Follow-up Of Lung Nodules Research Articles

Relevant Risk Factor and Follow-Up of Lung Nodules in Physical Examination with Low-Dose CT Screening.

We aimed to explore the risk factors of lung nodules and lung cancer in physical examination population with low-dose multi-slice spiral CT (LDCT) screening, to provide basis for lung cancer screening and follow-up management after CT examination. The general data, serum tumor markers and CT images of 2,274 patients underwent LDCT in the Physical Examination Center of the Fourth Hospital of Hebei Medical University, China in 2019 were retrospectively analyzed and followed up for three years. The detection rate of lung nodules was 48.42%. The detection rate of lung nodules was higher in females, those over 70, those with history of smoking, passive smoking, drinking, precious history of lung diseases and family history of malignant tumors, with statistically significant differences (P<0.05). The abnormal rate of serum tumor markers (CA199, CA125 female and CYFRA211) were higher than that in the non-nodule group, with statistically significant differences (P<0.05). Multivariate logistic regression analysis showed that gender, age, history of smoking, passive smoking, family history of malignant tumors and serum tumor markers (CYFRA211 and CA199) were independent risk factors for the occurrence of lung nodules. Gender female, age>35, history of smoking, passive smoking, history of drinking, history of past lung disease, family history of malignant tumors, abnormal CYFRA211 tumor markers were detected and low dose multi-slice spiral CT image showed ground-glass nodules are risk factors for lung nodules and lung cancer, which should be paid close attention to during physical examination and follow-up.

Patient responses to passive enrollment into a large, pragmatic clinical trial: A qualitative content analysis

BackgroundWhile passive enrollment or “opt-out” recruitment methods facilitate pragmatic clinical trials, they pose unique challenges, and it is unclear how participants feel about them. Here, we describe patient responses to passive enrollment into the Watch the Spot Trial, a pragmatic trial comparing two sets of guidelines for small lung nodule follow-up. MethodsFor this nested qualitative study, we analyzed participant-initiated calls and emails. We performed a qualitative content analysis, using a team-coding approach to identify reasons that eligible participants contacted the study team. We calculated the proportion of contacts containing each code, and how often each code coincided with study opt-outs and other codes. ResultsOf 23,412 eligible participants across seven sites, 1494 (6.4%) contacted the study team, with 1560 total contacts. Among the total contacts, the most common codes (i.e., reasons for contacting the team) were study opt-outs (n = 614, 39.0%), clarification of study procedures (n = 328, 21.0%), and unawareness of the nodule prior to research notification (n = 244, 15.6%). The least common codes were concerns about sharing of protected health information with the study team (n = 22, 1.4%) or outside of the healthcare system (n = 26, 1.7%), and disapproval of the opt-out approach (n = 10, 0.6%); most patients with these concerns opted-out. Nodule unawareness sometimes coincided with anger (n = 24) or distress (n = 15), and questions about nodule care sometimes coincided with distress (n = 20) and questions about follow-up surveys (n = 26). ConclusionMost participants did not report concerns about passive enrollment. Patient perspectives are an invaluable resource for minimizing risks and inconveniences of future pragmatic trials using this recruitment method.

NCCN Guidelines® Insights: Lung Cancer Screening, Version 1.2022.

The NCCN Guidelines for Lung Cancer Screening recommend criteria for selecting individuals for screening and provide recommendations for evaluation and follow-up of lung nodules found during initial and subsequent screening. These NCCN Guidelines Insights focus on recent updates to the NCCN Guidelines for Lung Cancer Screening.

“ROLE OF COMPUTER AIDED DIAGNOSIS (CAD) IN EVALUATING LUNG LESIONS – AN INSTITUTIONAL EXPERIENCE”

Introduction: Lung opacities are one of most common radiological ndings and can be seen in variety of lung pathologies. They are classied into ground glass opacities, nodules and masses depending on size. CT has been the imaging modality of choice for the detection, characterization and follow-up of lung nodules. Traditionally these tasks are performed by Radiologists , however recently advances like Computer-Aided Diagnosis (CAD) are gaining interest to reduce the load on Radiologists. Aim: To study the role of Computer Aided Diagnosis (CAD) in evaluating lung lesions on Chest Computed Tomography (CT). Materials and Methods:A retrospective analysis conducted in department of Radiology in a Tertiary care Hospital, Hyderabad over a period of 3 months . A total of 100 patients with lung lesions ( ground glass opacities (GGOs), nodules and masses ) who underwent Chest CT were studied. Results: In our study, 18 patients had GGOs, 65 had nodules and 17 had masses. CAD could detect GGOs only in 04 patients, whereas Radiologist detected GGOs in 16 patients. For nodules, we analysed size, number, location &amp; morphology for which CAD showed overall poor performance as compared to Radiologist. For masses, CAD and Radiologist could detect lesions in all 17 patients. Conclusions: In our study, the role of CAD is only a complimentary tool to the Radiologist in detection and characterization of lung lesions and thereby enhancing the workow.

