Dynamic surface reconstruction of individual gold nanoclusters by using a co-reactant enables color-tunable electrochemiluminescence.

Here we report for the first time the phenomenon of continuously color-tunable electrochemiluminescence (ECL) from individual gold nanoclusters (Au NCs) confined in a porous hydrogel matrix by adjusting the concentration of the co-reactant. Specifically, the hydrogel-confined Au NCs exhibit strong dual-color ECL in an aqueous solution with triethylamine (TEA) as a co-reactant, with a record-breaking quantum yield of 95%. Unlike previously reported Au NCs, the ECL origin of the hydrogel-confined Au NCs is related to both the Au(0) kernel and the Au(i)-S surface. Surprisingly, the surface-related ECL of Au NCs exhibits a wide color-tunable range of 625-829 nm, but the core-related ECL remains constant at 489 nm. Theoretical and experimental studies demonstrate that the color-tunable ECL is caused by the dynamic surface reconstruction of Au NCs and TEA radicals. This work opens up new avenues for dynamically manipulating the ECL spectra of core-shell emitters in biosensing and imaging research.

Predictive value of 18 F-FDG PET/CT and serum tumor markers for tumor mutational burden in patients with non-small cell lung cancer.

PURPOSE: To investigate the correlations between metabolic parameters (MPs) of 18 F-fluorodeoxyglucose (FDG) uptake on positron emission tomography/computed tomography (PET/CT), serum tumor markers (STMs), and tumor mutational burden (TMB) in patients with non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: In this retrospective study, we enrolled 129 patients with NSCLC (males, 78; females, 51) who underwent baseline TMB and STM tests and 18 F-FDG PET/CT scans before treatment between March 2018 and September 2022. Patients were categorized into TMB-high (TMB ≥10 mutations/Mb; n = 27 [20.9%]) and non-TMB-high (TMB <10 mutations/Mb; n = 102 [79.1%]) groups. Binary logistic regression analyses were performed to determine independent predictors of TMB-high. Univariate and multivariate linear regression analyses were performed to determine independent predictors of TMB level on a log scale. Subgroup analyses for adenocarcinoma (ADC), ADC with EGFR+, ADC with EGFR-, and squamous cell carcinoma (SCC) were performed. RESULTS: For ADC, all MPs (SULpeak , SULmax , SULmean , MTV, and TLG) were significantly higher in the TMB-high group than the non-TMB-high group; smoker (odds ratio [OR] = 27.08, p = 0.018), EGFR+ (OR = 0.03, p = 0.033), KRAS+ (OR = 7.98, p = 0.083), high CEA (OR = 33.56, p = 0.029), and high CA125 (OR = 13.68, p = 0.030) were independent predictors of TMB-high; and all MPs showed significant positive linear correlations with TMB on a log scale, with SULpeak as an independent predictor. However, no significant correlation was observed for SCC. CONCLUSION: MPs and STMs can predict the TMB level for patients with ADC, and may serve as potential substitutes for TMB with increased value and easy implementation in guiding immunotherapy through noninvasive methods.

Efficacy, Safety, and Biomarker Analysis of Neoadjuvant Camrelizumab and Apatinib in Patients With Resectable NSCLC: A Phase 2 Clinical Trial.

INTRODUCTION: Camrelizumab (an anti-programmed cell death protein-1 antibody) combined with apatinib (an antiangiogenic agent) has conferred benefits for advanced NSCLC. We aimed to assess the activity and safety of neoadjuvant camrelizumab plus apatinib in patients with resectable NSCLC. METHODS: In this phase 2 trial, patients with histologically confirmed resectable stages IIA to IIIB NSCLC (stage IIIB, T3N2 only) received intravenous camrelizumab (200 mg) every 2 weeks for three cycles and oral apatinib (250 mg) once daily for 5 days followed by 2 days off for 6 weeks. Surgery was planned 3 to 4 weeks after apatinib discontinuation. The primary end point was major pathologic response (MPR) rate, assessed in patients who received at least one dose of neoadjuvant treatment and underwent surgery. RESULTS: Between November 9, 2020, and February 16, 2022, 78 patients were treated and 65 (83%) underwent surgery. All 65 patients achieved an R0 surgical resection. Among the 65 patients, 37 (57%, 95% confidence interval [CI]: 44%-69%) had an MPR, of whom 15 (23%, 95% CI: 14%-35%) had a pathologic complete response (pCR). Pathologic responses observed in squamous cell NSCLC were superior to adenocarcinoma (MPR: 64% versus 25%; pCR: 28% versus 0%). The radiographic objective response rate was 52% (95% CI: 40%-65%). Among all the 78 enrolled patients, 37 (47%, 95% CI: 36%-59%) had an MPR, of whom 15 (19%, 95% CI: 11%-30%) had a pCR. Four (5%) of 78 patients had grade 3 neoadjuvant treatment-related adverse events. No grade 4 or 5 treatment-related adverse events occurred. Receiver operating characteristic analysis revealed a significant correlation between the maximum reduction of standard uptake values and pathologic response (R = 0.619, p < 0.0001). In addition, baseline programmed death-ligand 1 expression, HOXA9 and SEPT9 methylation levels, and circulating tumor DNA status before surgery were associated with pathologic responses. CONCLUSIONS: Neoadjuvant camrelizumab plus apatinib was found to have promising activity and manageable toxicity in patients with resectable stages IIA to IIIB NSCLC, which might be a potential therapeutic option in neoadjuvant setting.

