In vivo repeatability of automated volume calculations of small pulmonary nodules with CT

Factors influencing the outcome of volumetry tools for pulmonary nodule analysis: a systematic review and attempted meta-analysis

Health systems worldwide are implementing lung cancer screening programmes to identify early-stage lung cancer and maximise patient survival. Volumetry is recommended for follow-up of pulmonary nodules and outperforms other measurement methods. However, volumetry is known to be influenced by multiple factors. The objectives of this systematic review (PROSPERO CRD42022370233) are to summarise the current knowledge regarding factors that influence volumetry tools used in the analysis of pulmonary nodules, assess for significant clinical impact, identify gaps in current knowledge and suggest future research. Five databases (Medline, Scopus, Journals@Ovid, Embase and Emcare) were searched on the 21st of September, 2022, and 137 original research studies were included, explicitly testing the potential impact of influencing factors on the outcome of volumetry tools. The summary of these studies is tabulated, and a narrative review is provided. A subset of studies (n = 16) reporting clinical significance were selected, and their results were combined, if appropriate, using meta-analysis. Factors with clinical significance include the segmentation algorithm, quality of the segmentation, slice thickness, the level of inspiration for solid nodules, and the reconstruction algorithm and kernel in subsolid nodules. Although there is a large body of evidence in this field, it is unclear how to apply the results from these studies in clinical practice as most studies do not test for clinical relevance. The meta-analysis did not improve our understanding due to the small number and heterogeneity of studies testing for clinical significance. CRITICAL RELEVANCE STATEMENT: Many studies have investigated the influencing factors of pulmonary nodule volumetry, but only 11% of these questioned their clinical relevance in their management. The heterogeneity among these studies presents a challenge in consolidating results and clinical application of the evidence. KEY POINTS: • Factors influencing the volumetry of pulmonary nodules have been extensively investigated. • Just 11% of studies test clinical significance (wrongly diagnosing growth). • Nodule size interacts with most other influencing factors (especially for smaller nodules). • Heterogeneity among studies makes comparison and consolidation of results challenging. • Future research should focus on clinical applicability, screening, and updated technology.

Deep-learning reconstruction for ultra-low-dose lung CT: Volumetric measurement accuracy and reproducibility of artificial ground-glass nodules in a phantom study

OBJECTIVES

The lung nodule volume determined by CT is used for nodule diagnoses and monitoring tumor responses to therapy. Increased image noise on low-dose CT degrades the measurement accuracy of the lung nodule volume. We compared the volumetric accuracy among deep-learning reconstruction (DLR), model-based iterative reconstruction (MBIR), and hybrid iterative reconstruction (HIR) at an ultra-low-dose setting.

METHODS

Artificial ground-glass nodules (6 mm and 10 mm diameters, -660 HU) placed at the lung-apex and the middle-lung field in chest phantom were scanned by 320-row CT with the ultra-low-dose setting of 6.3 mAs. Each scan data set was reconstructed by DLR, MBIR, and HIR. The volumes of nodules were measured semi-automatically, and the absolute percent volumetric error (APEvol) was calculated. The APEvol provided by each reconstruction were compared by the Tukey-Kramer method. Inter- and intraobserver variabilities were evaluated by a Bland-Altman analysis with limits of agreements.

RESULTS

DLR provided a lower APEvol compared to MBIR and HIR. The APEvol of DLR (1.36%) was significantly lower than those of the HIR (8.01%, p = 0.0022) and MBIR (7.30%, p = 0.0053) on a 10-mm-diameter middle-lung nodule. DLR showed narrower limits of agreement compared to MBIR and HIR in the inter- and intraobserver agreement of the volumetric measurement.

CONCLUSIONS

DLR showed higher accuracy compared to MBIR and HIR for the volumetric measurement of artificial ground-glass nodules by ultra-low-dose CT.

ADVANCES IN KNOWLEDGE

DLR with ultra-low-dose setting allows a reduction of dose exposure, maintaining accuracy for the volumetry of lung nodule, especially in patients which deserve a long-term follow-up.

