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To develop artificial intelligence (AI) system that assists in checking endotracheal tube (ETT) placement on chest X-rays (CXRs) and evaluate whether it can move into clinical validation as a quality improvement tool.A retrospective data set including 2000 de-identified images from intensive care unit patients was split into 1488 for training and 512 for testing. AI was developed to automatically identify the ETT, trachea, and carina using semantically embedded neural networks that combine a declarative knowledge base with deep neural networks. To check the ETT tip placement, a "safe zone" was computed as the region inside the trachea and 3-7 cm above the carina. Two AI outputs were evaluated: (1) ETT overlay, (2) ETT misplacement alert messages. Clinically relevant performance metrics were compared against prespecified thresholds of85% overlay accuracy and positive predictive value (PPV)30% and negative predictive value NPV95% for alerts to move into clinical validation.An ETT was present in 285 of 512 test cases. The AI detected 95% (271/285) of ETTs, 233 (86%) of these with accurate tip localization. The system (correctly) did not generate an ETT overlay in 221/227 CXRs where the tube was absent for an overall overlay accuracy of 89% (454/512). The alert messages indicating that either the ETT was misplaced or not detected had a PPV of 83% (265/320) and NPV of 98% (188/192).The chest X-ray AI met prespecified performance thresholds to move into clinical validation.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, irreversible, and usually fatal lung disease of unknown reasons, generally affecting the elderly population. Early diagnosis of IPF is crucial for triaging patients’ treatment planning into anti-fibrotic treatment or treatments for other causes of pulmonary fibrosis. However, current IPF diagnosis workflow is complicated and time-consuming, which involves collaborative efforts from radiologists, pathologists, and clinicians and it is largely subject to inter-observer variability. PURPOSE: The purpose of this work is to develop a deep learning-based automated system that can diagnose subjects with IPF among subjects with interstitial lung disease (ILD) using an axial chest computed tomography (CT) scan. This work can potentially enable timely diagnosis decisions and reduce inter-observer variability. METHODS: Our dataset contains CT scans from 349 IPF patients and 529 non-IPF ILD patients. We used 80% of the dataset for training and validation purposes and 20% as the holdout test set. We proposed a two-stage model: at stage one, we built a multi-scale, domain knowledge-guided attention model (MSGA) that encouraged the model to focus on specific areas of interest to enhance model explainability, including both high- and medium-resolution attentions; at stage two, we collected the output from MSGA and constructed a random forest (RF) classifier for patient-level diagnosis, to further boost model accuracy. RF classifier is utilized as a final decision stage since it is interpretable, computationally fast, and can handle correlated variables. Model utility was examined by (1) accuracy, represented by the area under the receiver operating characteristic curve (AUC) with standard deviation (SD), and (2) explainability, illustrated by the visual examination of the estimated attention maps which showed the important areas for model diagnostics. RESULTS: During the training and validation stage, we observe that when we provide no guidance from domain knowledge, the IPF diagnosis model reaches acceptable performance (AUC±SD = 0.93±0.07),but lacks explainability; when including only guided high- or medium-resolution attention, the learned attention maps are not satisfactory; when including both high- and medium-resolution attention, under certain hyperparameter settings, the model reaches the highest AUC among all experiments (AUC±SD = 0.99±0.01) and the estimated attention maps concentrate on the regions of interests for this task. Three best-performing hyperparameter selections according to MSGA were applied to the holdout test set and reached comparable model performance to that of the validation set. CONCLUSIONS: Our results suggest that, for a task with only scan-level labels available, MSGA+RF can utilize the population-level domain knowledge to guide the training of the network, which increases both model accuracy and explainability.

Rationale: Tocilizumab, an anti–interleukin-6 receptor antibody, had no statistically significant effect on skin sclerosis but preserved lung function over 48 weeks in patients with early systemic ...