A nonuniform projection distribution CT method for solitary lung nodule follow-up: personal previous lung image-guided, patchwise, low-rank constrained imaging

In this paper, a nonuniform projection distribution (NUPD) CT method is proposed for the region-of-interest-specific examination in the solitary lung nodule follow-up application in order to reduce redundant x-ray projections exposed on normal tissues. The method exploits personal previous lung CT scan information to design a nonuniform x-ray projection modulation scheme where x-rays are sparsely modulated over the areas outside of the nodule in each projection view. The nonuniform projection modulation scheme could obstruct 71.84% of the x-ray projections within each scanning view in the case of a 40-mm-diameter region of interest of a solitary lung nodule, and eventually, 96.80% of the x-ray projections are eliminated in a complete circular scan in cooperation with the double sparse sampling protocol. We also devise a prior image-guided patchwise low-rank reconstruction in NUPD CT to improve the imaging quality. The proposed reconstructions have the highest Peak Signal to Noise Ratio values compared with other methods for both the full field of view (FOV) and region of interest (ROI). The structural similarities with the references are 0.9922 for the complete FOV and above 0.9999 for the ROI.

Radiologists are increasingly recommending follow-up of chest radiographs: a 10-year review.

To assess for changes in trends of GP chest radiograph reporting over a 10-year period and to assess if there has been a change in recommendations for follow-up. Retrospective study of an Irish tertiary referral center. The total number of GP-referred chest x-rays performed per year from 2007 to 2017 are recorded. One-hundred male/100 female GP-referred chest x-rays are chosen at random from NIMIS data for each of 2007, 2010, 2013, and 2017. Reports are analyzed with regard to abnormal findings, recommendation for follow-up, and yield of follow-up imaging. There were 4917 GP CXRs performed in 2007, 4856 in 2010, 5561 in 2013, and 6492 in 2017. Follow-up was recommended in 17 studies(8.5%) in 2007, 19 studies(9.5%) in 2010, 22 studies(11%) in 2013, and 27 studies(13.5%) in 2017. Indications for follow-up recommendation were largely to ensure resolution of infection (52%) or for nodule surveillance (43%). There has been a notable increase in lung nodule follow-up, with suggested follow-ups increasing from 6 in 2007, to 7 in 2010, 9 in 2013, and 14 in 2017, an increase of 58%. Along with the increase in the quantity of GP-referred chest radiographs over the past 10years, suggestions for follow-up have increased, particularly for nodule surveillance. Reasons for this increase may include lack of availability of CT to GPs for lung cancer screening, insensitivity of plain radiographs to early cancer detection, and possible fear of litigation for missing lesions, making radiologists more cautious.

No stone unturned: Nodule Net, an intervention to reduce loss to follow-up of lung nodules.

Inadequate lung nodule surveillance leads to diagnostic delays. We implemented a retrospective intervention program, Nodule Net, to improve surveillance in our hospital. 9,224 Chest computed tomography (CT) scans between January 1, 2015 and December 31, 2016 were manually reviewed for lung nodules. For patients without follow-up, charts were reviewed to assess follow-up. If follow-up appeared indicated, the clinician or patient was contacted, and follow-up was tracked. Lung nodules were identified on 5,101 (55%) of 9,224 scans. Follow-up was potentially indicated and not completed in 1,385 (27%). 183 (13%) were excluded after imaging review. 1,202 received outreach. Of the 801 (66%) with a provider in our system, 225 (27%) returned for follow-up. Nodules were stable in 199 (88%), new or growing in 23 (11%), resolved in 3 (1%), and stage 1 lung cancer in 2 (1%). 90 (11%) had follow-up outside our system and 431 (51%) had no follow-up due to a clinical contraindication. 55 (7%) have imaging pending and 14 (2%) are awaiting pulmonary evaluation. Of the 302 (25%) patients with providers outside our system, 121 (40%) had followed-up elsewhere. 146 (48%) had no follow-up due to a clinical reason. 35 (12%) providers did not respond to outreach. We identified 1,202 patients with lung nodules who needed follow-up over a two-year period. Compliance was more successful with providers within our hospital system. We recommend robust surveillance for patients to ensure follow-up is completed and clinical contraindications are well documented.