On the performance of lung nodule detection, segmentation and classification

Computed tomography (CT) screening is an effective way for early detection of lung cancer in order to improve the survival rate of such a deadly disease. For more than two decades, image processing techniques such as nodule detection, segmentation, and classification have been extensively studied to assist physicians in identifying nodules from hundreds of CT slices to measure shapes and HU distributions of nodules automatically and to distinguish their malignancy. Thanks to new parallel computation, multi-layer convolution, nonlinear pooling operation, and the big data learning strategy, recent development of deep-learning algorithms has shown great progress in lung nodule screening and computer-assisted diagnosis (CADx) applications due to their high sensitivity and low false positive rates. This paper presents a survey of state-of-the-art deep-learning-based lung nodule screening and analysis techniques focusing on their performance and clinical applications, aiming to help better understand the current performance, the limitation, and the future trends of lung nodule analysis.

Evaluate the performance of four artificial intelligence-aided diagnostic systems in identifying and measuring four types of pulmonary nodules

Purpose

This study aims to evaluate the performance of four artificial intelligence‐aided diagnostic systems in identifying and measuring four types of pulmonary nodules.

Methods

Four types of nodules were implanted in a commercial lung phantom. The phantom was scanned with multislice spiral computed tomography, after which four systems (A, B, C, D) were used to identify the nodules and measure their volumes.

Results

The relative volume error (RVE) of system A was the lowest for all nodules, except for small ground glass nodules (SGGNs). System C had the smallest RVE for SGGNs, −0.13 (−0.56, 0.00). In the Bland–Altman test, only systems A and C passed the consistency test, P = 0.40. In terms of precision, the miss rate (MR) of system C was 0.00% for small solid nodules (SSNs), ground glass nodules (GGNs), and solid nodules (SNs) but 4.17% for SGGNs. The comparable system D MRs for SGGNs, SSNs, and GGNs were 71.30%, 25.93%, and 47.22%, respectively, the highest among all the systems. Receiver operating characteristic curve analysis indicated that system A had the best performance in recognizing SSNs and GGNs, with areas under the curve of 0.91 and 0.68. System C had the best performance for SGGNs (AUC = 0.91).

Conclusion

Among four types nodules, SGGNs are the most difficult to recognize, indicating the need to improve higher accuracy and precision of artificial systems. System A most accurately measured nodule volume. System C was most precise in recognizing all four types of nodules, especially SGGN.

Lung nodules: size still matters

The incidence of indeterminate pulmonary nodules has risen constantly over the past few years. Determination of lung nodule malignancy is pivotal, because the early diagnosis of lung cancer could lead to a definitive intervention. According to the current international guidelines, size and growth rate represent the main indicators to determine the nature of a pulmonary nodule. However, there are some limitations in evaluating and characterising nodules when only their dimensions are taken into account. There is no single method for measuring nodules, and intrinsic errors, which can determine variations in nodule measurement and in growth assessment, do exist when performing measurements either manually or with automated or semi-automated methods. When considering subsolid nodules the presence and size of a solid component is the major determinant of malignancy and nodule management, as reported in the latest guidelines. Nevertheless, other nodule morphological characteristics have been associated with an increased risk of malignancy. In addition, the clinical context should not be overlooked in determining the probability of malignancy. Predictive models have been proposed as a potential means to overcome the limitations of a sized-based assessment of the malignancy risk for indeterminate pulmonary nodules.

Variability in CT lung-nodule volumetry: Effects of dose reduction and reconstruction methods

PURPOSE

Measuring the size of nodules on chest CT is important for lung cancer staging and measuring therapy response. 3D volumetry has been proposed as a more robust alternative to 1D and 2D sizing methods. There have also been substantial advances in methods to reduce radiation dose in CT. The purpose of this work was to investigate the effect of dose reduction and reconstruction methods on variability in 3D lung-nodule volumetry.

METHODS

Reduced-dose CT scans were simulated by applying a noise-addition tool to the raw (sinogram) data from clinically indicated patient scans acquired on a multidetector-row CT scanner (Definition Flash, Siemens Healthcare). Scans were simulated at 25%, 10%, and 3% of the dose of their clinical protocol (CTDIvol of 20.9 mGy), corresponding to CTDIvol values of 5.2, 2.1, and 0.6 mGy. Simulated reduced-dose data were reconstructed with both conventional filtered backprojection (B45 kernel) and iterative reconstruction methods (SAFIRE: I44 strength 3 and I50 strength 3). Three lab technologist readers contoured "measurable" nodules in 33 patients under each of the different acquisition/reconstruction conditions in a blinded study design. Of the 33 measurable nodules, 17 were used to estimate repeatability with their clinical reference protocol, as well as interdose and inter-reconstruction-method reproducibilities. The authors compared the resulting distributions of proportional differences across dose and reconstruction methods by analyzing their means, standard deviations (SDs), and t-test and F-test results.