Background Interstitial lung abnormalities (ILA) may represent undiagnosed early-stage or subclinical interstitial lung disease (ILD). ILAs are often observed incidentally in patients who subsequently develop clinically overt ILD. There is limited information on consensus definitions for, and the appropriate evaluation of, ILA. Early recognition of patients with ILD remains challenging, yet critically important. Expert consensus could inform early recognition and referral. Research Question Can consensus-based expert recommendations be identified to guide clinicians in the recognition, referral, and follow-up of patients with or at risk of developing early ILDs? Study Design and Methods Pulmonologists and radiologists with expertise in ILD participated in two iterative rounds of surveys. The surveys aimed to establish consensus regarding ILA reporting, identification of patients with ILA, and identification of populations that might benefit from screening for ILD. Recommended referral criteria and follow-up processes were also addressed. Threshold for consensus was defined a priori as ≥ 75% agreement or disagreement. Results Fifty-five experts were invited and 44 participated; consensus was reached on 39 of 85 questions. The following clinically important statements achieved consensus: honeycombing and traction bronchiectasis or bronchiolectasis indicate potentially progressive ILD; honeycombing detected during lung cancer screening should be reported as potentially significant (eg, with the Lung CT Screening Reporting and Data System “S-modifier” [which indicates clinically significant or potentially significant noncancer findings]), recommending referral to a pulmonologist in the radiology report; high-resolution CT imaging and full pulmonary function tests should be ordered if nondependent subpleural reticulation, traction bronchiectasis, honeycombing, centrilobular ground-glass nodules, or patchy ground-glass opacity are observed on CT imaging; patients with honeycombing or traction bronchiectasis should be referred to a pulmonologist irrespective of FVC and diffusion capacity values; and patients with systemic sclerosis should be screened with pulmonary function tests for early-stage ILD. Interpretation Guidance for identifying clinically relevant ILA, with subsequent referral and follow-up, was established. These results lay the foundation for developing practical guidance on managing patients with ILA.

Purpose To examine the use of multiple fast-helical free breathing CT (FHFBCT) scans for ventilation measurement METHODS: Ten patients were scanned 25 times in alternating directions using a FHFBCT protocol. Simultaneously, an abdominal pneumatic bellows was used as a real-time breathing surrogate. Regions-of-interest (ROIs) were selected from the upper right lungs of each patient for analysis. The ROIs were first registered using a published registration technique (pTV). A subsequent followup registration employed an objective function with two terms, a ventilation-adjusted Hounsfield Unit difference and a conservation-of-mass term labeled ΔΓ that denoted the difference between the deformation Jacobian and the tissue density ratio. The ventilations were calculated voxel-by-voxel as the slope of a first-order fit of the Jacobian as a function of the breathing amplitude. Results The ventilations of the 10 patients showed different patterns and magnitudes. The average ventilation calculated from the DVFs of the pTV and secondary registration were nearly identical, but the standard deviation of the voxel-to-voxel differences were approximately 0.1. The mean of the 90th percentile values of ΔΓ were reduced from 0.153 to 0.079 between the pTV and secondary registration, implying first that the secondary registration improved the conservation-of-mass criterion by almost 50% and that on average the correspondence between the Jacobian and density ratios as demonstrated by ΔΓ were less than 0.1. This improvement occurred in spite of the average of the 90th percentile changes in the DVF magnitudes being only 0.58 mm. Conclusions This work introduces the use of multiple free-breathing CT scans for free-breathing ventilation measurements. The approach has some benefits over the traditional use of 4DCT or breath-hold scans. The benefit over 4DCT is that FHFBCT does not have sorting artifacts. The benefits over breath-hold scans include the relatively small motion induced by quiet respiration versus deep-inspiration breath hold and the potential for characterizing dynamic breathing processes that disappear during breath hold. This article is protected by copyright. All rights reserved.