AgInZnS quantum dots as anodic emitters with strong and stable electrochemiluminescence for biosensing application.

Quantum dots (QDs) have become promising electrochemiluminescence (ECL) emitters with high quantum yield and size-tunable luminescence. However, most QDs generate strong ECL emission at the cathode, developing anodic ECL-emitting QDs with excellent performance is challenging. In this work, low-toxic quaternary AgInZnS QDs synthesized by a one-step aqueous phase method were used as novel anodic ECL emitters. AgInZnS QDs exhibited strong and stable ECL emission and a low excitation potential, which could avoid the side reaction of oxygen evolution. Furthermore, AgInZnS QDs displayed high ECL efficiency (ΦECL) of 5.84, taking the ΦECL of Ru(bpy)32+/tripropylamine (TPrA) ECL system as 1. Compared to AgInS2 QDs without Zn doping and traditional anode luminescent CdTe QDs, the ECL intensity of AgInZnS QDs was 1.62 times and 3.64 times higher than that of AgInS2 QDs and CdTe QDs, respectively. As a proof-of-concept, we further designed an "on-off-on" ECL biosensor for detecting microRNA-141 based on a dual isothermal enzyme-free strand displacement reaction (SDR), which not only to achieve the cyclic amplification of the target and ECL signal, but also to construct a switch of the biosensor. The ECL biosensor had a wide linear range from 100 aM to 10 nM with a low detection limit of 33.3 aM. Together, the constructed ECL sensing platform is a promising tool for rapid and accurate diagnosis of clinical diseases.

Association of Clinical and Radiological Features with Disease Severity of Symptomatic Immune Checkpoint Inhibitor-Related Pneumonitis.

OBJECTIVES: To investigate the predictive ability of clinical and chest computed tomography (CT) features to predict the severity of symptomatic immune checkpoint inhibitor-related pneumonitis (CIP). METHODS: This study included 34 patients diagnosed with symptomatic CIP (grades 2-5) and divided into mild (grade 2) and severe CIP (grades 3-5) groups. The groups' clinical and chest CT features were analyzed. Three manual scores (extent, image finding, and clinical symptom scores) were conducted to evaluate the diagnostic performance alone and in combination. RESULTS: There were 20 cases of mild CIP and 14 cases of severe CIP. More severe CIP occurred within 3 months than after 3 months (11 vs. 3 cases, p = 0.038). Severe CIP was significantly associated with fever (p < 0.001) and the acute interstitial pneumonia/acute respiratory distress syndrome pattern (p = 0.001). The diagnostic performance of chest CT scores (extent score and image finding score) was better than that of clinical symptom score. The combination of the three scores demonstrated the best diagnostic value, with an area under the receiver operating characteristic curve of 0.948. CONCLUSIONS: The clinical and chest CT features have important application value in assessing the disease severity of symptomatic CIP. We recommend the routine use of chest CT in a comprehensive clinical evaluation.

Radiomic-signature changes after early treatment improve the prediction of progression-free survival in patients with advanced anaplastic lymphoma kinase-positive non-small cell lung cancer.

