Choi Yeonu, Kim Jonghoon, Park Hyunjin, Kim Hong Kwan, Kim Jhingook, Jeong Ji Yun, Ahn Joong Hyun, Lee Ho Yun
Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), 81 Irwon-Ro, Gangnam-Gu, Seoul 06351, Korea.
Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea.
Cancers (Basel). 2021 Jun 4;13(11):2785. doi: 10.3390/cancers13112785.
Prognostic considerations for non-predominant patterns are necessary because most lung adenocarcinomas (ADCs) have a mixed histologic pattern, and the spectrum of actual prognosis varies widely even among lung ADCs with the same most predominant pattern. We aimed to identify prognostic stratification by second most predominant pattern of lung ADC and to more accurately assess prognostic factors with CT imaging analysis, particularly enhancing non-predominant but high-grade pattern.
In this prospective study, patients with early-stage lung ADC undergoing curative surgery underwent preoperative dual-energy CT (DECT) and positron emission tomography (PET)/CT. Histopathology of ADC, the most predominant and second most predominant histologic patterns, and preoperative imaging parameters were assessed and correlated with patient survival.
Among the 290 lung ADCs included in the study, 231 (79.7%) were mixed-pathologic pattern. When the most predominant histologic pattern was intermediate-grade, survival curves were significantly different among the three second most predominant subgroups ( = 0.004; low, lepidic; intermediate, acinar and papillary; high, micropapillary and solid). When the second most predominant pattern was high-grade, recurrence risk increased by 4.2-fold compared with the low-grade group ( = 0.005). To predict a non-predominant but high-grade pattern, the non-contrast CT value of tumor was meaningful with a lower HU value associated with the histologic combination of lower grade (low-grade as most predominant and intermediate-grade as second most predominant pattern, OR = 6.15, = 0.005; intermediate-grade as most predominant and high-grade as second most predominant pattern, OR = 0.10, = 0.033). SUVmax of the tumor was associated with the non-predominant but high-grade pattern, especially in the histologic combination of intermediate-high grade (OR = 1.14, = 0.012).
The second most predominant histologic pattern can stratify lung ADC patients according to prognosis. Thus, predicting the malignant potential and establishing treatment policies should not rely only on the most predominant pattern. Moreover, imaging parameters of non-contrast CT value and SUVmax could be useful in predicting a non-predominant but high-grade histologic pattern.
由于大多数肺腺癌（ADC）具有混合组织学模式，且即使在具有相同最主要模式的肺ADC中，实际预后范围也差异很大，因此对非主要模式进行预后考量很有必要。我们旨在通过肺ADC的第二主要模式确定预后分层，并通过CT成像分析更准确地评估预后因素，特别是增强的非主要但高级别模式。
在这项前瞻性研究中，接受根治性手术的早期肺ADC患者接受了术前双能CT（DECT）和正电子发射断层扫描（PET）/CT检查。评估了ADC的组织病理学、最主要和第二主要组织学模式以及术前成像参数，并将其与患者生存率相关联。
在纳入研究的290例肺ADC中，231例（79.7%）为混合病理模式。当最主要组织学模式为中级时，三个第二主要亚组的生存曲线有显著差异（P = 0.004；低级别，鳞屑状；中级，腺泡状和乳头状；高级别，微乳头状和实性）。当第二主要模式为高级别时，与低级别组相比，复发风险增加了4.2倍（P = 0.005）。为了预测非主要但高级别的模式，肿瘤的平扫CT值具有意义，较低的HU值与较低级别的组织学组合相关（低级别为最主要且中级为第二主要模式，OR = 6.15，P = 当中级为最主要且高级别为第二主要模式，OR = 0.10，P = 0.033）。肿瘤的SUVmax与非主要但高级别的模式相关，特别是在中级 - 高级别的组织学组合中（OR = 1.14，P = 0.012）。
第二主要组织学模式可根据预后对肺ADC患者进行分层。因此，预测恶性潜能和制定治疗策略不应仅依赖于最主要模式。此外，平扫CT值和SUVmax的成像参数可用于预测非主要但高级别的组织学模式。 0.005；
