Results from this study demonstrated that as for lung adenocarcinoma manifesting as SSN, the largest diameter of SSN measured on HRCT image was greater than that measured pathologically, but there was a positive correlation between HRCT and pathological measurements; secondly, the discrepancy between HRCT and pathological measurements was correlated with the ratio of GGO in the SSN. These findings to a certain degree help explain the reason why the largest diameter of a tumor measured pathologically was smaller than that measured manually or semi-automatically on HRCT scans, and further suggest that alveolar collapse is likely to be one of important factors that lead to the discrepancy between HRCT and pathological measurements.
For patients with lung cancer, the size of tumor is one of important factors influencing the prognosis. According to the latest TNM staging system, the largest tumor diameter measured pathologically is a reference for evaluating the stage of a tumor, however, in the clinic, CT measurement of the largest tumor diameter is an important method used to preoperatively evaluate the stage of a tumor, and the clinical stage and the pathological stage are not always consistent (11). This is also true for the lung adenocarcinoma manifesting as SSN.
The discrepancy of the largest diameter of SSN between HRCT and pathological measurements has specific characteristics and interpretation. It is difficult to gauge the largest diameter of SSN on HRCT image owing to the unclear boundary between SSN and the surrounding normal lung tissue and irregular SSN morphology. Isaka et al (14) demonstrated that after specimen fixation by formalin, pathological tumor size was significantly less than CT tumor size, and the discrepancy between CT and pathological measurements in GGO ratio > 50% tumors was significantly larger than in GGO ratio < 50% tumors. Therefore, they suggest that for the pathologically diagnosed lung adenocarcinoma manifesting as SSN, the resected lung specimen should be sufficiently inflated with physical saline to prevent the shrinking of the lepidic component in the tumor, because under the condition of sufficient inflation, there was a well correlation between CT tumor size and pathological tumor size. These findings were consistent with some results from the present study. This confirms that alveolar collapse is a factor leading to the discrepancy between CT tumor size and pathological tumor size and GGO ratio greatly influences the discordance (14).
Tumor clinical stage and pathological stage are not completely consistent. As for lung adenocarcinoma manifesting as SSN, GGO ratio is another important factor related to patient’s prognosis, and it is also one of important factors that influence the prognosis of lung adenocarcinoma in addition to TNM staging. Results from this study have demonstrated that as for SSN, GGO ratio to a certain degree contributes to the discrepancy between tumor clinical stage and pathological stage, i.e., higher GGO ratio indicates a smaller pathological tumor size, which to a certain degree suggests a better prognosis of lung adenocarcinoma manifesting as SSN (15, 16). It is worth noting that the correlation between manual and pathological measurements of tumor size is superior to that between semi-automatic and pathological measurements of tumor size. This occurs possibly because the lung nodule analysis software can automatically measure the largest diameter of an irregular nodule three-dimensionally, and the largest diameter of SSN measured manually is always less than that measured semi-automatically; however, pathological tumor size is often determined by randomly selecting the subjectively considered largest diameter on tissue specimens, and pathological tumor size is often less than the length of the true largest diameter of a tumor.
Vazquez et al. (15) conducted a study regarding low-dose CT screening for lung cancer and found that with the reduction in lepidic components, GGO ratio on HRCT decreases, and simultaneously the number of patients with tumors invading pleura, blood vessels, lymphatic vessels and bronchi increases proportionally. Nakata et al. (3) analyzed the imaging data of 146 T1N0M0 peripheral non-small cell lung cancers and they concluded that GGO ratio well correlated with histological classification, pathological invasiveness and prognosis, tumors with GGO ratio > 50% have a better prognosis because patients with tumors that have GGO ratio > 50% can receive limited surgical resection, for example pulmonary lobectomy or segmentectomy. Based on evidence that in patients with lung adenocarcinoma, GGO ratio and vessel invasion by the lesion on HRCT have a great predictive value, the largest diameter or volume of GGO should be considered when measuring GGO ratio, and use of analysis software for GGO volume measurement is reproducible (17, 18). Oda et al. (19) calculated the volume-doubling time of SSN and demonstrated that the largest diameter of SSN was not significantly correlated with the doubling time of tumor (r = -0.19, P = 0.19). Therefore, this suggests that to a certain degree the largest diameter of SSN is of limited value in tumor prognosis evaluation. On the contrary, there is a certain correlation between lesion density and doubling time (r = -0.57, P < 0.01), demonstrating that the ratio of solid component is of important value for evaluating tumor prognosis (19). As for part solid nodule, the largest diameter of the solid component is considered as a more reliable index used for evaluating tumor prognosis (5). Lee et al. (13) reported that the size of solid component on CT image well correlates with pathological tumor size. As for SSN, the ratio of solid component in the total lesion volume on CT image is one of the important factors influencing patient’s prognosis in addition to the TNM staging. Therefore, when evaluating SSN, the size and ratio of solid component are important supplements for simple measurement of the largest diameter of SSN and are important indices for prognosis evaluation in addition to the TNM staging. With continuing improvement in CT technology, computer-aided measurement of SSN has attracted increasing attention, and the accuracy of SSN parameter measurement is also gradually increased. Sumikawa et al. (20) analyzed the records of 49 patients with lung adenocarcinoma manifesting as SSN smaller than 2 cm in diameter. Measurement of solid component ratio using semi-automated lung nodule analysis software is reproducible, and semi-automatic measurement of solid component ratio is more reproducible than semi-automatic measurement of the largest diameter and area ratios (20).
This study has several limitations. First, it is a retrospective study, selection bias exists in patient inclusion, the proportion of pure SSN cases is very low, and the majority of included cases have invasive adenocarcinoma with lepidic growth, the largest diameter of the invasive adenocarcinomas with lepidic growth is greater than the pure GGN, and relatively speaking, the measurement bias is small in pure GGN. Second, pathological tumor size is determined by measuring the largest diameter of tumor based on a randomly selected plane, and it is difficult to ensure that pathological tumor size correspond to semi-automatically measured tumor size one by one. In addition, the size of pathologically infiltrated component was not measured because this was not performed in the routine pathological section measurement. Third, pathological measurement was performed after formalin fixation, so it is difficult to avoid the influence of formalin fixation on the shrinkage of the tissue. Fourth, the solid component on HRCT cannot completely correspond to the infiltrated component on pathological section, because alveolar collapse and fibrous connective tissue proliferation also manifest as solid component on HRCT scans, which influence SSN measurement in some diseases.
5.1. In Conclusion
Taken together, HRCT measurement of the largest diameter of SSN correlates with its pathological measurement, but HRCT tumor size is greater than pathological tumor size. GGO ratio correlates with the discrepancy between HRCT tumor size and pathological tumor size, which to a certain degree explains that alveolar collapse is one of causes of the discordance between HRCT and pathological measurements.
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