99mTc-MAA accumulation within tumor in preoperative lung perfusion SPECT/CT associated with occult lymph node metastasis in patients with clinically N0 non-small cell lung cancer

• Published in: BMC cancer Vol. 23; no. 1; pp. 1 - 381
• Main Authors: Murad, Vanessa, Suh, Minseok, Choi, Hongyoon, Cheon, Gi Jeong, Na, Kwon Joong, Kim, Young Tae
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 26.04.2023; BioMed Central; BMC
• Subjects: 99mTc-MAA; Adenocarcinoma; Analysis; Biological markers; Blood vessels; Care and treatment; Comparative analysis; Computed tomography; CT imaging; Development and progression; Imaging biomarker; Lung cancer; Lung cancer, Non-small cell; Lung cancer, Small cell; Lung perfusion scintigraphy; Lymph nodes; Lymphatic metastasis; Medical prognosis; Metastases; Metastasis; Multivariate analysis; Non-small cell lung cancer; Non-small cell lung carcinoma; Occult nodal metastasis; Patients; Perfusion; Prevention; Prognosis; Radioisotope scanning; Risk factors; Single photon emission computed tomography; Single-photon emission tomography (SPECT) / computed tomography (CT); Small cell lung carcinoma; Statistical analysis; Tomography; Tumors; South Korea
• ISSN: 1471-2407; 1471-2407
• DOI: 10.1186/s12885-023-10846-x

Background .sup.99mTc-MAA accumulation within the tumor representing pulmonary arterial perfusion, which is variable and may have a clinical significance. We evaluated the prognostic significance of .sup.99mTc-MAA distribution within the tumor in non-small cell lung cancer (NSCLC) patients in terms of detecting occult nodal metastasis and lymphovascular invasion, as well as predicting the recurrence-free survival (RFS). Methods Two hundred thirty-nine NSCLC patients with clinical N0 status who underwent preoperative lung perfusion SPECT/CT were retrospectively evaluated and classified according to the visual grading of .sup.99mTc-MAA accumulation in the tumor. Visual grade was compared with the quantitative parameter, standardized tumor to lung ratio (TLR). The predictive value of .sup.99mTc-MAA accumulation with occult nodal metastasis, lymphovascular invasion, and RFS was assessed. Results Eighty-nine (37.2%) patients showed .sup.99mTc-MAA accumulation and 150 (62.8%) patients showed the defect on .sup.99mTc-MAA SPECT/CT. Among the accumulation group, 45 (50.5%) were classified as grade 1, 40 (44.9%) were grade 2, and 4 (4.5%) were grade 3. TLR gradually and significantly increased from grade 0 (0.009 [+ or -] 0.005) to grade 1 (0.021 [+ or -] 0.005, P < 0.05) and to grade 2-3 (0.033 [+ or -] 0.013, P < 0.05). The following factors were significant predictors for occult nodal metastasis in univariate analysis: central location, histology different from adenocarcinoma, tumor size greater than 3 cm representing clinical T2 or higher, and the absence of .sup.99mTc-MAA accumulation within the tumor. Defect in the lung perfusion SPECT/CT remained significant at the multivariate analysis (Odd ratio 3.25, 95%CI [1.24 to 8.48], p = 0.016). With a median follow-up of 31.5 months, the RFS was significantly shorter in the defect group (p = 0.008). Univariate analysis revealed that cell type of non-adenocarcinoma, clinical stage II-III, pathologic stage II-III, age greater than 65 years, and the .sup.99mTc-MAA defect within tumor as significant predictors for shorter RFS. However, only the pathologic stage remained statistically significant, in multivariate analysis. Conclusion The absence of .sup.99mTc-MAA accumulation within the tumor in preoperative lung perfusion SPECT/CT represents an independent risk factor for occult nodal metastasis and is relevant as a poor prognostic factor in clinically N0 NSCLC patients. .sup.99mTc-MAA tumor distribution may serve as a new imaging biomarker reflecting tumor vasculatures and perfusion which can be associated with tumor biology and prognosis. Keywords: Lung perfusion scintigraphy, Single-photon emission tomography (SPECT) / computed tomography (CT), .sup.99mTc-MAA, Non-small cell lung cancer, Occult nodal metastasis, Imaging biomarker.