RESULTS

The clinical-dose repeatability experiment yielded a mean proportional difference of 1.1% and SD of 5.5%. The interdose reproducibility experiments gave mean differences ranging from -5.6% to -1.7% and SDs ranging from 6.3% to 9.9%. The inter-reconstruction-method reproducibility experiments gave mean differences of 2.0% (I44 strength 3) and -0.3% (I50 strength 3), and SDs were identical at 7.3%. For the subset of repeatability cases, inter-reconstruction-method mean/SD pairs were (1.4%, 6.3%) and (-0.7%, 7.2%) for I44 strength 3 and I50 strength 3, respectively. Analysis of representative nodules confirmed that reader variability appeared unaffected by dose or reconstruction method.

CONCLUSIONS

Lung-nodule volumetry was extremely robust to the radiation-dose level, down to the minimum scanner-supported dose settings. In addition, volumetry was robust to the reconstruction methods used in this study, which included both conventional filtered backprojection and iterative methods.

Differentiating between Subsolid and Solid Pulmonary Nodules at CT: Inter- and Intraobserver Agreement between Experienced Thoracic Radiologists

PURPOSE

To quantify the reproducibility and accuracy of experienced thoracic radiologists in differentiating between subsolid and solid pulmonary nodules at CT.

MATERIALS AND METHODS

The institutional review board of Beth Israel Deaconess Medical Center approved this multicenter study. Six thoracic radiologists, with a mean of 21 years of experience in thoracic radiology (range, 17-22 years), selected images of 10 solid and 10 subsolid nodules to create a database of 120 nodules; this selection served as the reference standard. Each radiologist then interpreted 120 randomly ordered nodules in two different sessions that were separated by a minimum of 3 weeks. The radiologists classified whether or not each nodule was subsolid. Inter- and intraobserver agreement was assessed with a κ statistic. The number of correct classifications was calculated and correlated with nodule size by using Bland-Altman plots. The relationship between disagreement and nodule morphologic characteristics was analyzed by calculating the intraclass correlation coefficient.

RESULTS

Interobserver agreement (κ) was 0.619 (range, 0.469-0.745; 95% confidence interval (CI): 0.576, 0.663) and 0.670 (range, 0.440-0.839; 95% CI: 0.608, 0.733) for interpretation sessions 1 and 2, respectively. Intraobserver agreement (κ) was 0.792 (95% CI: 0.750, 0.833). Averaged for interpretation sessions, correct classification was achieved by all radiologists for 58% (70 of 120) of nodules. Radiologists agreed with their initial determination (the reference standard) in 77% of cases (range, 45%-100%). Nodule size weakly correlated with correct classification (long axis: Spearman rank correlation coefficient, rs = 0.161 and P = .049; short axis: rs = 0.128 and P = .163).

CONCLUSION

The reproducibility and accuracy of thoracic radiologists in classifying whether or not a nodule is subsolid varied in the retrospective study. This inconsistency may affect surveillance recommendations and prognostic determinations.

Indeterminate pulmonary nodules: risk for having or for developing lung cancer?

This perspective discusses the report by Pinsky and colleagues, which addresses whether noncalcified pulmonary nodules identified on CT screening carry short- and long-term risk for lung cancer. We are facing challenges related to distinguishing a large majority of benign nodules from malignant ones and among those a majority of aggressive from indolent cancers. Key questions in determining individual probabilities of disease, given their history, findings on CT, and upcoming biomarkers of risk, remain most challenging. Reducing the false positives associated with current low-dose computed tomography practices and identification of individuals who need therapy and at what time during tumor surveillance could reduce costs and morbidities associated with unnecessary interventions.

A new robot for flexible ureteroscopy: development and early clinical results (IDEAL stage 1-2b)

BACKGROUND

An improved armamentarium has had a significant impact on the emerging role of flexible ureteroscopy (FURS) for the management of nephrolithiasis; however, FURS still represents a challenging technique.