BACKGROUND: The prognosis of lung cancer varies widely, even in cases wherein the tumor stage, genetic mutation, and treatment regimens are the same. Thus, an effective means for risk stratification of patients with lung cancer is needed. PURPOSE: To develop and validate a combined model for predicting progression-free survival and risk stratification in patients with advanced anaplastic lymphoma kinase (ALK)-positive non-small cell lung cancer (NSCLC) treated with ensartinib. MATERIAL AND METHODS: We analyzed 203 tumor lesions in 114 patients and evaluated average radiomic feature measures from all lesions at baseline and changes in these features after early treatment (Δradiomic features). Combined models were developed by integrating clinical with radiomic features. The prediction performance and clinical value of the proposed models were evaluated using receiver operating characteristic analysis, calibration curve, decision curve analysis (DCA), and Kaplan-Meier survival analysis. RESULTS: Both the baseline and delta combined models achieved predictive efficacy with a high area under the curve. The calibration curve and DCA indicated the high accuracy and clinical usefulness of the combined models for tumor progression prediction. In the Kaplan-Meier analysis, the delta and baseline combined models, Δradiomic signature, and two selected clinical features could distinguish patients with a higher progression risk within 42 weeks. The delta combined model had the best performance. CONCLUSION: The combination of clinical and radiomic features provided a prognostic value for survival and progression in patients with NSCLC receiving ensartinib. Radiomic-signature changes after early treatment could be more valuable than those at baseline alone.

Genomic features and tumor immune microenvironment alteration in NSCLC treated with neoadjuvant PD-1 blockade.

Several clinical trials have shown the safety and effectiveness of PD-1/PD-L1 inhibitors in neoadjuvant therapy in resectable non-small cell lung cancer (NSCLC). However, 18-83% patients can benefit from it. In this study, we aimed to assess the association of PD-L1 expression, tumor mutation burden, copy number alteration (CNA, including copy number gain and loss) burden with the pathologic response to neoadjuvant PD-1 blockade and investigate the changes in the tumor immune microenvironment (TIME) during neoadjuvant immunotherapy in NSCLC. Pre-immunotherapy treatment tumor samples from twenty-nine NSCLC patients who received neoadjuvant immunotherapy with sintilimab, an anti-PD-1 drug, were subjected to targeted DNA sequencing and PD-L1 immunochemistry staining. The pathological response was positively correlated with tumor proportion score (TPS) of PD-L1 and negatively correlated with copy number gain (CNgain) burden. Of note, the combination of CNgain burden and TPS can better stratify major pathological response (MPR) patients than did CNgain or TPS alone. Whereas, TMB showed a limited correlation with pathological regression. Additionally, PD-1 blockade led to an increase in CD8+PD-1-T cells which was clinically relevant to MPR as evaluated by multiplex immunofluorescence. A significant reduction in CD19+ cells was observed in the Non-MPR group but not in the MPR group, indicating the involvement of B cells in improving neoadjuvant immunotherapy response in NSCLC. Together, our study provides new data for the correlation of PD-L1 expression and genomic factors with drug response in neoadjuvant immunotherapy settings in NSCLC. The changes of TIME may provide novel insight into the immune responses to neoadjuvant anti-PD-1 therapy.

Association of anaplastic lymphoma kinase variants and alterations with ensartinib response duration in non-small cell lung cancer.

BACKGROUND: Here, we aimed to assess the association of ALK variants and alterations with ensartinib response duration in NSCLC, and explore the potential value of computed tomography (CT) radiomic features in predicting progression-free survival (PFS). METHODS: We enrolled 88 patients with identified ALK variant NSCLC in a multicenter phase 2 trial, and assessed the impact of ALK variants and secondary ALK alterations on the clinical outcome (response duration) of patients receiving ensartinib. We also established a multifactorial model of clinicopathological and quantitative CT radiomic features to predict PFS and risk stratification. Kaplan-Meier analysis was conducted to identify risk factors for tumor progression. RESULTS: Univariate analysis indicated a statistical difference (p = 0.035) in PFS among ALK variants in three classifications (V1, V3, and other variants). Secondary ALK alterations were adversely associated with PFS both in univariate (p = 0.008) and multivariate (p = 0.04) analyses and could identify patients at high risk for early progression in the Kaplan-Meier analysis (p = 0.002). Additionally, response duration to crizotinib <1 year and liver metastasis were adversely associated with PFS. The combined model, composed of clinicopathological signature and CT radiomic signature, showed good prediction ability with the area under the receiver operating characteristic curve being 0.85, and 0.89 in the training and validation dataset respectively. CONCLUSIONS: Our study showed that secondary ALK alterations were adversely associated with ensartinib efficacy, and that ALK variants might not correlate with PFS. The quantitative radiomic signature provided added prognostic prediction value to the clinicopathological features.

