Assessing the impact of nodule features and software algorithm on pulmonary nodule measurement uncertainty for nodules sized 20 mm or less.

Background

Measurements are not exact, so that if a measurement is repeated, one would get a different value each time. The spread of these values is the measurement uncertainty. Understanding measurement uncertainty of pulmonary nodules is important for proper interpretation of size and growth measurements. Larger amounts of measurement uncertainty may require longer follow-up intervals to be confident that any observed growth is due to actual growth rather than measurement uncertainty. We examined the influence of nodule features and software algorithm on measurement uncertainty of small, solid pulmonary nodules.

Methods

Volumes of 107 nodules were measured on 4-6 repeated computed tomography (CT) scans (Siemens Somatom AS, 100 kVp, 120 mA, 1.0 mm slice thickness reconstruction) prospectively obtained during CT-guided fine needle aspiration biopsy between 2015-2021 at Department of Diagnostic, Molecular, and Interventional Radiology in Icahn School of Medicine at Mount Sinai, using two different automated volumetric algorithms. For each, the coefficient of variation (standard deviation divided by the mean) of nodule volume measurements was determined. The following features were considered: diameter, location, vessel and pleural attachments, nodule surface area, and extent of the nodule in the three acquisition dimensions of the scanner.

Results

Median volume of 107 nodules was 515.23 and 535.53 mm

Conclusions

Even in the best-case scenario represented in this study, using the same measurement algorithm, scanner, and scanning protocol, considerable measurement uncertainty exists in nodule volume measurement for nodules sized 20 mm or less. We found that measurement uncertainty was affected by interactions between nodule volume, algorithm, and shape complexity.

Informations de copyright

2024 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Déclaration de conflit d'intérêts

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-23-1501/coif). A.J. received support as the Principal Investigator from a grant from the Prevent Cancer Foundation for this work. He also served as a co-chair on an unpaid basis of the RSNA QIBA Small Lung Nodule Volume committee from Jan 2023 to Feb 2024. R.Y. received support for this work from a grant from the Prevent Cancer Foundation. K.J.M. served as a co-chair on an unpaid basis of the RSNA QIBA Small Lung Nodule Volume committee from Jan 2023 to Feb 2024. She is the owner of Puente Solutions LLC, a for-profit company. She receives consulting fee from Annalise.ai; HeartLung; InformAI; Median iBiopsy; Malcova; Mt. Sinai School of Medicine; Sira; Voronoi; and VoxelCloud. C.I.H. is the President and serves on the board of the Early Diagnosis and Treatment Research Foundation. She receives no compensation from the Foundation. The Foundation is established to provide grants for projects, conferences, and public databases for research on early diagnosis and treatment of diseases. C.I.H. is also a named inventor on a number of patents and patent applications relating to the evaluation of pulmonary nodules on CT scans of the chest which are owned by Cornell Research Foundation (CRF). Since 2009, C.I.H. does not accept any financial benefit from these patents including royalties and any other proceeds related to the patents or patent applications owned by CRF. She is on the advisory board of Lunglife AI without compensation. D.Y. is a named inventor of General Electric on a number of patents and patent applications related to the evaluation of chest diseases including measurements of chest nodules. He has received financial compensation for the licensing of these patents. In addition, he is a consultant and co-owner of Accumetra, a private company developing tools to improve the quality of CT imaging. He is on the advisory board and owns equity in HeartLung, a company that develops software related to CT scans of the chest. He is on the medical advisory board of Median Technology that is developing technology related to analyzing pulmonary nodules and is on the medical advisory board of Carestream, a company that develops radiography equipment. He is also on the advisory board of Lunglife AI. The other author has no conflicts of interest to declare.