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. 2024 Aug 16;14(16):1795.
doi: 10.3390/diagnostics14161795.

Effectiveness of Apparent Diffusion Coefficient Values in Predicting Pathologic Subtypes and Grade in Non-Small-Cell Lung Cancer

Affiliations

Effectiveness of Apparent Diffusion Coefficient Values in Predicting Pathologic Subtypes and Grade in Non-Small-Cell Lung Cancer

Hasibe Gokce Cinar et al. Diagnostics (Basel). .

Abstract

Background and objective: The aim of this study is to evaluate the effectiveness of apparent diffusion coefficient (ADC) values in predicting pathologic subtypes and grade in non-small-cell lung cancer (NSCLC).

Materials and methods: From January 2018 to March 2020, 48 surgically diagnosed NSCLC cases were included in this study. To obtain ADC values, ADC maps were constructed, and a region of interest was put on the tumor. The values were measured three times from different places of the lesion, and the mean value of these measurements was recorded. All MRI scans were evaluated by two radiologists in consensus.

Results: A total of 14 cases were squamous cell cancer, 32 cases were adenocarcinoma, and 2 cases were large cell carcinoma. The mean ADC values of adenocarcinoma, squamous cell carcinoma, and large cell cancer were 1.51 ± 0.19 × 10-3 mm2/s, 1.32 ± 0.15 × 10-3 mm2/s, and 1.39 ± 0.25 × 10-3 mm2/s, respectively. There were 11 grade 1, 27 grade 2, and 10 grade 3 NSCLC cases. The mean ADC value was 1.44 ± 0.14 × 10-3 mm2/s in grade 1 tumors, 1.25 ± 0.10 × 10-3 mm2/s in grade 2 tumors, and 1.07 ± 0.15 × 10-3 mm2/s in grade 3 tumors. The cut-off value to discriminate grade 2 from grade 1 tumors was 1.31 ± 0.11 × 10-3 mm2/s (85% sensitivity, 75% specificity). The cut-off value to discriminate grade 3 from grade 2 tumors was 1.11 ± 0.15 × 10-3 mm2/s (87% sensitivity, 69% specificity).

Conclusions: ADC values can accurately predict NSCLC histopathologic subtypes and tumor grade.

Keywords: ADC value; diffusion-weighted imaging; lung adenocarcinoma; non-small-cell lung cancer; squamous cell lung cancer; tumor grade.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
The ADC value for pathologic cell types of NSCLC. The graph shows the ADC values according to each NSCLC pathological subtype. There is a statistically significant difference between adenocarcinoma and SCC, but no significant difference was found between adenocarcinoma and LHH and between SCC and LHH.
Figure 2
Figure 2
The ADC value for the pathologic grade of NSCLC. The graph shows ADC values according to each NSCLC pathological grade. There is a statistically significant difference between grade 1 and grade 2 and between grade 2 and grade 3 tumors.
Figure 3
Figure 3
A 72-year-old patient diagnosed with grade 1 adenocarcinoma. (A) An axial T1W image showing a hypo-isointense nodule with lobulated contour at the right upper lobe (red arrow). (B) A coronal T2W MRI image showing a hyperintense right upper lobe lung nodule (red arrow); (C,D) b = 0 and b = 800 DW images are shown, respectively. In the b = 0 DW image, there is a hyperintense nodule in the upper lobe of the right lung. In the b = 800 DW images, it is seen that the nodule has lost its signal significantly. (E,F) In the ADC map, the mean ADC value is measured as 1492.36 × 10−6 mm2/s within the lesion.
Figure 4
Figure 4
A 62-year-old patient diagnosed with grade 2 squamous cell carcinoma. (A) An axial T1W image showing an isointense, round-shaped lung nodule with a slightly spiculated extension towards the pleura in the upper lobe of the left lung. (B) A coronal T2W MRI image showing an isointense left upper lobe lung nodule (red arrow); (C,D) b = 0 and b = 800 DW images, respectively. In the b = 0 DW images, the nodule has a heterogeneous internal structure and there is a more hyperintense area on the left side of the lesion. In the b = 800 DW images, it is seen that the signal of the lesion decreases slightly and the left side remains more hyperintense than the lesion. (E,F) ADC maps showing a hypointense nodule and a mean ADC value of 1234.25 × 10−6 mm2/s. While placing the ROI for measurement on the ADC maps, the asymmetric signal area on the left side of the lesion was excluded in the DW images in order to prevent the DW parameters from being affected by non-tumor areas, such as necrosis, abscess, etc., within the tumor.
Figure 5
Figure 5
A 68-year-old patient with grade 3 squamous cell carcinoma. (A,B) b = 0 and b = 800 DW images, respectively. A heterogeneous left upper lobe lung mass (red arrows). (C,D). ADC maps showing a heterogeneous mass and a mean ADC value of 1107.45 × 10−6 mm2/s.

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References

    1. Chaitanya Thandra K., Barsouk A., Saginala K., Sukumar Aluru J., Barsouk A. Epidemiology of Lung Cancer. Współczesna Onkol. 2021;25:45–52. doi: 10.5114/wo.2021.103829. - DOI - PMC - PubMed
    1. Global Cancer Observatory: Cancer Today. International Agency for Research on Cancer; Lyon, France: [(accessed on 15 September 2020)]. Available online: https://gco.iarc.fr/today.
    1. Sung H., Ferlay J., Siegel R.L., Laversanne M., Soerjomataram I., Jemal A., Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 2021;71:209–249. doi: 10.3322/caac.21660. - DOI - PubMed
    1. Nicholson A.G., Tsao M.S., Beasley M.B., Borczuk A.C., Brambilla E., Cooper W.A., Dacic S., Jain D., Kerr K.M., Lantuejoul S., et al. The 2021 WHO Classification of Lung Tumors: Impact of Advances Since 2015. J. Thorac. Oncol. 2022;17:362–387. doi: 10.1016/j.jtho.2021.11.003. - DOI - PubMed
    1. Barta J.A., Powell C.A., Wisnivesky J.P. Global Epidemiology of Lung Cancer. Ann. Glob. Health. 2019;85:8. doi: 10.5334/aogh.2419. - DOI - PMC - PubMed

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