Method for Minimizing Observer Variation for the Quantitation of High-Resolution Computed Tomographic Signs of Lung Disease

Sverzellati, Nicola; Devaraj, Anand; Quigley, Maureen; Wells, Athol U.; Hansell, David M.

doi:10.1097/rct.0b013e3182277d05

Cited by 17 publications

(13 citation statements)

References 26 publications

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“…These variations are even more prevalent in real-world patient care within- and across-specialty physicians from academic and community health centers 25 . Even diagnosis by consensus of multiple experts and utilization of continuous learning techniques, which do improve consistency to some degree, does not assure dependable results 26 .…”

Section: Introductionmentioning

confidence: 99%

Quantitative Computed Tomography Imaging of Interstitial Lung Diseases

Bartholmai¹,

Raghunath²,

Karwoski³

et al. 2013

Journal of Thoracic Imaging

139

108

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Purpose High-Resolution chest CT (HRCT) is essential in the characterization of interstitial lung disease (ILD). The HRCT features of some diseases can be diagnostic. Longitudinal monitoring with HRCT can assess progression of ILD; however, subtle changes in the volume and character of abnormalities can be difficult to assess. Accuracy of diagnosis can be dependent on expertise and experience of the radiologist, pathologist or clinician. Quantitative analysis of thoracic HRCT has the potential to determine the extent of disease reproducibly, classify the types of abnormalities and automate the diagnostic process. Materials and Methods Novel software that utilizes histogram signatures to characterize pulmonary parenchyma was used to interrogate chest HRCT data, including retrospective processing of clinical CT scans and research data from the Lung Tissue Research Consortium (LTRC). Additional information including physiologic, pathologic and semi-quantitative radiologist assessment was available to allowcomparison of quantitative results with visual estimates of disease, physiologic parameters and measures of disease outcome. Results Quantitative analysis results were provided in regional volumetric quantities for statistical analysis as well as a graphical representation. Analysis suggests that quantitative HRCT analysis can serve as a biomarker with physiologic, pathologic and prognostic significance. Conclusion It is likely that quantitative analysis of HRCT can be used in clinical practice as a means to aid in identifying probable diagnosis, stratifying prognosis in early disease, and consistently determining progression of disease or response to therapy. Further optimization of quantitative techniques and longitudinal analysis of well-characterized subjects would be helpful to validate these methods.

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Section: Introductionmentioning

confidence: 99%

Quantitative Computed Tomography Imaging of Interstitial Lung Diseases

Bartholmai¹,

Raghunath²,

Karwoski³

et al. 2013

Journal of Thoracic Imaging

139

108

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“…With modern imaging techniques, it is now feasible to directly visualize early signs of pulmonary disease, including emphysema, by a multidetector computed tomography (MDCT) examination (5). However, the visual assessment of emphysema is individual, and dependent on the observer (6). Reliability of visual assessment depends upon good intra-and interobserver agreement in assessing the presence and severity of the disease (7).…”

mentioning

confidence: 99%

Visual and Quantitative Evaluation of Emphysema: A Case-Control Study of 1111 Participants in the Pilot Swedish CArdioPulmonary BioImage Study (SCAPIS)

et al. 2020

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Rationale and Objectives: Emphysema is a hallmark of chronic obstructive pulmonary disease. The primary aim of this study was to investigate inter-and intraobserver agreement of visual assessment of mild emphysema in low-dose multidetector computed tomography of subjects in the pilot SCAPIS in order to certify consistent detection of mild emphysema. The secondary aim was to investigate the performance of quantitative densitometric measurements in the cohort. Materials and Methods: Participants with emphysema (n = 100, 56 males and 44 females) reported in the electronic case report form of pilot SCAPIS and 100 matched controls (gender, age, height, and weight) without emphysema were included. To assess interobserver variability the randomized examinations were evaluated by two thoracic radiologists. For intraobserver variability three radiologists re-evaluated randomized examinations which they originally evaluated. The results were evaluated statistically by Krippendorff's a. The dataset was also assessed quantitively for % lung attenuation value À950 HU (LAV950), mean lung density and total lung volume by commercially available software. Results: Emphysema was visually scored as mild and Krippendorff's a was 0.8 for both the inter-and intraobserver agreement regarding presence of emphysema and approaching 0.8 regarding presence and extent of emphysema by location in the upper lobes. Mean LAV950 was not different between the emphysematous and the nonemphysematous participants; 8.3% and 8.4%, respectively. Conclusion: The inter-and intraobserver agreement for visual detection of mild emphysema in low-dose multidetector computed tomography was good. Surprisingly, quantitative analysis could not reliably identify participants with mild emphysema, which hampers the use of automatic evaluation.