Radiologists' recommendations for additional imaging (RAI) in the inpatient setting.

The aim of our study was to measure the rate of radiologists' additional recommended imaging examinations (RAI) at a hospital-based inpatient setting and to estimate the influence on RAI of clinical variables. This retrospective study was approved by the institutional review board. Inpatients CT and US examinations interpreted by fifteen radiologists between October and December 2016 were studied. Information about RAI from radiology report texts was extracted manually. The analytic data set included the interpreting radiologists' years of experience, patient age, patient gender, radiologist gender, ordering service and "clinical question to be answered" as collected from the radiology request forms. Of the 1996 US and CT examinations performed between October and December 2016 in the inpatient setting, 34% (683 examinations) had a radiologists' RAI. The largest proportion of RAI was for chest CT, followed by PET-CT, abdominal CT and abdominal MRI. Patient age and gender had no impact on RAI. Radiologists' years of experience were inversely correlated to RAI. "Pneumonia" showed the highest rate of RAI due to follow-up of lung nodules. A high percentage of RAI resulted from CT and US radiologists' reports. The largest proportion of RAI was for chest CT, followed by PET-CT, abdominal CT, and abdominal MRI. Radiologists' years of experience play an important role in the number of the requested RAI. Further studies with a larger cohort of radiologists are needed to confirm the role of radiologists' experience in RAI. Also, follow-up studies are warranted to assess the number of RAI that are actually acted upon by the referring physicians.

Impact of noncardiac findings in patients undergoing CT coronary angiography: a substudy of the Scottish computed tomography of the heart (SCOT-HEART) trial

ObjectivesNoncardiac findings are common on coronary computed tomography angiography (CCTA). We assessed the clinical impact of noncardiac findings, and potential changes to surveillance scans with the application of new lung nodule guidelines.MethodsThis substudy of the SCOT-HEART randomized controlled trial assessed noncardiac findings identified on CCTA. Clinically significant noncardiac findings were those causing symptoms or requiring further investigation, follow-up or treatment. Lung nodule follow-up was undertaken following the 2005 Fleischner guidelines. The potential impact of the 2015 British Thoracic Society (BTS) and the 2017 Fleischner guidelines was assessed.ResultsCCTA was performed in 1,778 patients and noncardiac findings were identified in 677 (38%). In 173 patients (10%) the abnormal findings were clinically significant and in 55 patients (3%) the findings were the cause of symptoms. Follow-up imaging was recommended in 136 patients (7.6%) and additional clinic consultations were organized in 46 patients (2.6%). Malignancy was diagnosed in 7 patients (0.4%). Application of the new lung nodule guidelines would have reduced the number of patients undergoing a follow-up CT scan: 68 fewer with the 2015 BTS guidelines and 78 fewer with the 2017 Fleischner guidelines; none of these patients subsequently developed malignancy.ConclusionsClinically significant noncardiac findings are identified in 10% of patients undergoing CCTA. Application of new lung nodule guidelines will reduce the cost of surveillance, without the risk of missing malignancy.Key Points• Clinically significant noncardiac findings occur in 10% of patients undergoing CCTA.• Noncardiac findings may be an important treatable cause of chest pain• Further imaging investigations for noncardiac findings were recommended in 8% of patients after CCTA.• New lung nodule follow-up guidelines will result in cost savings.

App Review Series Introduction

App Review Series Introduction

Lung Nodule Follow-up at an Academic Center: A Revealing Quality Study

Lung Nodule Follow-up at an Academic Center: A Revealing Quality Study

Systematic Error in Lung Nodule Volumetry: Effect of Iterative Reconstruction Versus Filtered Back Projection at Different CT Parameters

