening-eligible lung cancer patients, we estimated that 31.4% of nearly 600,000 annual cancer deaths were from colorectal, female breast, cervical, and smoking-eligible lung cancers (Table). Further accounting for adherence to lung cancer screening guidelines reduced the estimated proportion of screened cancer deaths to 17.4%; thus, 82.6% of cancer deaths may not be addressed by current guideline-based screening. Among the cancers not covered by guideline-based screening are uncommon cancer types, which (as defined by the National Cancer Institute) comprised 30.4% of cancer deaths. According to incidence-based mortality data from Surveillance, Epidemiology, and End Results registries, 24.7% of all cancer deaths were from stage 4 cancer types without guideline-based screening. These estimates, based on population data without patient-level information on mode of diagnosis, almost certainly underestimate the percentage of cancer deaths missed by currently available screening efforts. The large proportion of cancer deaths unaddressed by guideline-based screening represents a vast opportunity for new cancer screening technologies that are safe, effective, accessible, and affordable to enable earlier detection and successful treatment of the full spectrum of cancer types that contribute to the overall cancer burden. Table. Deaths from cancer by primary type in 2018-2019, US National Center for Health Statistics, with eligibility for and adherence to guideline-based low-dose computed tomography screening for lung cancer All cancer types Lung Colon/rectum Breast (female) Uterine cervix Total screened % of all All cancer deaths 1,198,854 281,681 104,059 84,745 8,290 478,775 39.9% Eligible for screening based on smoking (63.7% of lung)* 179,431 104,059 84,745 8,290 376,525 31.4% Adherent to smoking-guideline-based screening (6.6% of lung)† 11,842 104,059 84,745 8,290 208,936 17.4% *Modeled estimate of proportion of lung cancer patients eligible for screening (Landy et al. 2023). †Lung cancer screening receipt from 2019 American College of Radiology Lung Cancer Screening Registry (Fedewa et al. 2022). Citation Format: Ellen T. Chang, Anuraag Kansal, Earl A. Hubbell, Graham A. Colditz, Allison W. Kurian, Christina A. Clarke. Most cancer deaths are unaddressed by current screening paradigms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6075.

Factors Associated With Delay in Lung Cancer Diagnosis and Surgery in a Lung Cancer Screening Program.

Delays to biopsy and surgery after lung nodule detection can impact survival from lung cancer. The aim of this study was to identify factors associated with delay in a lung cancer screening (LCS) program. We evaluated patients in an LCS program from May 2015 through October 2021 with a malignant lung nodule classified as lung CT screening reporting and data system (Lung-RADS) 4B/4X. A cutoff of more than 30 days between screening computed tomography (CT) and first tissue sampling and a cutoff of more than 60 days between screening CT and surgery were considered delayed. We evaluated the relationship between delays to first tissue sampling and surgery and patient sex, age, race, smoking status, median income by zip code, language, Lung-RADS category, and site of surgery (academic vs community hospital). A total of 185 lung cancers met the inclusion criteria, of which 150 underwent surgical resection. The median time from LCS CT to first tissue sampling was 42 days, and the median time from CT to surgery was 52 days. 127 (69%) patients experienced a first tissue sampling delay and 60 (40%) had a surgical delay. In multivariable analysis, active smoking status was associated with delay to first tissue sampling (odds ratio: 3.0, CI: 1.4-6.6, P = 0.005). Only performing enhanced diagnostic CT of the chest before surgery was associated with delayed lung cancer surgery (odds ratio: 30, CI: 3.6-252, P = 0.02). There was no statistically significant difference in delays with patients' sex, age, race, language, or Lung-RADS category. Delays to first tissue sampling and surgery in a LCS program were associated with current smoking and performing diagnostic CT before surgery.

Morphometric analysis of posterior cranial fossa and foramen magnum and it’s clinical implications in craniovertebral junction malformations: a computed tomography based institutional study in a tertiary care hospital of northern part of India