Objective Tocilizumab (TCZ) has demonstrated lung function preservation in 2 randomized controlled trials in early systemic sclerosis (SSc). This effect has yet to be characterized in terms of radiographically evident quantitative lung involvement. We undertook this study to assess the impact of TCZ on lung function preservation in a post hoc analysis, stratifying treatment arms according to the degree of lung involvement. Methods The focuSSced trial was a phase III randomized placebo-controlled trial of TCZ in patients with SSc and progressive skin disease. Participants underwent baseline and serial spirometry along with high-resolution chest computed tomography at baseline and at week 48. Quantitative interstitial lung disease (QILD) and fibrosis scores were assessed by computer software. We classified QILD into the following categories of lung involvement: mild (>5-10%), moderate (>10-20%), and severe (>20%). Results Of 210 participants recruited for the trial, 136 patients (65%) had ILD. The majority of these patients (77%) had moderate-to-severe involvement (defined as >10% lung involvement). The TCZ arm demonstrated preservation of forced vital capacity percent predicted (FVC%) over 48 weeks (least squares mean change in FVC% = -0.1) compared to placebo (-6.3%). For mild, moderate, and severe QILD, the mean ± SD change in FVC% in the TCZ arm at 48 weeks were -4.1 ± 2.5% (n = 11), 0.7 ± 1.9% (n =19), and 2.1 ± 1.6% (n = 26), respectively, and in the placebo group were -10.0 ± 2.6% (n = 11), -5.7 ± 1.6% (n = 26), and -6.7 ± 2.0% (n = 16), respectively. Similar treatment-related preservation findings were seen independent of fibrosis severity. Conclusion TCZ in early SSc-associated ILD with progressive skin disease stabilized FVC% over 48 weeks, independent of the extent of radiographically evident QILD.

Background Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, known as coronavirus disease 2019 (COVID-19), is an ongoing issue in some populations with rapidly worsening pneumonia and persistent symptoms. This study aimed to test the predictability of rapid progression within 7 days of hospitalization using radiographic scores with laboratory markers at baseline and to present longitudinal changes. Methods This retrospective study included 222 subjects (mean age: 53.4 years, 50.9% male) diagnosed with COVID-19 and admitted between February and September 2020 at Chungnam National University Hospital. Rapid progression was defined as respiratory failure requiring ventilator support. From high-resolution computed tomography (HRCT) analyses, quantitative COVID (QCOVID) scores were derived: (1) ground glass opacity (QGGO), (2) mixed diseases (QMD), and (3) consolidation (QCON), and the sum, quantitative total lung diseases (QTLD). ROC analyses were performed to predict progression. Mixed-effects models were performed using serial 2–6 HRCTs over 2–4 months, where the last scans were obtained after discharge. The laboratory data including white blood cell count, platelet count, neutrophil count, lymphocyte count, C-reactive protein (CRP), procalcitonin, and interleukin-6 (IL-6) were obtained from electronic medical records. Results Rapid progression was observed in 10.4% (23/222) of patients. All QCOVID scores predicted rapid progression, with QMD showing the best predictability (area under the curve, AUC = 0.813, p 10 folds (p 2 months follow-up, parenchymal areas were still observed with a QTLD of 1.4–29.3%, even after several weeks of negative reverse transcription polymerase chain reaction test. Conclusions AI-driven quantitative scores can be useful in predicting the rapid progression and monitoring of COVID-19 with other laboratory markers.

Determination of therapeutic benefit in intracranial tumors is intimately dependent on serial assessment of radiographic images. The Response Assessment in Neuro-Oncology (RANO) criteria were established in 2010 to provide an updated framework to better characterize tumor response to contemporary treatments. Since this initial update a number of RANO criteria have provided some basic principles for the interpretation of changes on MR images; however, the details of how to operationalize RANO and other criteria for use in clinical trials are ambiguous and not standardized. In this review article designed for the neuro-oncologist or treating clinician, we outline essential steps for performing radiographic assessments by highlighting primary features of the Imaging Charter (referred to as the Charter for the remainder of this article), a document that describes the clinical trial imaging methodology and methods to ensure operationalization of the Charter into the workings of a clinical trial. Lastly, we provide recommendations for specific changes to optimize this methodology for neuro-oncology, including image registration, requirement of growing tumor for eligibility in trials of recurrent tumor, standardized image acquisition guidelines, and hybrid reader paradigms that allow for both unbiased measurements and more comprehensive interpretation.