Iterative reconstruction potentially can reduce radiation dose compared with filtered back projection (FBP) for chest CT. This is especially important for repeated CT scanning, as is the case in patients with indeterminate lung nodules. It is currently unknown whether absolute nodule volumes measured with iterative reconstruction are comparable to those measured with FBP. We compared nodule volumes measured with iterative reconstruction and FBP at different CT parameters. An anthropomorphic chest phantom was scanned using a 256-MDCT scanner at various tube voltages and tube current-time products. Raw data were reconstructed using FBP or a commercially available iterative reconstruction algorithm. Five inserted nodules with 100 HU radiodensity and different sizes (3, 5, 8, 10, and 12 mm) were measured by two observers using semiautomatic software. Volumetric nodule measurements were performed using thin-slice reconstructions. For very small nodules (volume, 14.1 mm(3); diameter, 3 mm), FBP and iterative reconstruction measurements exhibited large errors and overestimated the nodule size by up to 160%. For larger nodules (volume, ≥ 65.4 mm(3); diameter, ≥ 5 mm), CT underestimated the actual size, but errors were small (within 25%) and remained small when the tube voltage and tube current-time product were reduced, even without iterative reconstruction. In a phantom model, no clinically relevant differences beyond reported interscan variation levels between lung nodule volumes were measured in nodules 5 mm or larger at reduced tube voltage and tube current-time product, with radiation dose reductions up to 90.6% for both FBP and iterative reconstruction, suggesting that it is safe to convert FBP protocols to iterative reconstruction and reduce tube voltage and tube current-time product for lung nodule follow-up. CT appears to slightly underestimate actual nodule volume.

Can Low-Dose Unenhanced Chest CT Be Used for Follow-Up of Lung Nodules?

The purpose of this study is to establish the difference in lung nodule volume between standard-dose contrast-enhanced and low-dose unenhanced CT. Twenty patients with known pulmonary metastases underwent three CT examinations on 1 day: two unenhanced low-dose (120 kVp and 30 mAs) and a standard-dose (120-140 kVp and 75-200 mAs) contrast-enhanced chest CT examinations. For nodules<1000 mm3, nodule volume was quantified using dedicated software from the CT manufacturer. Wilcoxon's signed rank tests were used for analysis of nodules≤200 mm3 and >200 mm3 (approximately diameter of 8 mm). One hundred one nodules (n=69≤200 mm3) were analyzed in 15 of these subjects. Measured volume of nodules≤200 mm3 was systematically lower on both low-dose unenhanced CT examinations when compared with standard-dose contrast-enhanced CT (differences, 13.7% and 15.5%, respectively; p<0.0001), but nodule volume was not different between low-dose CT (median difference, 1.0%; p=0.10). Nodule volume was not systematically different between the protocols for nodules>200 mm3 (p>0.30). For lung nodules≤200 mm3 (approximately 8 mm) the measured volume on low-dose unenhanced CT is significantly lower when compared with standard-dose contrast-enhanced CT. This effect is likely due to contrast administration rather than other imaging parameters, which should be taken into account in the follow-up of lung nodules because growth can remain undetected or doubling time underestimated.

CT Screening and Follow-Up of Lung Nodules: Effects of Tube Current–Time Setting and Nodule Size and Density on Detectability and of Tube Current–Time Setting on Apparent Size

The purpose of the study was to quantify and compare the effect of CT dose and of size and density of nodules on the detectability of lung nodules and to quantify the influence of CT dose on the size of the nodules. From 50 patients a total of 125 cuboidal regions of interest (3 × 3 × 1.5 cm volumes) showing a single nodule (≤ 8 mm) and 27 normal cuboids were selected. Image sets were reconstructed with the software from raw data simulating different dose levels: 300 (original dose), 220, 180, 140, 100, 80, 60, 50, 40, 30, 20, 10, and 5 reference mAs. A logistic regression model was used to analyze detectability for three blinded readers. Odds ratios were calculated for nodule size smaller than 3 mm versus 3 mm and larger and for nodule attenuation of -300 HU and greater versus less than -300 HU. Tube current-time settings of 10 mAs and greater were not associated with a significant difference in individual reader sensitivity compared with the standard setting of 300 mAs. At 5 mAs only one reader had a significant decrease in sensitivity, from 82% to 77% (p = 0.0035). According to the odds ratios and logistic regression results, the strongest negative effect on sensitivity can be assumed for low nodule density followed by small nodule size and dose level. The mean nodule volume measurement error between 5 and 300 mAs was 2.2% ± 18% (SD) and much lower than the interobserver volume measurement error rate of 38% ± 45%. The results show the feasibility of a low-dose CT protocol at 10 mAs for follow-up of lung nodules. Computer-aided volume measurement in follow-up of lung nodules decreases interobserver variability.

Non-rigid registration techniques for automatic follow-up of lung nodules

Our long-term research goal is to develop an automatic approach for early detection of lung nodules that may lead to lung cancer. This paper focuses on the monitoring of the progress (growth or shrinking) of lung nodules in successive chest low dose CT (LDCT) scans of a person using non-rigid registration. The overall nodule detection approach consists of four main steps: (1) extraction of lung region by modeling the gray level distribution of LDCT slices using a linear combination of Gaussians, (2) classifying the lung region into homogenous tissues, arteries, veins and lung nodules, (3) applying rigid registration using a combination of segmentation information and mutual information as a similarity measure, and (4) compensating for the effects of heartbeats and respiration using non-rigid registration. Our earlier work addressed a number of steps in this protocol; this paper focuses on the registration step. We show that proper registration could lead to precise identification of the progress of the lung nodules.

