HRCT features between lepidic-predominant type and other pathological subtypes in early-stage invasive pulmonary adenocarcinoma appearing as a ground-glass nodule

Background Different pathological subtypes of invasive pulmonary adenocarcinoma (IPA) have different surgical methods and heterogeneous prognosis. It is essential to clarify IPA subtypes before operation and high-resolution computed tomography (HRCT) plays a very important role in this regard. We aimed to investigate the HRCT features of lepidic-predominant type and other pathological subtypes of early-stage (T1N0M0) IPA appearing as a ground-glass nodule (GGN). Methods We performed a retrospective analysis on clinical data and HRCT features of 630 lesions in 589 patients with pathologically confirmed IPA (invasive foci > 5 mm) appearing as pure GGN (pGGN) and mixed GGN (mGGN) with consolidation-to-tumor ratio (CTR) ≤0.5 from January to December 2019. All GGNs were classified as lepidic-predominant adenocarcinoma (LPA) and nonlepidic-predominant adenocarcinoma (n-LPA) groups. Univariate analysis was performed to analyze the differences of clinical data and HRCT features between the LPA and n-LPA groups. Multivariate analysis was conducted to determine the variables to distinguish the LPA from n-LPA group independently. The diagnostic performance of different parameters was compared using receiver operating characteristic curves. Results In total, 367 GGNs in the LPA group and 263 GGNs in the n-LPA group were identified. In the univariate analysis, the CTR, mean CT values, and mean diameters as well as mixed GGN, deep lobulation, spiculation, vascular change, bronchial change, and tumor–lung interface were smaller in the LPA group than in the n-LPA group (P < 0.05). Logistic regression model was reconstructed including the mean CT value, CTR, deep lobulation, spiculation, vascular change, and bronchial change (P < 0.05). Area under the curve of the logistic regression model for differentiating LPA and n-LPA was 0.840 (76.4% sensitivity, 78.7% specificity), which was significantly higher than that of the mean CT value or CTR. Conclusions Deep lobulation, spiculation, vascular change, and bronchial change, CT value > − 472.5 HU and CTR > 27.4% may indicate nonlepidic predominant invasive pulmonary adenocarcinoma in GGNs.

HRCT Features Between Lepidic-Predominant Type and Other Pathological Subtypes in Early-Stage Invasive Pulmonary Adenocarcinoma Appearing as a Ground-Glass Nodule

Background: We aimed to investigate the high-resolution computed tomography (HRCT) features of lepidic-predominant type and other pathological subtypes of early-stage (T1N0M0) invasive pulmonary adenocarcinoma appearing as a ground-glass nodule (GGN). Methods: We performed a retrospective analysis on clinical data and HRCT features of 630 lesions in 589 patients with pathologically confirmed invasive pulmonary adenocarcinomas presenting as pure GGN and mixed GGN [consolidation-to-tumor ratio (CTR), <0.5] from January to December 2019. All GGNs were classified as lepidic-predominant adenocarcinoma (LPA) and nonlepidic-predominant adenocarcinoma (n-LPA) groups. Univariate analysis was performed to analyze the difference of clinical data and HRCT features between the LPA and n-LPA groups. Multivariate analysis was conducted to determine the variables to distinguish the LPA from n-LPA group independently. The diagnostic performance of different parameters was compared using receiver operating characteristic curves. Results: In total, 367 GGNs in the LPA group and 263 GGNs in the n-LPA group were identified. In the univariate analysis, the CTR, mean computed tomography (CT) values, and mean diameters as well as mixed GGN, deep lobulation, spiculation, vascular change, bronchial change, and tumor–lung interface were smaller in the LPA group than in the n-LPA group (P < 0.05). Logistic regression model was reconstructed including the mean CT value, deep lobulation, and vascular change (P < 0.001), as well as CTR, spiculation, and bronchial change (P < 0.05). Area under the curve of the logistic regression model for differentiating LPA and n-LPA was 0.840 (76.4% sensitivity, 78.7% specificity), which was significantly higher than that of the mean CT value or CTR (both P < 0.05). Conclusions: HRCT features were helpful in differentiating lepidic-predominant type from other subtypes in early-stage GGN invasive pulmonary adenocarcinoma. The mean CT value of <−472.5 HU and CTR of <27.4% were highly suspected in lepidic-predominant invasive pulmonary adenocarcinoma.

Photoacoustic 3D imaging detects potential microvascular injuries

The photoacoustic imaging (PAI) system is an emerging imaging modality that can be useful in clinical diagnostic testing. Previous studies have shown utility of PAI in diagnosing breast cancer, visualizing vascular change in ageing, and planning flap reconstruction surgeries. In this study, we show that PAI can be used to non-invasively visualize microvascular injuries in smokers, and in a vasculitis patient.We used two prototype PAI systems, PAI-03, and PAI-04 in this study. These systems were equipped with hemisphere-detector arrays, and used lasers at wavelengths of 795 nm (PAI-03), 756 and 797nm (PAI-04). Healthy volunteers and a patient diagnosed with vasculitis were enrolled upon obtaining written informed consent. The whole hand of the volunteers was scanned.We noted there were unique circular structures that we coined “minute signals”. There were higher number of minute signals in smokers than in non-smokers. Enhanced minute signals were noted in the patient with vasculitis. In this patient, minute signals were suggested to have lower oxygenated hemoglobin content, likely suggesting blood clots or hemorrhage. Our study shows PAI systems can visualize unappreciated abnormalities in fine vasculatures non-invasively. Use of PAI can extend to other clinical entities with suspected vascular involvement.