BackgroundThe posterior cranial fossa (PCF) and the foramen magnum (FM) are the critical anatomical components of the craniovertebral junction region, which comprise and transmit numerous vital neurovascular structures. So, a fundamental knowledge of the basic radiological anatomy of PCF and FM is of paramount importance in the evaluation of associated pathologies and approaching these areas surgically. The aim of this study is to describe different linear and angular craniometric parameters of PCF, FM and surrounding territory based on reconstructed computed tomography (CT) images.Material and methodsThis study was conducted in our tertiary care hospital in northern India from the period of January 2023 to June 2023 on 120 patients, and CT screening was done for the head and spine region following a history of head injury.ResultsIn this study, 120 patients were included, of whom 50.83% (n = 61) were females and 49.17% (n = 59) were males. Age ranged from 18 to 70 years with mean age of 43.5 ± 14.08 years. The mean values for linear craniometric parameters of PCF were statistically nonsignificant for different age groups. Statistically significant differences were found for twinning line (TL) (p < 0.0001), McRae’s line (< 0.0001), clivus length (< p < 0.0001), internal occipital protuberence -opisthion line (p = 0.01), Klaus’ index (p < 0.0001), height of posterior fossa (h) (p < 0.0001), h/TL (p = 0.028), when these values were compared for the genders. The measurements of FM transverse diameter, anteroposterior diameter and area were 27.12 ± 1.42 mm (range 23.6–30.1 mm), 30.99 ± 2.23 mm (range 27.6–35.8 mm) and 691.32 ± 30.35 mm2 (range 632.7–777.7 mm2). The values of clivus canal angle (p = 0.038) and clivoodontoid angle (p = 0.012) were statistically significant when compared for different age groups. The values of Boogard’s angle (p = 0.021) and tentorial slope (p = 0.031) were statistically significant when these were compared for the genders.ConclusionsThis study described almost all the linear and angular craniometric parameters used in the morphometric analysis of PCF and FM. The findings of this study provide valuable data regarding linear and angular craniometric parameters of PCF and FM which can redefine reference values.

Association Between Head Computed Tomography Findings and In-Hospital Mortality in COVID-19 Patients.

The present study investigated the association between head computed tomography (CT) findings and mortality in patients with COVID-19. Specifically, we focused on low-density lesions identified on head CT screenings. We performed a single-center, retrospective cohort study based on data obtained from the medical charts of inpatients admitted to the Tokyo Metropolitan Hiroo Hospital between January 1 and December 31, 2021. We focused on the basal ganglia--a representative anatomical region for assessing routine head CT in patients with COVID-19. Patients were divided into two groups based on the presence or absence of low-density lesions in the basal ganglia. The primary outcome was all-cause in-hospital mortality, and the secondary outcome was the length of hospital stay. We performed multivariable regression analyses for outcomes to adjust for patients' background and disease severity. During the study period, 1,906 COVID-19 patients were admitted to our facility. Among them, 1,203 patients underwent head CT evaluations and were included in this study. The median age was 56 years (interquartile range: 43-76 years) and 725 patients (60.3%) were male. A total of 235 (19.5%) patients required oxygen therapy on admission and 1,051 (87.4%) patients had pneumonia. Crude in-hospital mortality was 6.1% and the median length of hospital stay was 10 days (interquartile range: 8-14 days). The multivariate regression analyses showed that low-density lesions in the basal ganglia were significantly associated with increased in-hospital mortality and prolonged hospital stay. The presence of ischemic changes in the basal ganglia denoted by low-density findings may be a promising prognostic factor in patients with COVID-19.

Estimating lung function from computed tomography at the patient and lobe level using machine learning.

Automated estimation of Pulmonary function test (PFT) results from Computed Tomography (CT) could advance the use of CT in screening, diagnosis, and staging of restrictive pulmonary diseases. Estimating lung function per lobe, which cannot be done with PFTs, would be helpful for risk assessment for pulmonary resection surgery and bronchoscopic lung volume reduction. To automatically estimate PFT results from CT and furthermore disentangle the individual contribution of pulmonary lobes to a patient's lung function. We propose I3Dr, a deep learning architecture for estimating global measures from an image that can also estimate the contributions of individual parts of the image to this global measure. We apply it to estimate the separate contributions of each pulmonary lobe to a patient's total lung function from CT, while requiring only CT scans and patient level lung function measurements for training. I3Dr consists of a lobe-level and a patient-level model. The lobe-level model extracts all anatomical pulmonary lobes from a CT scan and processes them in parallel to produce lobe level lung function estimates that sum up to a patient level estimate. The patient-level model directly estimates patient level lung function from a CT scan and is used to re-scale the output of the lobe-level model to increase performance. After demonstrating the viability of the proposed approach, the I3Dr model is trained and evaluated for PFT result estimation using a large data set of 8433 CT volumes for training, 1775 CT volumes for validation, and 1873 CT volumes fortesting. First, we demonstrate the viability of our approach by showing that a model trained with a collection of digit images to estimate their sum implicitly learns to assign correct values to individual digits. Next, we show that our models can estimate lobe-level quantities, such as COVID-19 severity scores, pulmonary volume (PV), and functional pulmonary volume (FPV) from CT while only provided with patient-level quantities during training. Lastly, we train and evaluate models for producing spirometry and diffusion capacity of carbon mono-oxide (DLCO) estimates at the patient and lobe level. For producing Forced Expiratory Volume in one second (FEV1), Forced Vital Capacity (FVC), and DLCO estimates, I3Dr obtains mean absolute errors (MAE) of 0.377L, 0.297L, and 2.800mL/min/mm Hg respectively. We release the resulting algorithms for lung function estimation to the research community at https://grand-challenge.org/algorithms/lobe-wise-lung-function-estimation/ CONCLUSIONS: I3Dr can estimate global measures from an image, as well as the contributions of individual parts of the image to this global measure. It offers a promising approach for estimating PFT results from CT scans and disentangling the individual contribution of pulmonary lobes to a patient's lung function. The findings presented in this work may advance the use of CT in screening, diagnosis, and staging of restrictive pulmonary diseases as well as in risk assessment for pulmonary resection surgery and bronchoscopic lung volumereduction.