OBJECTIVE

To examine a robotic device designed for FURS for its impact on ergonomics and outcome of the procedure based on the IDEAL (idea, development, evaluation, assessment, long-term study) framework.

DESIGN, SETTING, AND PARTICIPANTS

Roboflex Avicenna consists of a surgeon's console and a manipulator for the flexible ureterorenoscope. Following experimental evaluation of the prototype (IDEAL stage 1) and receipt of ethical approval, seven surgeons treated 81 patients (mean age: 42 yr [range: 6-68]) with renal calculi (mean volume: 1296±544 mm(3) [range: 432-3100 mm3]) in an observational study (IDEAL stage 2).

SURGICAL PROCEDURE

Robotic FURS was performed with the Roboflex Avicenna robotic device.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Numerical data were analysed with the Mann-Whitney test, and categorical variables were analysed using the chi-square test or Fisher exact test. P values <0.05 were considered statistically significant.

RESULTS AND LIMITATIONS

Mean robot docking time was 59.6±45 s. Mean operative time was 74min (range: 40-182). Mean fragmentation speed was 29.1±6.1 mm3/min. Ergonomics based on a validated questionnaire showed significant advantage for robotic FURS (total score: 5.6 vs 31.3; p<0.01). A 10/12F-access sheath was used in 72 patients. Two cases required secondary FURS, one because of malfunction of the flexible digital ureteroscope and another because of larger residual fragments. In the remaining 79 cases, complete stone disintegration was accomplished.

CONCLUSIONS

Roboflex Avicenna provides a suitable and safe platform for robotic FURS with significant improvement of ergonomics. Future studies should evaluate its impact on the clinical outcome of FURS.

PATIENT SUMMARY

Robotic flexible ureteroscopy (FURS) was performed with the Roboflex Avicenna robotic device. Results showed that Roboflex Avicenna provides a suitable and safe platform for robotic FURS with significant improvement of ergonomics.

Differentiation of lung neoplasms with lepidic growth and good prognosis from those with poor prognosis using computer-aided 3D volumetric CT analysis and FDG-PET

BACKGROUND

Many studies have reported that transverse computed tomography (CT) imaging findings correlate with prognosis of patients with small peripheral lung neoplasm with lepidic growth. However, no studies have examined this correlation with the aid of three-dimensional (3D) CT data.

PURPOSE

To determine the most efficacious imaging factor for differentiation of lepidic growth type lung neoplasms with good prognosis from those with poor prognosis.

MATERIAL AND METHODS

We evaluated CT findings, nodule patterns, SUVmax on FDG-PET/CT, as well as nodule volume and ratios of solid parts to nodule volume that were semi-automatically measured on CT images of 64 pulmonary nodules of ≤ 2 cm in 60 consecutive patients (24 men and 36 women; mean age, 65 years). For logistic modeling, we used all of the significant factors observed between the neoplasms with good and with poor prognosis as independent variables to estimate the statistically significant factors for discriminating invasive adenocarcinomas with lepidic growth (lesions with poor prognosis, n=42) from the other neoplasms, including preinvasive lesions (lesions with good prognosis, n=22), resulting in a recommendation for the optimal criterion for predicting lesions with poor prognosis.

RESULTS

The logistic regression model identified the ratio of the solid part to the whole volume of a pulmonary nodule as the only significant factor (P=0.04) for differentiating lepidic growth type lung neoplasms with good prognosis from those with poor prognosis. A ratio of 0.238 or more showed the highest discriminatory accuracy of 84% with 91% sensitivity and 76% specificity.

CONCLUSION

Computer-aided analyses of pulmonary nodules proved most useful for establishing the optimal criterion for differentiation of lepidic growth type lung neoplasms with good prognosis from those with poor prognosis.