Automatic segmentation of pulmonary lobes on low-dose computed tomography using deep learning.

BACKGROUND: To develop and validate a fully automated deep learning-based segmentation algorithm to segment pulmonary lobe on low-dose computed tomography (LDCT) images. METHODS: This study presents an automatic segmentation of pulmonary lobes using a fully convolutional neural network named dense V-network (DenseVNet) on lung cancer screening LDCT images. A total of 160 LDCT cases for lung cancer screening (100 in the training set, 10 in the validation set, and 50 in the test set) was included in this study. Specifically, the template of pulmonary lobes (the right lung consists of three lobes, and the left lung consists of two lobes) were obtained from pixel-level annotations by semiautomatic segmentation platform. Then, the model was trained under the supervision of the LDCT training set. Finally, the trained model was used to segment the LDCT in the test set. Dice coefficient, Jaccard coefficient, and Hausdorff distance were adopted as evaluation metrics to verify the performance of our segmentation model. RESULTS: In this study, the model achieved the accurate segmentation of each pulmonary lobe in seconds without the intervention of researchers. The testing set consisted 50 LDCT cases were used to evaluate the performance of the segmentation model. The all-lobes Dice coefficient of the test set was 0.944, the Jaccard coefficient was 0.896, and the Hausdorff distance was 92.908 mm. CONCLUSIONS: The segmentation model based on LDCT can automatically and robustly and efficiently segment pulmonary lobes. It will provide effective location information and contour constraints for pulmonary nodule detection on LDCT images for lung cancer screening, which may have potential clinical application.

MRI radiomic signature predicts intracranial progression-free survival in patients with brain metastases of ALK-positive non-small cell lung cancer.

BACKGROUND: Intracranial progression is considered an important cause of treatment failure in anaplastic lymphoma kinase (ALK)-positive non-small cell lung cancer (NSCLC) patients. Recent advances in targeted therapy and radiomics have generated considerable interest for the exploration of prognostic imaging biomarkers to predict the clinical course. Here, we developed a magnetic resonance imaging (MRI) radiomic signature that can stratify survival and intracranial progression. METHODS: We analyzed 87 brain metastatic lesions in 24 ALK-positive NSCLC patients undergoing ALK-inhibitor ensartinib therapy and divided them into training (n=61) and validation (n=26) sets. Radiomic features were extracted and screened from contrast-enhanced MR images. Combined with these selected features, the Rad-score was calculated with multivariate logistic regression. The predictive model and Rad-score performance were assessed in the training set and validated in the validation set; decision curve analysis was performed with the combined training and validation sets to estimate Rad-score's patient-stratification ability. RESULTS: The prediction model constructed with nine selected radiomic features could predict intracranial progression within 51 weeks (AUC =0.84 and 0.85 in the training and validation sets, respectively), while clinical and regular MRI characteristics were independent of progression (P>0.05). The decision-curve analysis showed that the radiomic prediction model was clinically useful. The Kaplan-Meier analysis showed that the progression-free survival (PFS) difference between the high- and low-risk groups distinguished by the Rad-score was significant (P=0.017). CONCLUSIONS: Radiomics may provide prognostic information and improve pretreatment risk stratification in ALK-positive NSCLC patients with brain metastases undergoing ensartinib treatment, allowing follow-up and treatment to be tailored to the patient's individual risk profile.

Self-Assembly of Gold Nanoclusters into a Metal-Organic Framework with Efficient Electrochemiluminescence and Their Application for Sensitive Detection of Rutin.

Ligand-protected gold nanoclusters (Au NCs) are promising electrochemiluminescence (ECL) emitters because of their striking optical properties and excellent biocompatibility, but free vibration and rotation of their ligand result in low ECL efficiency, dramatically limiting their applications. Herein, using the ligand of Au NCs as one of the building units, a Au NC-based metal-organic framework (Au NC-based MOF) was constructed by the coordination-assisted self-assembly strategy, which not only impedes the ligand rotation-induced energy dissipation but also diminishes the self-quenching effect due to the spatial distribution of Au NCs. As a proof of concept, the prepared GSH-Au NCs@ZIF-8 gives rise to a 10-fold enhanced anodic ECL efficiency compared to that of densely aggregated GSH-Au NCs with triethylamine as the coreactant. Based on high ECL efficiency of GSH-Au NCs@ZIF-8, a "signal off" sensing platform was proposed with rutin as a model analyte, achieving a low detection limit of 10 nM. Therefore, the strategy paves an effective and alternative methodology to enhance ECL efficiency of metal NCs, considerably broadening their potential applications in sensing analysis, clinical diagnosis, and light-emitting devices.

