8th Edition Tumor, Node, and Metastasis T-Stage Prognosis Discrepancies: Solid Component Diameter Predicts Prognosis Better than Invasive Component Diameter

Funai, Kazuhito; Kawase, Akikazu; Mizuno, Kiyomichi; Koyama, Satoshi; Shiiya, Norihiko

doi:10.3390/cancers12061577

Cited by 3 publications

(6 citation statements)

References 24 publications

(37 reference statements)

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“…Ahn et al reported that the kappa values for agreement between clinical T-stage and pathological T-stage were 0.53–0.69 10 . In the present study, the kappa values for agreement between clinical T stage determined by virtual TSCT and the pathological T stage was 0.59 in both observers, which was consistent with the results of Ahn et al Interestingly, in the article by Funai et al, clinical T-stage based on TSCT was more correlated with the postoperative recurrence than with the pathological T-stage based on the invasive size 21 . Therefore, we speculate that the clinical T-stage measured by virtual TSCT may also be correlated with prognosis.…”

Section: Discussionsupporting

confidence: 92%

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Measurement of solid size in early-stage lung adenocarcinoma by virtual 3D thin-section CT applied artificial intelligence

Iwano,

Kamiya,

Ito

et al. 2023

Sci Rep

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An artificial intelligence (AI) system that reconstructs virtual 3D thin-section CT (TSCT) images from conventional CT images by applying deep learning was developed. The aim of this study was to investigate whether virtual and real TSCT could measure the solid size of early-stage lung adenocarcinoma. The pair of original thin-CT and simulated thick-CT from the training data with TSCT images (thickness, 0.5–1.0 mm) of 2700 pulmonary nodules were used to train the thin-CT generator in the generative adversarial network (GAN) framework and develop a virtual TSCT AI system. For validation, CT images of 93 stage 0–I lung adenocarcinomas were collected, and virtual TSCTs were reconstructed from conventional 5-mm thick-CT images using the AI system. Two radiologists measured and compared the solid size of tumors on conventional CT and virtual and real TSCT. The agreement between the two observers showed an almost perfect agreement on the virtual TSCT for solid size measurements (intraclass correlation coefficient = 0.967, P < 0.001, respectively). The virtual TSCT had a significantly stronger correlation than that of conventional CT (P = 0.003 and P = 0.001, respectively). The degree of agreement between the clinical T stage determined by virtual TSCT and the clinical T stage determined by real TSCT was excellent in both observers (k = 0.882 and k = 0.881, respectively). The AI system developed in this study was able to measure the solid size of early-stage lung adenocarcinoma on virtual TSCT as well as on real TSCT.

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Section: Discussionsupporting

confidence: 92%

“…However, it was comparable to the clinical T stage determined by real TSCT. Several previous studies have reported a difference between clinical TNM stages and pathological stages 7 , 10 , 15 , 21 . Ahn et al reported that the kappa values for agreement between clinical T-stage and pathological T-stage were 0.53–0.69 10 .…”

Section: Discussionmentioning

confidence: 89%

Measurement of solid size in early-stage lung adenocarcinoma by virtual 3D thin-section CT applied artificial intelligence

Iwano,

Kamiya,

Ito

et al. 2023

Sci Rep

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“…A total of 84 patients (58 male and 26 female) with lung cancer with a mean age of 60.78 years (range, 37–87) were enrolled in the present study. According to the International Association for the Study of Lung Cancer Staging Project ( 29 ), various clinical stages were present among the enrolled patients, including three cases at stage I, five cases at stage III and 76 cases at stage IV. Detailed clinical characteristics of the patients are presented in Table I .…”

Section: Resultsmentioning

confidence: 99%

A three serum miRNA panel as diagnostic biomarkers of radiotherapy‑related metastasis in non‑small cell lung cancer