Objective To evaluate short- and long-term outcomes of African American (AA) participants of Scleroderma Lung Studies (SLS) I and II. Methods SLS I randomized 158 participants with systemic sclerosis-interstitial lung disease (SSc-ILD) to 1 year of oral cyclophosphamide (CYC) versus placebo. SLS II randomized 142 participants with SSc-ILD to 1 year of oral CYC followed by 1 year of placebo versus 2 years of mycophenolate (MMF). Joint models compared the course of forced vital capacity (FVC) and diffusing capacity for carbon monoxide (DLCO) between AA and non-AA, and Cox proportional hazard models assessed long-term morbidity and mortality outcomes. Results In SLS I, there was no difference in the course of the FVC or DLCO between AA and non-AA in either treatment arm. In SLS II, AA had an improved course of the FVC compared with non-AA in the CYC arm; in the MMF arm, there was no difference in FVC course. There was no difference in DLCO course in either arm. Time to death and respiratory failure were similar for AA and non-AA in SLS I. There was a trend for improved survival and time to respiratory failure in AA compared with non-AA in SLS II. AA race was not independently associated with mortality in the SLS I or II in the Cox models. Conclusion Data from two randomized controlled trials demonstrated that AA patients with SSc-ILD have similar morbidity and mortality outcomes compared with non-AA patients. These findings contrast with the racial disparities described in prior observational studies and warrant further investigation.

Background: Nintedanib slows disease progression in patients with Idiopathic Pulmonary Fibrosis (IPF) by reducing decline in Forced Vital Capacity (FVC). The effects of nintedanib on abnormalities on high-resolution computed tomography scans have not been previously studied. Objective: We conducted a Phase IIIb trial to assess the effects of nintedanib on changes in Quantitative Lung Fibrosis (QLF) score and other measures of disease progression in patients with IPF. Methods: 113 patients were randomized 1:1 to receive nintedanib 150 mg bid or placebo double-blind for ?6 months, followed by open-label nintedanib. The primary endpoint was the relative change from baseline in QLF score (%) at month 6. Analyses were descriptive and exploratory. Results: Adjusted mean relative changes from baseline in QLF score at month 6 were 11.4% in the nintedanib group (n=42) and 14.6% in the placebo group (n=45) (difference 3.2% [95% CI: ?9.2, 15.6]). Adjusted mean absolute changes from baseline in QLF score at month 6 were 0.98% and 1.33% in these groups, respectively (difference 0.35% [95% CI: ?1.27, 1.96]). Adjusted mean absolute changes from baseline in FVC at month 6 were ?14.2 mL and ?83.2 mL in the nintedanib (n=54) and placebo (n=54) groups, respectively (difference 69.0 mL [95% CI: ?8.7, 146.8]). Conclusion: Exploratory data suggest that in patients with IPF, 6 months’ treatment with nintedanib was associated with a numerically smaller degree of fibrotic change in the lungs and reduced FVC decline versus placebo. These data support previous findings that nintedanib slows the progression of IPF. © 2020 Lancaster et al., Boehringer Ingelheim, BI, This trial was funded by Boehringer Ingelheim Pharmaceuticals, Inc.