Clinical evaluation of a software for automated localization of lung nodules at follow-up CT examinations

To evaluate a software algorithm for automated localization of pulmonary nodules at follow-up CT examinations of the chest and to determine factors influencing the rate of correctly matched nodules. The "real-time automatic matching" (RAM) algorithm (Siemens LungCare trade mark software) was applied to 22 follow-up multirow-detector CT (MDCT) examinations in 11 patients (Siemens Somatom VolumeZoom, tube voltage 120 kVp; effective tube current 20 mAs (n = 18) or 100 mAs (n = 4); 4 x 1 mm detector configuration, 1.25 mm slice thickness; 0.8 mm reconstruction increment; standard lung kernel B50f) with a total of 190 lung nodules (mean diameter 6.7 +/- 3.5 mm, range 2 - 17 mm). The following nodule features were recorded: diameter, edge definition (well- or ill-defined), location (upper, middle or lower third; central or peripheral; right or left lung) and inspiration level (considered identical if the difference of diaphragm-apex distance between baseline and follow-up examination was < 5 %, otherwise it was considered different). A nodule was regarded as correctly localized if the marking box drawn by the software was visible on at least one slice together with the nodule and the center of the nodule was located inside the marking box. chi(2)-test was used to describe influence of nodule features on detection rate. Influence of nodule size was assessed using Mann-Whitney-U-Test. RAM correctly located 164 of 190 of all lung nodules (86.3 %). Detection rate did not depend on nodule location (left vs. right lung: p = 0.48; upper vs. middle vs. lower third: p = 0.96; peripheral vs. central: p = 0.47) or diameter (p = 0.30). Influence of inspiration level was highly significant (p < 0.001): nodules were detected in 100 % (146/146) for identical inspiration levels and in 40.9 % (18/44) for different inspiration levels. The observation of a significant better localization of ill-defined nodules (p = 0.028) corresponds to a statistical artifact due to the inhomogeneous distributions of this specific feature in our data. RAM is a valuable tool for follow-up of lung nodules at CT. Only very different inspiration levels influenced detection rate.

Klinische Evaluation einer Software zur automatischen Lokalisation von Lungenrundherden in CT- Verlaufskontrollen

Purpose: To evaluate a software algorithm for automated localization of pulmonary nodules at follow-up CT examinations of the chest and to determine factors influencing the rate of correctly matched nodules. Materials andMethods: The real-time automatic matching (RAM) algorithm (Siemens LungCare software) was applied to 22 follow-up multirow-detector CT (MDCT) examinations in 11 patients (Siemens Somatom VolumeZoom, tube voltage 120 kVp; effective tube current 20mAs (n = 18) or 100 mAs (n=4); 4x1 mm detector configuration, 1.25mm slice thickness; 0.8mm reconstruction increment; standard lung kernel B50f) with a total of 190 lung nodules (mean diameter 6.7′3.5mm, range 2 - 17 mm). The following nodule features were recorded: diameter, edge definition (well- or ill-defined), location (upper, middle or lower third; central or peripheral; right or left lung) and inspiration level (considered identical if the difference of diaphragm-apex distance between baseline and follow-up examination was<5%, otherwise it was considered different). A nodule was regarded as correctly localized if the marking box drawn by the software was visible on at least one slice together with the nodule and the center of the nodule was located inside the marking box. Χ 2 -test was used to describe influence of nodule features on detection rate. Influence of nodule size was assessed using Mann-Whitney-U-Test. Results: RAM correctly located 164 of 190 of all lung nodules (86.3 %). Detection rate did not depend on nodule location (left vs. right lung: p=0.48; upper vs. middle vs. lower third: p=0.96; peripheral vs. central: p=0.47) or diameter (p=0.30). Influence of inspiration level was highly significant (p < 0.001): nodules were detected in 100% (146/146) for identical inspiration levels and in 40.9% (18/44) for different inspiration levels. The observation of a significant better localization of ill-defined nodules (p=0.028) corresponds to a statistical artifact due to the inhomogeneous distributions of this specific feature in our data. Conclusion: RAM is a valuable tool for follow-up of lung nodules at CT. Only very different inspiration levels influenced detection rate.