Kill Three Birds with One Stone: Poly(3,4-ethylenedioxythiophene)-Hosted Ag Nanoclusters with Boosted Cathodic Electrochemiluminescence for Biosensing Application.

Metal nanoclusters (NCs) have attracted extensive interest in electrochemiluminescence (ECL) field, but it is still a significant challenge to prepare high ECL efficiency NCs, which tremendously precludes their application in sensing and imaging. Herein, we report poly(3,4-ethylenedioxythiophene) (PEDOT) as a functional ligand for NCs with a "kill three birds with one stone" role, acting as a stabilizer like existing templates, excitingly, excellent electrical conductivity to accelerate the injection of interfacial electrons, and outstanding electrocatalytic activity toward coreactants (S2O82-), which breaks the convention that traditional ligands act as a double-edged sword in ECL field. As an illustration, PEDOT-hosted Ag NCs were prepared with an unprecedented ECL intensity with S2O82- as a cathodic coreactant, which indicates that this novel ligand strategy will bring exciting opportunities, not only in opening up new horizons for rational development of high ECL efficiency metal NCs but also in advancing their potential applications in light-emitting devices and clinical biosensing. As a proof of concept, the PEDOT-hosted Ag NCs were applied as neoteric ECL emitters to achieve sensitive detection of dopamine (DA), which showcased a wide linear response from 1 nM to 10 mM and a low detection limit of 0.17 nM.

Different pathologic responses to neoadjuvant anti-PD-1 in primary squamous lung cancer and regional lymph nodes.

Neoadjuvant immunotherapy provides a unique opportunity for understanding therapeutic responses. We analyzed pathologic responses in surgical specimens obtained from 31 squamous non-small cell lung cancer (NSCLC) patients receiving neoadjuvant anti-PD-1 treatment. Fifteen (48.4%) patients achieved pathologic complete response (pCR) or major pathologic response (MPR). Among them, seven (46.7%) were assessed as radiological partial response and eight (53.3%) as stable disease. Among 20 patients with pathologically identified tumor beds in lymph nodes (LNs), 10 and six patients achieved pCR/MPR in primary tumors and paired LNs, respectively. pCR was achieved in 6/19 N1 nodes and 1/7 N2 nodes. Residual viable tumor (RVT) cells in 8/9 MPR specimens had 100% immune-activated phenotype, while a median of 80% of RVT cells in pathologic nonresponse specimens presented immune-excluded/desert phenotype. These findings demonstrated that assessment of pathologic responses in both primary tumor and LNs may be important as a surrogate for assessing neoadjuvant immunotherapeutic efficacy.

Neoadjuvant PD-1 inhibitor (Sintilimab) in NSCLC.

INTRODUCTION: Programmed death receptor-1 (PD-1) inhibitors have shown efficacy in first-line treatment of NSCLC; however, evidence of PD-1 inhibitor as neoadjuvant treatment is limited. This is a phase 1b study to evaluate the safety and outcome of PD-1 inhibitor in neoadjuvant setting. METHODS: Treatment-naive patients with resectable NSCLC (stage IA-IIIB) received two cycles of sintilimab (200 mg, intravenously, day 1 out of 22). Operation was performed between day 29 and 43. Positron emission tomography-computed tomography scans were obtained at baseline and before the operation. The primary end point was safety. Efficacy end points included rate of major pathologic response (MPR) and objective response rate. Expression of programmed cell death ligand 1 was also evaluated (registration number: ChiCTR-OIC-17013726). RESULTS: A total of 40 patients enrolled, all of whom received two doses of sintilimab and 37 underwent radical resection. A total of 21 patients (52.5%) experienced neoadjuvant treatment-related adverse events (TRAEs). Four patients (10.0%) experienced grade 3 or higher neoadjuvant TRAEs, and one patient had grade 5 TRAE. Eight patients achieved radiological partial response, resulting in an objective response rate of 20.0%. Among 37 patients, 15 (40.5%) achieved MPR, including six (16.2%) with a pathologic complete response in primary tumor and three (8.1%) in lymph nodes as well. Squamous cell NSCLC exhibited superior response compared with adenocarcinoma (MPR: 48.4% versus 0%). Decrease of maximum standardized uptake values after sintilimab treatment correlated with pathologic remission (p < 0.00001). Baseline programmed cell death ligand 1 expression of stromal cells instead of tumor cells was correlated with pathologic regression (p = 0.0471). CONCLUSIONS: Neoadjuvant sintilimab was tolerable for patients with NSCLC, and 40.5% MPR rate is encouraging. The decrease of maximum standardized uptake values after sintilimab might predict pathologic response.