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“…Chest HRCT is one of the common clinical examinations to diagnose IPF and assess IPF severity and prognosis. Honeycomb lung is the most representative lesion of pulmonary brosis, and the area of honeycomb lesion directly correlates to IPF prognosis [11][12][13][14]16].…”

Section: Discussionmentioning

confidence: 99%

“…However, the honeycomb lung of IPF usually in the lower lungs. Thus we referred the theories proposed in the previous studies [15,16] and calculus principles to design a "four-section honeycomb lung percentage" method. We selected the following four representative lung CT sections to semi-quantitatively estimate the extent of honeycomb lesion in the entire lung: the aortic arch section, the tracheal bifurcation section, the section of basal (dorsal) segment of the tracheal bifurcation at the inferior lobes, and the section below the right lung apex.…”

mentioning

confidence: 99%

A New Scoring System Combining A Four-Section Honeycomb Lung Percentage on HRCT and Other Comprehensive Multiparameter for Evaluating Pulmonary Fibrosis Severity

Yin

Zhang

et al. 2020

Preprint

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Background: How to accurately assess IPF severity and predict prognosis remains a problem. This study aimed to develop a new method, which can be easily used to assess pulmonary fibrosis severity.Method:1. Development of a HRCT combined pulmonary function & physiological parameter (CTPF) assessment method: The method included two parts. 1) CT-based fibrosis staging: Four representative lung CT sections were selected and evenly divided into 100 small areas. The percentage of honeycomb lesion area in the four sections was determined fibrosis stage,2) PF-based severity grade: FVC%pred,DLco%pred,SpO2% age and gender were used to assess PF severity grade. 2. Validation of the new method: The method was used to assess 192 patients with IPF. Two radiologists used the CT-based fibrosis staging method to determine the fibrosis stage. Pulmonologist determined the PF severity grade. 3. Statistical analyses: By Intra-group correlation coefficient and Spearman correlation coefficient to estimate the consistency between the CT scores from the two radiologists and the correlation between CT scores and lung function parameters. Using the competitive risk Fine–Gray model to analyze the relationship between CT-based stage/PF-based grade and prognosis. CT-based stage, PF-based grade, and GAP stage were used as predictor models to predicted the death risk. Results: 1. The intra-group correlation coefficient of the CT scores of the two radiologists was 0.95, P<0.05. 2. The CT scores negatively correlated with pulmonary function. 3. The CTPF comprehensive model, showed higher predictive accuracy.Conclusion: Combined CT-based staging and PF-based grading methods CTPF can be adopted easily in clinical practice, and can assess IPF severity and predict death risk more accurately.

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Method for Minimizing Observer Variation for the Quantitation of High-Resolution Computed Tomographic Signs of Lung Disease

Abstract: The CLM reduces noise from observer variation in studies that require visual quantitation of HRCT signs of lung disease.

Cited by 17 publications

References 26 publications

Quantitative Computed Tomography Imaging of Interstitial Lung Diseases

Quantitative Computed Tomography Imaging of Interstitial Lung Diseases

Visual and Quantitative Evaluation of Emphysema: A Case-Control Study of 1111 Participants in the Pilot Swedish CArdioPulmonary BioImage Study (SCAPIS)

A New Scoring System Combining A Four-Section Honeycomb Lung Percentage on HRCT and Other Comprehensive Multiparameter for Evaluating Pulmonary Fibrosis Severity

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