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Can dynamic imaging, using 18F-FDG PET/CT and CT perfusion differentiate between benign and malignant pulmonary nodules? Cover

Can dynamic imaging, using 18F-FDG PET/CT and CT perfusion differentiate between benign and malignant pulmonary nodules?

Open Access
|May 2021

Figures & Tables

Figure 1

Dynamic PET images of a small pulmonary nodule in the left upper lobe and corresponding time activity curve (TAC) of the nodule displayed by PMOD 3.409 software.

Figure 2

Patlak plot derived from the tissue time activity curve (TAC) and the input function (plasma TAC). The Patlak plot becomes linear after the tracer concentrations in reversible compartments and in plasma are in steady state.

Figure 3

(A) standardized uptake value (SUVmax), (B) Dynamic 18F-FDG PET/CT influx constant (Ki), (C) Perfusion CT parameters blood volume (BV) and (D) Average arterial flow (AF) of the benign and malignant nodules.

Figure 4

Comparison of AUCs on ROC curves (A) SUVmax, SURBLOOD, SURLIVER, PET grade and (B) SURLIVER, Ki, BV and AF. 95% CI, p values for SUVmax / SURBLOOD / SURLIVER / PET grade / Ki / BV / AF: 0.6264 to 1.000, 0.0157/ 0.6486 to 1.000, 0.0105/ 0.6550 to 1.000, 0.0105/ 0.507 to 0.956, 0.0756/ 0.602 to 1.000, 0.0300/ 0.6322 to 1.000, 0.0248/ 0.4342 to 0.9944, 0.1432.

The demographic data, average nodule size, standardized uptake value (SUVmax), metabolic parameter relating to the pulmonary nodules through dynamic 18F-FDG PET/CT, and perfusion parameters through perfusion CT for the benign and malignant nodules

Benign NodulesMalignant Nodulesp value
Total Number of nodules912
Number of male patients (%)5/9 (55 %)6/12 (50 %)
Average patient age (years ± SD)63 ± 7.568 ± 6.7
Average nodule size, range (mm)18, 9–2922, 12–30
Average SUVmax 18F-FDG PET/CT ± SD2.2 ± 1.77.0 ± 4.50.0148
Number of nodules analysed for dynamic 18F-FDG PET/CT79
Average Ki ± SD (min-1)0.0057 ± 0.00710.0230 ± 0.01550.0311
Number of nodules analysed for perfusion CT parameters710
Average BV ± SD (Patlak, ml/100ml)11.6857 ± 6.734728.3400 ± 15.96720.0250
Average AF ± SD (ml/100g/min)74.4571 ± 89.032189.2000 ± 49.88830.1613

Comparison of the diagnostic accuracy of different techniques and parameters with pre-specified and derived cut-point values for malignancy

ParameterCut-point value/gradeSensitivity (95% CI)Specificity (95% CI)Accuracy
SUVmaxPre-specified Derived≥ 2.5* ≥ 3.475.0% (46.8 to 91.1%) 75.0% (46.8 to 91.1%)66.7% (35.4 to 87.9%) 88.9% (56.5 to 99.43%)71.4% 81.0%
SURBLOODPre-Derived specified≥ 1.5683.3% (55.2 to 97.0%)88.9% (56.5 to 99.4%)85.7%
SURLIVERPre-specified Derived≥ 1.12 ≥ 1.6583.3% (55.2 to 97.0%) 75% (46.8 to 91.1%)66.7% (35.4 to 87.9%) 88.9% (56.5 to 99.4%)76.2% 81.0%
SUV gradePre-specified & Derived≥ 366.7% (39.0 to 86.2%)77.8% (45.3 to 96.0%)71.4%
KiDerived≥ 0.01 min-177.8% (45.2 to 96.0%)85.7% (48.7 to 99.3%)81.3%
BVDerived≥ 21 ml/100ml70% (39.7 to 89.2%)100% (64.6 to 100%)82.4%
AFDerived≥ 65 ml/100g/min70% (39.7 to 89.2%)85.7% (48.7 to 99.3%)76.5%
DOI: https://doi.org/10.2478/raon-2021-0024 | Journal eISSN: 1581-3207 | Journal ISSN: 1318-2099
Language: English
Page range: 259 - 267
Submitted on: Mar 26, 2021
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Accepted on: Apr 24, 2021
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Published on: May 31, 2021
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2021 Aleksander Marin, John T. Murchison, Kristopher M. Skwarski, Adriana A.S. Tavares, Alison Fletcher, William A. Wallace, Vladka Salapura, Edwin J.R. van Beek, Saeed Mirsadraee, published by Association of Radiology and Oncology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.