The efficiency of 18F-FDG PET-CT for predicting the major pathologic response to the neoadjuvant PD-1 blockade in resectable non-small cell lung cancer.

PURPOSE: Investigate whether 18F-FDG PET-CT has the potential to predict the major pathologic response (MPR) to neoadjuvant sintilimab in resectable NSCLC patients, and the potential of sifting patients who probably benefit from immunotherapy. METHODS: Treatment-naive patients with resectable NSCLC (stage IA-IIIB) received two cycles of sintilimab (200 mg, intravenously, day 1 and 22). Surgery was performed between day 29 and 43. PET-CT was obtained at baseline and prior to surgery. The following lean body mass-corrected metabolic parameters were calculated by PET VCAR: SULmax, SULpeak, MTV, TLG, ΔSULmax%, ΔSULpeak%, ΔMTV%, ΔTLG%. PET responses were classified using PERCIST. The above metabolic information on FDG-PET was correlated with the surgical pathology. (Registration Number: ChiCTR-OIC-17013726). RESULTS: Thirty-six patients received 2 doses of sintilimab, all of whom underwent PET-CT twice and had radical resection (35) or biopsy (1). MPR occurred in 13 of 36 resected tumors (36.1%, 13/36). The degree of pathological regression was positively correlated with SULmax (p = 0.036) of scan-1, and was negatively correlated with all metabolic parameters of scan-2, and the percentage changes of the metabolic parameters after neoadjuvant therapy (p < 0.05). According to PERCIST, 13 patients (36.1%, 13/36) showed partial metabolic response (PMR), 21 (58.3%, 21/36) had stable metabolic disease, and 2 (5.6%, 2/36) had progressive metabolic disease (PMD). There was a significant correlation between the pathological response and the PET responses which were classified using PERCIST. All (100.0%) the PMR (ΔSULpeak% < - 30.0%) tumors showed MPR. CONCLUSIONS: 18F-FDG PET-CT can predict MPR to neoadjuvant sintilimab in resectable non-small cell lung cancer.

DCE-MRI Perfusion and Permeability Parameters as predictors of tumor response to CCRT in Patients with locally advanced NSCLC.

In this prospective study, 36 patients with stage III non-small cell lung cancers (NSCLC), who underwent dynamic contrast-enhanced MRI (DCE-MRI) before concurrent chemo-radiotherapy (CCRT) were enrolled. Pharmacokinetic analysis was carried out after non-rigid motion registration. The perfusion parameters [including Blood Flow (BF), Blood Volume (BV), Mean Transit Time (MTT)] and permeability parameters [including endothelial transfer constant (Ktrans), reflux rate (Kep), fractional extravascular extracellular space volume (Ve), fractional plasma volume (Vp)] were calculated, and their relationship with tumor regression was evaluated. The value of these parameters on predicting responders were calculated by receiver operating characteristic (ROC) curve. Multivariate logistic regression analysis was conducted to find the independent variables. Tumor regression rate is negatively correlated with Ve and its standard variation Ve_SD and positively correlated with Ktrans and Kep. Significant differences between responders and non-responders existed in Ktrans, Kep, Ve, Ve_SD, MTT, BV_SD and MTT_SD (P < 0.05). ROC indicated that Ve < 0.24 gave the largest area under curve of 0.865 to predict responders. Multivariate logistic regression analysis also showed Ve was a significant predictor. Baseline perfusion and permeability parameters calculated from DCE-MRI were seen to be a viable tool for predicting the early treatment response after CCRT of NSCLC.

