Volumetry versus linear diameter lung nodule measurement: an ultra-low-dose computed tomography lung cancer screening study

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Abstract

BACKGROUND: The Dutch–Belgian Randomized Lung Cancer Screening Trial (NELSON) used a volume-based protocol and significantly reduced the prevalence of false-positive results (2.1%).

AIM: To compare the performance of manual linear diameter and semi-automated volumetric nodule measurement in the pilot project “Moscow Lung Cancer Screening” ultra-low-dose computed tomography pilot study.

MATERIALS AND METHODS: The study included individuals with a lung nodule of at least 4 mm on baseline-computed tomography of the Moscow lung cancer screening between February 2017 and February 2018, without verified lung cancer diagnosis until 2020. The radiation dose was selected individually and did not exceed 1 mSv. All scans were assessed by three blinded readers to measure the maximum and minimum transversal nodule diameter and extrapolated volume. As a reference value of size and volume, the average value from the results of expert measurements was obtained. A false-positive nodule was defined as a nodule <6 mm/<100 mm3 and a false-negative nodule as a nodule ≥6 mm/≥100 mm3.

RESULTS: Overall, 293 patients were included (166 men; mean age, 64.6 ± 5.3years); 199 lung nodules were <6 mm/<100 mm3 and 94 were ≥6 mm/≥100 mm3. Regarding volumetric measurements, 32 [10.9%; 4 false-positive, 28 false-negative], 29 [9.9%; 17 false-positive, 12 false-negative], and 30 [10.2%; 6 false-positive, 24 false-negative] nodule discrepancies were reported by readers 1, 2, and 3 respectively. For linear diameter measurement, 92 [65.5%; 107 false-positive, 85 false-negative], 146 [49.8%; 58 false-positive, 88 false-negative], and 102 [34.8%; 23 false-positive, 79 false-negative] nodule discrepancies were reported by readers 1, 2, and 3 respectively.

CONCLUSIONS: The use of lung nodule volumetry strongly reduces the number of false-positive and false-negative nodules compared with nodule diameter measurements, in an ultra-low-dose computed tomography lung cancer screening program.

About the authors

Maria M. Suchilova

Moscow Center for Diagnostics and Telemedicine

Author for correspondence.
Email: m.suchilova@npcmr.ru
ORCID iD: 0000-0003-1117-0294
SPIN-code: 4922-1894

MD

Russian Federation, Moscow

Ivan A. Blokhin

Moscow Center for Diagnostics and Telemedicine

Email: i.blokhin@npcmr.ru
ORCID iD: 0000-0002-2681-9378
SPIN-code: 3306-1387

MD

Russian Federation, Moscow

Olga O. Aleshina

City Clinical Hospital No 13

Email: olya.aleshina.tula@gmail.com
ORCID iD: 0000-0001-9924-0204
SPIN-code: 6004-2422

MD

Russian Federation, Moscow

Victor A. Gombolevskiy

Artificial Intelligence Research Institute

Email: gombolevskiy@npcmr.ru
ORCID iD: 0000-0003-1816-1315
SPIN-code: 6810-3279

MD, Cand. Sci. (Med)

Russian Federation, Moscow

Roman V. Reshetnikov

Moscow Center for Diagnostics and Telemedicine

Email: reshetnikov@fbb.msu.ru
ORCID iD: 0000-0002-9661-0254
SPIN-code: 8592-0558

Cand. Sci. (Phys.-Math.)

Russian Federation, Moscow

Viktor Yu. Bosin

Moscow Center for Diagnostics and Telemedicine

Email: bosin@npcmr.ru
ORCID iD: 0000-0002-4619-2744
SPIN-code: 3380-7889

MD, Dr. Sci. (Med.)

Russian Federation, Moscow

Olga V. Omelyanskaya

Moscow Center for Diagnostics and Telemedicine

Email: o.omelyanskaya@npcmr.ru
ORCID iD: 0000-0002-0245-4431
SPIN-code: 8948-6152
Russian Federation, Moscow

Anton V. Vladzymyrskyy

Moscow Center for Diagnostics and Telemedicine; The First Sechenov Moscow State Medical University (Sechenov University)

Email: a.vladzimirskiy@npcmr.ru
ORCID iD: 0000-0002-2990-7736
SPIN-code: 3602-7120

MD, Dr. Sci (Med.)

Russian Federation, Moscow; Moscow

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Supplementary files

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2. Figure 1. Patient selection process for the study.

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3. Figure 1. Subject selection flowchart.

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