Long-term study of ovine pulmonary adenocarcinogenesis in sheep with marginal vs. sufficient nutritional selenium supply: results from computed tomography, pathology, immunohistochemistry, JSRV-PCR and lung biochemistry

The impact of selenium (Se) in carcinogenesis is still debatable due to inconsistent results of observational studies, recent suspicion of diabetic side effects and e.g. dual roles of glutathione peroxidases (GPx). Previously, our group introduced long-term studies on lung carcinogenesis using the jaagtsiekte sheep retrovirus (JSRV) induced ovine pulmonary adenocarcinoma (OPA) as an innovative animal model. The present report describes the results of sufficient (0.2 mg Se/kg dry weight (dw)) vs. marginal (<0.05 mg Se/kg dw) nutritional Se supply on cancer progression over a two-year period in 16 animals. Computed tomography (CT) evaluation of lung cancer progression, final pathological examination, evidence of pro-viral JSRV-DNA in lung, lymph nodes and broncho-alveolar lavage cells as well as biochemical analysis of Se, GPx1 and thioredoxin reductase (TrxR) activity in lung tissue were recorded. Additionally, immunohistochemical determination of GPx1 expression in unaffected and neoplastic lung cells was implemented. The feeding regime caused significant differences in Se concentration and GPx1 activity in lung tissue between groups, whereas TrxR activity remained unaffected. JSRV was evident in broncho-alveolar lavage cells, lung tissue and lung lymph nodes. Quarterly executed CT could not demonstrate differences in lung cancer proliferation intensity. Necropsy and histopathology substantiated CT findings. Immunohistochemical analysis of GPx1 in lung tissue suggested a coherency of GPx1 immunolabelling intensity in dependence of tumour size. It was concluded that the model proved to be suitable for long-term studies of lung cancer proliferation including the impact of modifiable nutritional factors. Proliferation of OPA was unaffected by marginal vs. sufficient nutritional Se supply.

Inter- and intrascanner variability of pulmonary nodule volumetry on low-dose 64-row CT: an anthropomorphic phantom study

OBJECTIVE

To assess inter- and intrascanner variability in volumetry of solid pulmonary nodules in an anthropomorphic thoracic phantom using low-dose CT.

METHODS

Five spherical solid artificial nodules [diameters 3, 5, 8, 10 and 12 mm; CT density +100 Hounsfield units (HU)] were randomly placed inside an anthropomorphic thoracic phantom in different combinations. The phantom was examined on two 64-row multidetector CT (64-MDCT) systems (CT-A and CT-B) from different vendors with a low-dose protocol. Each CT examination was performed three times. The CT examinations were evaluated twice by independent blinded observers. Nodule volume was semi-automatically measured by dedicated software. Interscanner variability was evaluated by Bland-Altman analysis and expressed as 95% confidence interval (CI) of relative differences. Intrascanner variability was expressed as 95% CI of relative variation from the mean.

RESULTS

No significant difference in CT-derived volume was found between CT-A and CT-B, except for the 3-mm nodules (p<0.05). The 95% CI of interscanner variability was within ±41.6%, ±18.2% and ±4.9% for 3, 5 and ≥8 mm nodules, respectively. The 95% CI of intrascanner variability was within ±28.6%, ±13.4% and ±2.6% for 3, 5 and ≥8 mm nodules, respectively.

CONCLUSION

Different 64-MDCT scanners in low-dose settings yield good agreement in volumetry of artificial pulmonary nodules between 5 mm and 12 mm in diameter. Inter- and intrascanner variability decreases at a larger nodule size to a maximum of 4.9% for ≥8 mm nodules.

ADVANCES IN KNOWLEDGE

The commonly accepted cut-off of 25% to determine nodule growth has the potential to be reduced for ≥8 mm nodules. This offers the possibility of reducing the interval for repeated CT scans in lung cancer screenings.

Reduction in growth threshold for pulmonary metastases: an opportunity for volumetry and its impact on treatment decisions

OBJECTIVES

This study compares tumour response assessment by automated CT volumetry and standard manual measurements regarding the impact on treatment decisions and patient outcome.

METHODS

58 consecutive patients with 203 pulmonary metastases undergoing baseline and follow-up multirow detector CT (MDCT) under chemotherapy were assessed for response to chemotherapy. Tumour burden of pulmonary target lesions was quantified in three ways: (1) following response evaluation criteria in solid tumours (RECIST); (2) following the volume equivalents of RECIST (i.e. with a threshold of -65/+73%); and (3) using calculated limits for stable disease (SD). For volumetry, calculated limits had been set at ±38% prior to the study by repeated quantification of nodules scanned twice. Results were compared using non-weighted κ-values and were evaluated for their impact on treatment decisions and patient outcome.