Preliminary study of semi-quantitative and quantitative dynamic contrast-enhanced MRI in evaluating the response to concurrent chemoradiotherapy in patients with non-small cell lung cancer / 中华肿瘤杂志

<p><b>OBJECTIVE</b>To investigate the capability of semi-quantitative and quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict the response to concurrent chemoradiotherapy( CCRT) in patients with non-small cell lung cancer (NSCLC).</p><p><b>METHODS</b>A total of 24 patients with stage III or IIIB NSCLC, who underwent 3.0T DCE-MRI before CCRT, were enrolled in this study. Semi-quantitative and quantitative parameters were calculated by Funtool and Omnikinetics software. The relationship between these obtained parameters and tumor response was evaluated by Spearmen' s correlation analysis. The patients were classified into two groups according to the tumor regression rate after treatment, as response group (group A) and non-response group ( group B). Mann-Whitney U test was used to compare the parameters of responders and non-responders. The value of the parameters on predicting response was calculated by receiver operating characteristic curve (ROC).</p><p><b>RESULTS</b>The tumor regression rate after treatment was negatively correlated with time to peak (TTP) and the extravascular-extracellular volume fraction (Ve), and was positively correlated with signal enhancement ratio (SERmax) and volume transfer constant (Ktrans) (P < 0.05 for all). Statistical significant differences were found between group A and group B both in semi-quantitative and quantitative parameters (P < 0.05). Group A had a lower TTP value [(34.66 ± 16.37) s vs. (44.09 ± 17.41) s] and Ve value [(0.19 ± 0.03) vs. (0.25 ± 0.05)] than group B, whereas group A had a higher SERmax [(166.50 ± 44.95)% vs. (113.57 ± 46.62)%] and Ktrans [(0.41 ± 0.17) min(-1) vs. (0.28 ± 0.12) min(-1)] than group B (P < 0.05 for all). The ROC analysis indicated that when setting the threshold of Ve on ≤ 0.21 for predicting response, the specificity, sensitivity and accuracy were 85.7%, 80.0% and 83.3%, respectively, with an area under curve of 0.875 (P < 0.001).</p><p><b>CONCLUSIONS</b>Both the semi-quantitative and quantitative DCE-MRI parameters are helpful for predicting the response after CCRT of NSCLC. Quantitative parameters seem to be more meaningful than semi-quantitative parameters.</p>

[Comparative analysis of the correlation between HRCT image features and histopathologic characteristics of cyst-like lung adenocarcinoma].

OBJECTIVE: To evaluate the high resolution CT (HRCT) features of cyst-like lung adenocarcinoma, explore the correlation between HRCT image features and histopathological characteristics, and observe the pathological basis of air-containing space. METHODS: HRCT and histopathologic findings of cyst-like lung adenocarcinoma in 86 patients were investigated retrospectively. The image features of both tumor and air-containing space were analyzed. All surgically resected specimens were reviewed. The pathological analysis included histologic subtype, differentiation degree, and the pathological basis of air-containing space formation. The correlation between HRCT image features and histopathologic grades was analyzed. RESULTS: On HRCT, intratumoral necrosis was detected in 17 cases (19.8%), air-containing space with septa in 40 cases (46.5%), wall nodule in the air-containing space in 16 cases (18.6%), mixed thick and thin walls of air-containing space in 49 cases (57.0%). Air-containing space and its wall were observed in 63 cases on histological specimens, among which destruction of the alveolar wall by tumor cells might be the pathological basis of air-containing space in 42 (66.7%) cases. Differences of tumor attenuation (P = 0.030), intratumoral necrosis (P = 0.003) and proportion of thin-wall in air-containing space (P = 0.014) among different histopathologic grades were significant. The proportion of thin-wall in air-containing space was negatively correlated with histological grade (r = 0.267, P = 0.015). Differences of tumor contour (P = 0.002), tumor attenuation (P = 0.006), intratumoral necrosis (P < 0.001), septa in air-containing space (P = 0.016) and proportion of thin-wall in the air-containing space (P = 0.005) among different differentiation degrees were significant. The proportion of thin-wall in air-containing space was positively correlated with differentiation degree (r = 0.266, P = 0.013). CONCLUSIONS: On HRCT, cyst-like lung adenocarcinoma may manifest as an air-containing space with septa and mixed thin and thick walls, whereas wall nodule of air-containing space and intratumoral necrosis are not common. There is a certain correlation of HRCT manifestation with pathological subtype grading and tumor differentiation. Analysis of HRCT image features is helpful in prediction of the histopathologic grading and histological differentiation degree of the tumors. Destruction of the alveolar structure by tumor cells may be the main pathological basis of air-containing space formation in cyst-liked lung adenocarcinoma.