[A Retrospective Study of Mean Computed Tomography Value to Predict the Tumor Invasiveness in AAH and Clinical Stage Ia Lung Cancer]

Quantitative analysis of imaging characteristics in lung adenocarcinoma in situ using artificial intelligence

BACKGROUND

With the rising incidence of pulmonary nodules (PNs), lung adenocarcinoma in situ (AIS) is a critical early stage of lung cancer, necessitating accurate diagnosis for early intervention. This study applies artificial intelligence (AI) for quantitative imaging analysis to differentiate AIS from atypical adenomatous hyperplasia (AAH) and minimally invasive adenocarcinoma (MIA), aiming to enhance clinical diagnosis and prevent misdiagnosis.

METHODS

The study analyzed 1215 PNs with confirmed AAH, AIS, and MIA from six centers using the Shukun AI diagnostic module. Parameters evaluated included demographic data and various CT imaging metrics to identify indicators for clinical application, focusing on the mean CT value's predictive value.

RESULTS

Significant differences were found in several parameters between AAH and AIS, with nodule mass showing the highest predictive value. When comparing AIS to MIA, total nodule volume was the best predictor, followed by the maximum CT value.

CONCLUSION

The mean CT value has limited discriminative power for AIS diagnosis. Instead, the maximum CT value and maximum 3D diameter are recommended for clinical differentiation. Nodule mass and volume of solid components are strong indicators for differentiating AIS from AAH and MIA, respectively.

ZNT1 Regulates the Proliferation, Migration and Invasion of HaCaT Cells Infected with HPV Through the PI3K/Akt Pathway

Background

Condyloma acuminatum (CA), which is a highly contagious sexually transmitted illness generated by human papillomavirus (HPV) infection, is characterized by abnormal proliferation of keratinocytes resulting in verrucous lesions. Although solute carrier family 30 member 1 (ZNT1) is highly expressed in CA tissues, the function of ZNT1 in CA remains unclear.

Methods

HPV transfection was performed in HaCaT to simulate the CA pathological environment. The mRNA and protein levels were monitored using RT-qPCR and immunoblotting. Cell viability was found using the MTT test. Cell invasion and migration were probed using the transwell and wound healing.

Results

ZNT1 expression was up-regulated in CA tissues, and HPV transfection increased the expression of ZNT1. Overexpression of ZNT1 promoted the proliferation, migration and invasion of Human immortalized keratinocyte (HaCaT) transfected with HPV. Meanwhile, ZNT1 knockdown repressed the proliferation, migration and invasion of HaCaT that HPV transfected. Further research displayed that ZNT1 promoted the proliferation, migration and invasion of HaCaT transfected with HPV through the PI3K/Akt pathway.

Conclusion

Our research confirmed that ZNT1 regulated the proliferation, migration and invasion of HaCaT transfected with HPV through the PI3K/Akt pathway, providing a new target for the effective remedy of CA.

Correlation of computed tomography quantitative parameters with tumor invasion and Ki-67 expression in early lung adenocarcinoma

The purpose of the study is to investigate the correlation of computed tomography (CT) quantitative parameters with tumor invasion and Ki-67 expression in early lung adenocarcinoma.The study involved 141 lesions in 141 patients with early lung adenocarcinoma. According to the degree of tumor invasion, the lesions were assigned into (adenocarcinoma in situ + minimally invasive adenocarcinoma) group and invasive adenocarcinoma (IAC) group. Artificial intelligence-assisted diagnostic software was used to automatically outline the lesions and extract corresponding quantitative parameters on CT images. Statistical analysis was performed to explore the correlation of these parameters with tumor invasion and Ki-67 expression.The results of logistic regression analysis showed that the short diameter of the lesion and the average CT value were independent predictors of IAC. Receiver operating characteristic curve analysis identified the average CT value as an independent predictor of IAC with the best performance, with the area under the receiver operating characteristic curve of 0.893 (P < .001), and the threshold of -450 HU. Besides, the predicted probability of logistic regression analysis model was detected to have the area under the curve of 0.931 (P < .001). The results of Spearman correlation analysis showed that the expression level of Ki-67 had the highest correlation with the average CT value of the lesion (r = 0.403, P < .001).The short diameter of the lesion and the average CT value are independent predictors of IAC, and the average CT value is significantly positively correlated with the expression of tumor Ki-67.

Determining the invasiveness of pure ground-glass nodules using dual-energy spectral computed tomography

Background

The present work aimed to investigate the clinical application of using quantitative parameters generated in the unenhanced phase (UP) and venous phase (VP) in dual-energy spectral CT for differentiating the invasiveness of pure ground-glass nodule (pGGN).

Methods

Sixty-two patients with 66 pGGNs who underwent preoperative dual-energy spectral CT in UP and VP were evaluated retrospectively. Nodules were divided into three groups based on pathology: adenocarcinoma in situ (AIS, n=19), minimally invasive adenocarcinoma (MIA, n=22) (both in the preinvasive lesion group) and invasive adenocarcinoma (IA, n=25). The iodine concentration (IC) and water content (WC) in nodules were measured in material decomposition images. The nodule CT numbers and slopes(k) were measured on monochromatic images. All measurements, including the maximum diameter of nodules were statistically compared between the AIS-MIA group and IA group.

Results

There were significant differences of WC in VP between AIS-MIA group and IA group (P<0.05). The CT attenuation values of the 40–140 keV monochromatic images in UP and VP were significantly higher for the invasive nodules. Logistic regression analysis showed that the maximum nodule diameter [odd ratio (OR) =1.21, 95% CI: 1.050–1.400, P<0.01] and CT number in 130 keV images in venous phase (OR =1.03, 95% CI: 1.014–1.047, P<0.001) independently predicted histological invasiveness.

Conclusions

The quantitative parameters in dual-energy spectral CT in the unenhanced phase and venous phase provide useful information in differentiating preinvasive lesion group from IA group of pGGN, especially the maximum nodule diameter and CT number in the 130 keV images in the venous phase.