CT-based screening of sarcopenia and its role in cachexia syndrome in pancreatic cancer.

Since computed tomography (CT) is a part of standard diagnostic protocol in pancreatic ductal adenocarcinoma (PDAC), we have evaluated the value of CT for sarcopenia screening in patients with PDAC, intending to expand the diagnostic value of tomographic studies. In our study, we included 177 patients with available CT images. Two groups were formed: Group 1 consisted of 117 patients with PDAC in various locations and stages and Group 2, or the control group, consisted of 60 "nominally healthy" patients with other somatic non-oncological diseases. The body mass index (BMI) was defined as a ratio of patient's weight to the square of their height (kg/m2). CT-based body composition analysis was performed using commercially available software with evaluation of sarcopenia using skeletal muscle index (SMI, cm2/m2). Based on the SMI values, sarcopenia was found in 67.5% of patients (79 out of 117) in the first patient group. It was found more frequently in males (42 out of 56; 75%) than in females (37 out of 61; 60.6%). Additionally, we observed a decrease in muscle mass (hidden sarcopenia) in 79.7% in patients with a normal BMI. Even in overweight patients, sarcopenia was found in 50% (sarcopenic obesity). In patients with reduced BMI sarcopenia was found in all cases (100%). Statistically significant difference of SMI between two groups was revealed for both sexes (p = 0,0001), with no significant difference between groups in BMI. BMI is an inaccurate value for the assessment of body composition as it does not reflect in the details the human body structure. As SMI may correlate with the prognosis, decreased muscle mass- especially "hidden" sarcopenia or sarcopenic obesity- should be reported. The use of CT-based evaluation of sarcopenia and sarcopenic obesity will allow for a better treatment response assessment in patients with cancer cachexia.

Quantifying the Value of Reduced Health Disparities: Low-Dose Computed Tomography Lung Cancer Screening of High-Risk Individuals Within the United States

ObjectiveThis study aimed to measure the value of increasing lung cancer screening rates for high-risk individuals and its impact on health disparities. MethodsThe model estimated changes in health economic outcomes if low-dose computed tomography screening increased from current to 100% compliance, following clinical guidelines. Current low-dose computed tomography screening rates were estimated by income, education, and race, using 2017-2019 Behavioral Risk Factor Surveillance System data. The model contained a decision tree module to segment the population by screening outcomes and a Markov chain module to estimate cancer progression over time. Model parameters included information on survival, quality of life, and costs related to cancer diagnosis, treatment, and adverse events. Distributional cost-effectiveness analysis estimated the net monetary value from reduced health disparities—measured using quality-adjusted life expectancy—across income, education, and race groups. Outcomes were assessed over 30 years. ResultsLung cancer screening eligibility using US Preventive Services Task Force guidelines was higher for individuals with income <$15 000 (47.2%) and without a high-school education (46.1%) than individuals with income >$50 000 (16.6%) and with a college degree (13.5%), respectively. Increasing lung cancer screening to 100% compliance was cost-effective ($64 654 per quality-adjusted life-year) and produced economic value by up to $560 per person ($182.1 billion for United States overall). Up to 32.2% of the value was due to reductions in health disparities. ConclusionsSignificant value in increasing lung cancer screening rates derived from reducing health disparities. Policy makers and clinicians may not be appropriately prioritizing cancer screening if value from reducing health disparities is unconsidered.