Lv¹,

An²,

Zhang³

et al. 2020

Oncol Lett

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Serum microRNAs (miRNAs) have been implicated as noninvasive biomarkers for lung cancer diagnosis. However, there are no sensitive and specific biomarkers for the detection of radiotherapy-related non-small cell lung cancer (NSCLC) metastasis. The present study aimed to investigate the role of three serum miRNAs, namely miRNA (miR)-130a, miR-25 and miR-191 * , in diagnosing NSCLC, and their biological functions in radiation-mediated development of metastatic properties in A549 cells. To determine this, serum samples were collected from 84 patients with NSCLC and 42 age-and sex-matched healthy controls. Differential expression of serum miRNAs was analyzed by quantitative PCR. Significant associations between miRNA expression and overall survival of patients with NSCLC were identified using the Cox proportional regression model. A receiver operating characteristic curve was generated to evaluate diagnostic accuracy. The functions of miR-130a, miR-25 and miR-191 * in lung cancer cells were studied by transfecting A549 cells with miRNA mimics and inhibitors. The results of the present study demonstrated that the expression levels of miR-130a, miR-25 and miR-191 * in the serum of patients with NSCLC were increased compared with those in healthy controls, and these increases were associated with advanced age (≥60 years), radiotherapy, histological type (squamous carcinoma), low survival rate and low median survival time. Additionally, irradiation induced the upregulation of miR-130a, miR-25 and miR-191 * expression in A549 cells in vitro and in a xenograft mouse model. Irradiation also promoted the invasiveness of A549 cells in vitro and metastasis in vivo. In conclusion, miR-130a, miR-25 and miR-191 * may be potential biomarkers for the diagnosis of patients with NSCLC and may serve oncogenic roles in radiation-mediated metastasis of NSCLC.

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“…However, a recent study proposed that the clinical T category may be a better prognostic indicator than the pathological T category. 32 Second, variants of invasive adenocarcinoma were not included (e.g., invasive mucinous, colloid, fetal, and enteric adenocarcinoma). 3 In addition, the latest reported histologic subtypes were not assessed.…”

Section: Discussionmentioning

confidence: 99%

“…Indeed, a recent study reported that the solid portion size on CT demonstrated a better prognostic correlation than the invasive component size. 32 The longest diameter of the solid portion was measured on the lung window setting (window width, 1500 HU; level, -700 HU). All measurements were performed in the axial plane using an electronic caliper by one of the two trained radiology technicians (either M.L.…”

Section: Data Collectionmentioning

confidence: 99%

Prognostic Implications of the Predominant Histologic Subtype in Stage I Lung Adenocarcinoma: Lack of Association with Overall Survival Based on Multi-Aspect Survival Analyses

Lee

Kim

Park

et al. 2022

Preprint

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We aimed to investigate the prognostic role of the predominant histologic subtype classification of lung adenocarcinoma in the era of the eighth-edition staging system. A total of 587 patients with stage I adenocarcinomas (lepidic, n=46; acinar/papillary, n=484; solid/micropapillary, n=57) were assessed. The prognostic value of this subtype classification for overall survival (OS) was investigated with three multivariable analyses adjusted for the eighth-edition clinical T category and radiologic nodule type: the adjusted log-rank test, multivariable Cox hazard regression, and multivariable mixture cure model to evaluate long-term and short-term prognostic associations separately. In the adjusted log-rank test for pairwise comparisons, no evidence was found for differences in OS among the subtype classifications (p>.05). The histologic subtype was not an independent prognostic factor in either the Cox regression analysis (hazard ratio [HR] of acinar/papillary subtypes: 3.03; 95% confidence intertval [CI]: 0.4-22.59; p=0.28; HR of solid/micropapillary subtypes: 2.78; 95% CI: 0.34-22.37; p=.34) or the mixture cure model (cure probability model; odds ratio: 1.06 [95% CI: 0.38-2.95; p=.91]; failure time distribution model; HR: 0.94 [95% CI: 0.36-2.44; p=.89]). The prognostic implication of the predominant histologic subtype classification is not clear for stage I lung adenocarcinoma in the eighth-edition staging system.

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8th Edition Tumor, Node, and Metastasis T-Stage Prognosis Discrepancies: Solid Component Diameter Predicts Prognosis Better than Invasive Component Diameter

Cited by 3 publications

References 24 publications

Measurement of solid size in early-stage lung adenocarcinoma by virtual 3D thin-section CT applied artificial intelligence

Measurement of solid size in early-stage lung adenocarcinoma by virtual 3D thin-section CT applied artificial intelligence

A three serum miRNA panel as diagnostic biomarkers of radiotherapy‑related metastasis in non‑small cell lung cancer

Prognostic Implications of the Predominant Histologic Subtype in Stage I Lung Adenocarcinoma: Lack of Association with Overall Survival Based on Multi-Aspect Survival Analyses

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