RESULTS

In 15 (17%) of the 58 patients, the results of response assessment were inconsistent with 1 of the 3 methods, which would have had an impact on treatment decisions in 8 (13%). Patient outcome regarding therapy response could be verified in 5 (33%) of the 15 patients with inconsistent measurement results and was consistent with both RECIST and volumetry in 1, with calculated limits in 3 and with none in 1. Diagnosis as to the overall response was consistent with RECIST in six patients, with volumetry in six and with calculated limits in eight cases. There is an impact of different methods for therapy response assessment on treatment decisions.

CONCLUSION

A reduction of threshold for SD to ±30-40% of volume change seems reasonable when using volumetry.

Pulmonary Nodules: growth rate assessment in patients by using serial CT and three-dimensional volumetry

PURPOSE

To determine the precision of a three-dimensional (3D) method for measuring the growth rate of solid and subsolid nodules and its ability to detect abnormal growth rates.

MATERIALS AND METHODS

This study was approved by the Institutional Research Board and was HIPAA compliant. Informed consent was waived. The growth rates of 123 lung nodules in 59 patients who had undergone lung cancer screening computed tomography (CT) were measured by using a 3D semiautomated computer-assisted volume method. Clinical stability was established with long-term CT follow-up (mean, 6.4 years±1.9 [standard deviation]; range, 2.0-8.5 years). A mean of 4.1 CT examinations per patient±1.2 (range, two to seven CT examinations per patient) was analyzed during 2.4 years±0.5 after baseline CT. Nodule morphology, attenuation, and location were characterized. The analysis of standard deviation of growth rate in relation to time between scans yielded a normative model for detecting abnormal growth.

RESULTS

Growth rate precision increased with greater time between scans. Overall estimate for standard deviation of growth rate, on the basis of 939 growth rate determinations in clinically stable nodules, was 36.5% per year. Peripheral location (P=.01; 37.1% per year vs 25.6% per year) and adjacency to pleural surface (P=.05; 38.9% per year vs 34.0% per year) significantly increased standard deviation of growth rate. All eight malignant nodules had an abnormally high growth rate detected. By using 3D volumetry, growth rate-based diagnosis of malignancy was made at a mean of 183 days±158, compared with radiologic or clinical diagnosis at 344 days±284.

CONCLUSION

A normative model derived from the variability of growth rates of nodules that were stable for an average of 6.4 years may enable identification of lung cancer.

Lung nodule volumetry: segmentation algorithms within the same software package cannot be used interchangeably

Objective

We examined the reproducibility of lung nodule volumetry software that offers three different volumetry algorithms.

Methods

In a lung cancer screening trial, 188 baseline nodules >5 mm were identified. Including follow-ups, these nodules formed a study-set of 545 nodules. Nodules were independently double read by two readers using commercially available volumetry software. The software offers readers three different analysing algorithms. We compared the inter-observer variability of nodule volumetry when the readers used the same and different algorithms.

Results

Both readers were able to correctly segment and measure 72% of nodules. In 80% of these cases, the readers chose the same algorithm. When readers used the same algorithm, exactly the same volume was measured in 50% of readings and a difference of >25% was observed in 4%. When the readers used different algorithms, 83% of measurements showed a difference of >25%.

Conclusion

Modern volumetric software failed to correctly segment a high number of screen detected nodules. While choosing a different algorithm can yield better segmentation of a lung nodule, reproducibility of volumetric measurements deteriorates substantially when different algorithms were used. It is crucial even in the same software package to choose identical parameters for follow-up.

Lung cancer screening update

Low-dose computed tomography (ld-CT) for lung cancer screening in high-risk subjects is performed within clinical trials and has started to be used in routine clinical practice. The technique is well defined, even if some methodological problems are still debated, such as the measurements of pulmonary nodules, the size to define them as clinically significant, the management of small or non-solid nodules and the best diagnostic work-up to optimize diagnostic accuracy. The data derived from an IEO observational study, started in 2000, shows a high prevalence and incidence of early stage lung cancer detected at ld-CT, demonstrating the need to prolong observation for a long period of time. The high survival rate of patients with screening-detected cancer has recently been debated in a number of papers using statistical models, but the advantage of the yearly ld-CT for the individuals is unquestionable; its benefit on the population base has still to be demonstrated by ongoing randomized trials.