Inhalable point-of-care urinary diagnostic platform.

Although low-dose computed tomography screening improves lung cancer survival in at-risk groups, inequality remains in lung cancer diagnosis due to limited access to and high costs of medical imaging infrastructure. We designed a needleless and imaging-free platform, termed PATROL (point-of-care aerosolizable nanosensors with tumor-responsive oligonucleotide barcodes), to reduce resource disparities for early detection of lung cancer. PATROL formulates a set of DNA-barcoded, activity-based nanosensors (ABNs) into an inhalable format. Lung cancer-associated proteases selectively cleave the ABNs, releasing synthetic DNA reporters that are eventually excreted via the urine. The urinary signatures of barcoded nanosensors are quantified within 20 min at room temperature using a multiplexable paper-based lateral flow assay. PATROL detects early-stage tumors in an autochthonous lung adenocarcinoma mouse model with high sensitivity and specificity. Tailoring the library of ABNs may enable not only the modular PATROL platform to lower the resource threshold for lung cancer early detection tools but also the rapid detection of chronic pulmonary disorders and infections.

Pulmonary Computed Tomography Screening Frequency in Primary Antibody Deficiency

BackgroundPatients with primary antibody deficiency (PAD) frequently suffer from pulmonary complications, associated with severe morbidity and mortality. Hence, regular pulmonary screening by computed tomography (CT) scanning is advised. However, predictive risk factors for pulmonary morbidity are lacking. ObjectiveTo identify PAD patients at risk for pulmonary complications necessitating regular CT screening. MethodsA retrospective longitudinal cohort study of PAD patients (median follow-up 7.4 (2.3 – 14.8) years). CTs were scored using the modified Brody-II scoring system. Clinical and laboratory parameters were retrospectively collected. Potential risk factors were identified by univariate analysis when p<0.2 and confirmed by multivariable logistic regression when p<0.05. ResultsThe following independent risk factors for progression of airway disease (AD) were identified: 1) diagnosis of X-linked agammaglobulinemia (XLA), 2) recurrent airway infections (2.5/year), 3) presence of AD at baseline. Signs of AD progression were detected in 5/11 XLA patients and in 17/80 of the other PAD patients. Of the patients who progressed, 17/22 had preexistent AD scores ≥7.0%. Increased AD scores were related to poorer FEV1 values and chronic cough. CVID and increased CD4 effector/memory cells were risk factors for an interstitial lung disease (ILD) score ≥13.0%. ILD ≥13.0% occurred in 12/80 patients. Signs of ILD progression were detected in 8/80 patients and 4/8 patients showing progression had preexistent ILD scores ≥13.0%. ConclusionWe identified risk factors that distinguished PAD patients at risk for airway disease and interstitial lung disease presence and progression which could guide future screening frequency, however independent and preferably prospective validation is needed.

Comparing Lung Cancer Screening Strategies in a Nationally Representative US Population Using Transportability Methods for the National Lung Cancer Screening Trial

The National Lung Screening Trial (NLST) found that screening for lung cancer with low-dose computed tomography (CT) reduced lung cancer-specific and all-cause mortality compared with chest radiography. It is uncertain whether these results apply to a nationally representative target population. To extend inferences about the effects of lung cancer screening strategies from the NLST to a nationally representative target population of NLST-eligible US adults. This comparative effectiveness study included NLST data from US adults at 33 participating centers enrolled between August 2002 and April 2004 with follow-up through 2009 along with National Health Interview Survey (NHIS) cross-sectional household interview survey data from 2010. Eligible participants were adults aged 55 to 74 years, and were current or former smokers with at least 30 pack-years of smoking (former smokers were required to have quit within the last 15 years). Transportability analyses combined baseline covariate, treatment, and outcome data from the NLST with covariate data from the NHIS and reweighted the trial data to the target population. Data were analyzed from March 2020 to May 2023. Low-dose CT or chest radiography screening with a screening assessment at baseline, then yearly for 2 more years. For the outcomes of lung-cancer specific and all-cause death, mortality rates, rate differences, and ratios were calculated at a median (25th percentile and 75th percentile) follow-up of 5.5 (5.2-5.9) years for lung cancer-specific mortality and 6.5 (6.1-6.9) years for all-cause mortality. The transportability analysis included 51 274 NLST participants and 685 NHIS participants representing the target population (of approximately 5 700 000 individuals after survey-weighting). Compared with the target population, NLST participants were younger (median [25th percentile and 75th percentile] age, 60 [57 to 65] years vs 63 [58 to 67] years), had fewer comorbidities (eg, heart disease, 6551 of 51 274 [12.8%] vs 1 025 951 of 5 739 532 [17.9%]), and were more educated (bachelor's degree or higher, 16 349 of 51 274 [31.9%] vs 859 812 of 5 739 532 [15.0%]). In the target population, for lung cancer-specific mortality, the estimated relative rate reduction was 18% (95% CI, 1% to 33%) and the estimated absolute rate reduction with low-dose CT vs chest radiography was 71 deaths per 100 000 person-years (95% CI, 4 to 138 deaths per 100 000 person-years); for all-cause mortality the estimated relative rate reduction was 6% (95% CI, -2% to 12%). In the NLST, for lung cancer-specific mortality, the estimated relative rate reduction was 21% (95% CI, 9% to 32%) and the estimated absolute rate reduction was 67 deaths per 100 000 person-years (95% CI, 27 to 106 deaths per 100 000 person-years); for all-cause mortality, the estimated relative rate reduction was 7% (95% CI, 0% to 12%). Estimates of the comparative effectiveness of low-dose CT screening compared with chest radiography in a nationally representative target population were similar to those from unweighted NLST analyses, particularly on the relative scale. Increased uncertainty around effect estimates for the target population reflects large differences in the observed characteristics of trial participants and the target population.