With more than 900,000 confirmed cases worldwide and nearly 50,000 deaths during the first 3 months of 2020, the coronavirus disease 2019 (COVID-19) pandemic has emerged as an unprecedented health care crisis. The spread of COVID-19 has been heterogeneous, resulting in some regions having sporadic transmission and relatively few hospitalized patients with COVID-19 and others having community transmission that has led to overwhelming numbers of severe cases. For these regions, health care delivery has been disrupted and compromised by critical resource constraints in diagnostic testing, hospital beds, ventilators, and health care workers who have fallen ill to the virus exacerbated by shortages of personal protective equipment. Although mild cases mimic common upper respiratory viral infections, respiratory dysfunction becomes the principal source of morbidity and mortality as the disease advances. Thoracic imaging with chest radiography and CT are key tools for pulmonary disease diagnosis and management, but their role in the management of COVID-19 has not been considered within the multivariable context of the severity of respiratory disease, pretest probability, risk factors for disease progression, and critical resource constraints. To address this deficit, a multidisciplinary panel comprised principally of radiologists and pulmonologists from 10 countries with experience managing patients with COVID-19 across a spectrum of health care environments evaluated the utility of imaging within three scenarios representing varying risk factors, community conditions, and resource constraints. Fourteen key questions, corresponding to 11 decision points within the three scenarios and three additional clinical situations, were rated by the panel based on the anticipated value of the information that thoracic imaging would be expected to provide. The results were aggregated, resulting in five main and three additional recommendations intended to guide medical practitioners in the use of chest radiography and CT in the management of COVID-19.

Objective Our objective was to determine if treatment with cyclophosphamide (CYC) and mycophenolate mofetil (MMF) improves patient-reported outcomes (PROs) among patients with systemic sclerosis-related interstitial lung disease (SSc-ILD). Methods This study examined PROs in patients with SSc-ILD (N = 142) who participated in the Scleroderma Lung Study II, a randomized controlled trial comparing MMF for 2 years with oral CYC for 1 year followed by 1 year of a placebo. Joint models were created to evaluate the course of PROs over 2 years. The difference in PRO scores from baseline to 24 months was measured, and the percentage of patients meeting the minimum clinically important difference (MCID) was calculated. Correlations between PROs and SSc-ILD disease severity measures were also examined. Results Treatment with CYC and MMF led to improvements in several PROs with no between-treatment differences. Scores for the Transitional Dyspnea Index (TDI) and St. George's Respiratory Questionnaire (SGRQ) improved significantly over 2 years, and 29%/24% and 28%/25% of participants in the CYC/MMF groups met or exceeded the MCID estimates for TDI and SGRQ, respectively. At baseline, the forced vital capacity (FVC) percentage predicted (FVC%-predicted) did not correlate with the Baseline Dyspnea Index or SGRQ. However, improvements in the FVC%-predicted were weakly associated with improvements in dyspnea (assessed by the TDI) and SGRQ scores. Conclusion Treatment with CYC and MMF improved overall health-related quality of life in patients with SSc-ILD. The relationship between PRO measures and the FVC was relatively weak, suggesting that PROs provide complementary information about treatment efficacy not captured by changes in the FVC alone in this patient population.

CITATION: Allwood, B. W., et al. Transition from restrictive to obstructive lung function impairment during treatment and follow-up of active tuberculosis. International Journal of Chronic Obstructive Pulmonary Disease, 2020(15):039-1047, doi:10.2147/COPD.S219731.

BackgroundChronic lung allograft dysfunction (CLAD) phenotype determines prognosis and may have therapeutic implications. Despite the clarity achieved by recent consensus statement definitions, their reliance on radiologic interpretation introduces subjectivity. The Center for Computer Vision and Imaging Biomarkers at the University of California, Los Angeles (UCLA) has established protocols for chest high-resolution computed tomography (HRCT)-based computer-aided quantification of both interstitial disease and air-trapping. We applied quantitative image analysis (QIA) at CLAD onset to demonstrate radiographic phenotypes with clinical implications.MethodsWe studied 47 first bilateral lung transplant recipients at UCLA with chest HRCT performed within 90 d of CLAD onset and 47 no-CLAD control HRCTs. QIA determined the proportion of lung volume affected by interstitial disease and air-trapping in total lung capacity and residual volume images, respectively. We compared QIA scores between no-CLAD and CLAD, and between phenotypes. We also assigned radiographic phenotypes based solely on QIA, and compared their survival outcomes.ResultsCLAD onset HRCTs had more lung affected by the interstitial disease (P = 0.003) than no-CLAD controls. Bronchiolitis obliterans syndrome (BOS) cases had lower scores for interstitial disease as compared with probable restrictive allograft syndrome (RAS) (P < 0.0001) and mixed CLAD (P = 0.02) phenotypes. BOS cases had more air-trapping than probable RAS (P < 0.0001). Among phenotypes assigned by QIA, the relative risk of death was greatest for mixed (relative risk [RR] 11.81), followed by RAS (RR 6.27) and BOS (RR 3.15).ConclusionsChest HRCT QIA at CLAD onset appears promising as a method for precise determination of CLAD phenotypes with survival implications.