Program-Based Lung Cancer Care: A Prospective Observational Tumor Registry Linkage Study

IntroductionLow-dose computed tomography screening (LDCT) and lung nodule programs (LNP) promote early lung cancer detection, improve survival; Multidisciplinary Care Programs (MDC) promote guideline-concordant care. The impact of such program-based care on “real-world” lung cancer survival is unquantified. We evaluated outcomes of lung cancer care delivered through structured programs in a community health care system. MethodsWe conducted a cohort study linking institutional prospective observational LDCT, LNP and MDC databases with Tumor Registry of Baptist Cancer Center facilities. We categorized all patients diagnosed with lung cancer between 2011 and 2021 into program-based care versus non-program-based care cohorts. We compared patient characteristics, stage distribution, treatment modalities, survival and mortality in each pathway of care. ResultsOf 12,148 patients, 237, 1,165, 1,140 and 9,606 were diagnosed through the LDCT, LNP, MDC or no program, respectively; non-program-based care sequentially diminished from 96.3% to 66.5%, diagnosis through LDCT increased from 0.5% to 7.1%, LNP from 3.5% to 20.8%; and MDC alone decreased from a high of 12.8% in 2014 to 5.6% in 2021. Program-based care was associated with earlier stage (p < 0.001), higher surgical resection rates (p < 0.001), greater use of adjuvant therapy (p < 0.001), better aggregate and stage-stratified survival (p < 0.001), and lower all-cause and lung cancer-specific mortality (p < 0.001). Recipients of non-program-based care were considerably less likely to receive lung cancer treatment; results remained consistent when patients receiving no treatment were excluded. ConclusionsProgram-based care was associated with substantially better survival. Increasing access to program-based care should be explored as a matter of urgent public policy.

A reference equation for lung volume on computed tomography in Japanese middle-aged and elderly adults

BackgroundEffective use of lung volume data measured on computed tomography (CT) requires reference values for specific populations. This study examined whether an equation previously generated for multiple ethnic groups in the United States, including Asians predominantly composed of Chinese people, in the Multi-Ethnic Study of Atherosclerosis (MESA) could be used for Japanese people and, if necessary, to optimize this equation. Moreover, the equation was used to characterize patients with chronic obstructive pulmonary disease (COPD) and lung hyperexpansion. MethodsThis study included a lung cancer screening CT cohort of asymptomatic never smokers aged ≥40 years from two institutions (n = 364 and 419) to validate and optimize the MESA equation and a COPD cohort (n = 199) to test its applicability. ResultsIn all asymptomatic never smokers, the variance explained by the predicted values (R2) based on the original MESA equation was 0.60. The original equation was optimized to minimize the root mean squared error (RMSE) by adjusting the scaling factor but not the age, sex, height, or body mass index terms of the equation. The RMSE changed from 714 ml in the original equation to 637 ml in the optimized equation. In the COPD cohort, lung hyperexpansion, defined based on the 95th percentile of the ratio of measured lung volume to predicted lung volume in never smokers (122 %), was observed in 60 (30 %) patients and was associated with centrilobular emphysema and air trapping on inspiratory/expiratory CT. ConclusionsThe MESA equation was optimized for Japanese middle-aged and elderly adults.