Background Since IDH-mutant (mIDH) low-grade gliomas (LGGs) progress slowly and have a relatively long survival, there is a significant need for earlier measurements of clinical benefit. Guidance using the LGG RANO criteria recommends serial bidirectional (2D) measurements on a single slice; however, questions remain as to whether volumetric (3D) measurements are better, since they would allow for more accurate measurements in irregular shaped lesions and allow readers to better assess areas of subtle change. Methods Twenty-one (out of 24) non-enhancing, recurrent mIDH1 LGGs were enrolled in a phase I, multicenter, open-label study of oral ivosidenib (NCT02073994), and with imaging pre- and post-treatment as part of this exploratory ad hoc analysis. 2D and 3D measurements on T2-weighted FLAIR images were centrally evaluated at an imaging contract research organization using a paired read and forced adjudication paradigm. The effects of 2D vs 3D measurements on progression-free survival (PFS), growth rate measurement variability, and reader concordance and adjudication rates were quantified. Results 3D volumetric measurements showed significantly longer estimated PFS (P = .0181), more stable (P = .0063) and considerably slower measures of tumor growth rate (P = .0037), the highest inter-reader agreement (weighted kappa = 0.7057), and significantly lower reader discordance rates (P = .0002) with 2D LGG RANO. Conclusion 3D volumetric measurements are better for determining response assessment in LGGs due to more stable measures of tumor growth rates (ie, less “yo-yo-ing” of measurements over time), highest inter-reader agreement, and lowest reader discordance rates. Continued evaluation in future studies is warranted to determine whether these measurements reflect clinical benefit.

IntroductionIdiopathic pulmonary fibrosis (IPF) and non-IPF, progressive fibrotic interstitial lung diseases (PF-ILD), are associated with a progressive loss of lung function and a poor prognosis. Treatment with antifibrotic agents can slow, but not halt, disease progression, and treatment discontinuation because of adverse events is common. Fibrotic diseases such as these can be mediated by lysophosphatidic acid (LPA), which signals via six LPA receptors (LPA1–6). Signalling via LPA1 appears to be fundamental in the pathogenesis of fibrotic diseases. BMS-986278, a second-generation LPA1 antagonist, is currently in phase 2 development as a therapy for IPF and PF-ILD.Methods and analysisThis phase 2, randomised, double-blind, placebo-controlled, parallel-group, international trial will include adults with IPF or PF-ILD. The trial will consist of a 42-day screening period, a 26-week placebo-controlled treatment period, an optional 26-week active-treatment extension period, and a 28-day post-treatment follow-up. Patients in both the IPF (n=240) and PF-ILD (n=120) cohorts will be randomised 1:1:1 to receive 30 mg or 60 mg BMS-986278, or placebo, administered orally two times per day for 26 weeks in the placebo-controlled treatment period. The primary endpoint is rate of change in per cent predicted forced vital capacity from baseline to week 26 in the IPF cohort.Ethics and disseminationThis study will be conducted in accordance with Good Clinical Practice guidelines, Declaration of Helsinki principles, and local ethical and legal requirements. Results will be reported in a peer-reviewed publication.Trial registration numberNCT04308681.

Objective: To explore the presence of small airway disease (SAD) and emphysema in scleroderma-related interstitial lung disease (SSc-ILD) and to evaluate the physiologic and clinical correlates of SAD in SSc-ILD. Methods: Thoracic high-resolution computed tomography (HRCT) images obtained from the Scleroderma Lung Study II (SLSII) participants were reviewed by a group of thoracic radiologists. The presence of SAD was assessed by visual assessment for air trapping. HRCT scans were also evaluated for the presence of emphysema. The association of the presence of air trapping and emphysema with physiological measures of airway disease and clinical variables was evaluated. Results: A total of 155 baseline HRCT scans were reviewed. For assessment of air trapping, images needed to be adequate end-expiratory examinations, leaving 123 scans. Air trapping was seen in 13/123 (10.6%) of the SSc-ILD cohort and was independent of smoking history, asthma or the presence of gastroesophageal reflux. Air trapping on HRCT was not associated with physiologic evidence of SAD. We also identified 8/155 (5.2%) patients with emphysema on HRCT, which was independent of SAD and found mostly in prior smokers. Conclusion: We report the first study of air trapping on standardized, high-quality HRCT images as a reflection of SAD in a relatively large, well characterized SSc-ILD cohort. The presence of SAD in non-smoking SSc-ILD patients supports that SSc may cause not only restrictive lung disease (SSc-ILD), but also, to a lesser extent, obstructive disease. Physiologic measures alone may be inadequate to detect airway disease in patients with SSc-ILD.

High-resolution computed tomography (HRCT) plays an indispensable role in the diagnosis of idiopathic pulmonary fibrosis (IPF). Due to unpredictability in progression and the short median survival of 2–5 years, it is critical to delineate the patients with rapid progression. The aim is to evaluate the predictability of IPF progression using the early quantitative changes. Automated texture-based quantitative lung fibrosis (QLF) was calculated from the anonymized HRCT. Two datasets were collected retrospectively: (1) a pilot study of 35 subjects with three sequential scans (baseline and 6 and 12 months) to obtain a threshold, where visual assessments were stable at 6 months but worsened at 12 months; (2) 157 independent subjects to test the threshold. Landmark Cox regressions were used to compare the progression-free survival (PFS) defined by pulmonary function using the threshold from the early changes in QLF. C-indexes were reported as estimations of the concordance of prediction. A threshold of 4% QLF change at 6 months corresponded to the mean change that worsened on HRCT visually at 12 months from the pilot study. Using the threshold, significant differences were found in the independent dataset (hazard ratio (HZ) = 5.92, p = 0.001 by Cox model, C-index = 0.71 at the most severe lobe; and HZ = 3.22, p = 0.012, C-index = 0.68 in the whole lung). Median PFS was 11.9 months for subjects with ≥ 4% changes, whereas median PFS was greater than 18 months for subjects with

Rationale and Objectives The purpose of this paper is to describe the integration of a commercial chest CT computer-aided detection (CAD) system into the clinical radiology reporting workflow and perform an initial investigation of its impact on radiologist efficiency. It seeks to complement research into CAD sensitivity and specificity of stand-alone systems, by focusing on report generation time when the CAD is integrated into the clinical workflow. Materials and Methods A commercial chest CT CAD software that provides automated detection and measurement of lung nodules, ascending and descending aorta, and pleural effusion was integrated with a commercial radiology report dictation application. The CAD system automatically prepopulated a radiology report template, thus offering the potential for increased efficiency. The integrated system was evaluated using 40 scans from a publicly available lung nodule database. Each scan was read using two methods: (1) without CAD analytics, i.e., manually populated report with measurements using electronic calipers, and (2) with CAD analytics to prepopulate the report for reader review and editing. Three radiologists participated as readers in this study. Results CAD assistance reduced reading times by 7%–44%, relative to the conventional manual method, for the three radiologists from opening of the case to signing of the final report. Conclusion This study provides an investigation of the impact of CAD and measurement on chest CTs within a clinical reporting workflow. Prepopulation of a report with automated nodule and aorta measurements yielded substantial time savings relative to manual measurement and entry.