Spectral CT-based radiomics signature for distinguishing malignant pulmonary nodules from benign.

OBJECTIVES: To evaluate the discriminatory capability of spectral CT-based radiomics to distinguish benign from malignant solitary pulmonary solid nodules (SPSNs). MATERIALS AND METHODS: A retrospective study was performed including 242 patients with SPSNs who underwent contrast-enhanced dual-layer Spectral Detector CT (SDCT) examination within one month before surgery in our hospital, which were randomly divided into training and testing datasets with a ratio of 7:3. Regions of interest (ROIs) based on 40-65 keV images of arterial phase (AP), venous phases (VP), and 120kVp of SDCT were delineated, and radiomics features were extracted. Then the optimal radiomics-based score in identifying SPSNs was calculated and selected for building radiomics-based model. The conventional model was developed based on significant clinical characteristics and spectral quantitative parameters, subsequently, the integrated model combining radiomics-based model and conventional model was established. The performance of three models was evaluated with discrimination, calibration, and clinical application. RESULTS: The 65 keV radiomics-based scores of AP and VP had the optimal performance in distinguishing benign from malignant SPSNs (AUC65keV-AP = 0.92, AUC65keV-VP = 0.88). The diagnostic efficiency of radiomics-based model (AUC = 0.96) based on 65 keV images of AP and VP outperformed conventional model (AUC = 0.86) in the identification of SPSNs, and that of integrated model (AUC = 0.97) was slightly further improved. Evaluation of three models showed the potential for generalizability. CONCLUSIONS: Among the 40-65 keV radiomics-based scores based on SDCT, 65 keV radiomics-based score had the optimal performance in distinguishing benign from malignant SPSNs. The integrated model combining radiomics-based model based on 65 keV images of AP and VP with Zeff-AP was significantly superior to conventional model in the discrimination of SPSNs.

Understanding barriers and enablers to participation in a proposed online lifestyle intervention for older adults with age-related macular degeneration to guide programme implementation.

Age-related macular degeneration (AMD) is a blinding condition associated with depression, loneliness and unhealthy lifestyle behaviours which drives AMD progression. We have proposed the first online lifestyle intervention for AMD, called Movement, Interaction and Nutrition for Greater Lifestyles in the Elderly (MINGLE) to promote positive lifestyle changes and reduce loneliness. This qualitative grounded-theory study explored enablers and barriers to future participation in MINGLE for older adults with AMD. Thirty-one participants were interviewed and thematic analysis revealed nine themes. Enablers to participation were: socialising and learning about AMD, motivation to improve health, programme accessibility and structure. Barriers were: lack of time, technology, limited knowledge regarding holistic interventions, vision-related issues, mobility and negative perception of group interactions. These factors must be considered when developing lifestyle interventions for AMD patients to maximise participation. Supporting technology use and raising awareness about benefits of healthy lifestyle behaviours for AMD may help overcome these barriers.

Added value of spectral parameters for the assessment of lymph node metastasis of lung cancer with dual-layer spectral detector computed tomography.

BACKGROUND: Lymph node (LN) metastasis is an important factor affecting the treatment of lung cancer. The purpose of this article was to investigate the benefits of dual-layer spectral detector computed tomography (SDCT) for the evaluation of metastatic LNs in lung cancer. METHODS: Data from 93 patients with lung cancer who underwent dual-phase enhanced scanning with SDCT were retrospectively analyzed. According to the pathological findings, 166 LNs were grouped as metastatic (n=80) or non-metastatic (n=86). LNs in station 4 (n=80) and station 7 (n=35) accounted for the majority of the LNs (approximately 69.23%). The short-axis diameter of the LN, arterial enhancement fraction (AEF), normalized iodine concentration (NIC), and the slope of the spectral Hounsfield unit curve (λHU) during the arterial phase (AP) and venous phase (VP) were measured. The Mann-Whitney U test was used to statistically compare these quantitative parameters. Receiver operating characteristic (ROC) curves were plotted to identify the cutoff values, and decision curve analysis (DCA) was performed to determine the net benefit of each parameter. The diagnostic performance, obtained by combining the short-axis diameter with each of the above parameters, was also studied. RESULTS: The short-axis LN diameter, AEF, NIC, and λHU during the AP and VP all showed significant differences between the metastatic and non-metastatic groups (P<0.05). Of the parameters, the AEF had the greatest diagnostic efficiency for metastatic LNs [area under the ROC curve (AUC)AEF =0.885] with a threshold of 86.40%. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and 95% confidence interval were 90.00%, 89.53%, 88.89%, 90.59%, and 0.830-0.944, respectively. When the quantitative parameters were combined with the short-axis diameter, the AUCs of the parameters, except the AEF, were significantly improved (P<0.05). CONCLUSIONS: The iodine quantitative parameters from SDCT, such as the AEF, demonstrated high diagnostic performances in the differentiation of metastatic and non-metastatic LNs.

The application of dual-layer spectral detector computed tomography in solitary pulmonary nodule identification.

BACKGROUND: Differentiating between malignant solitary pulmonary nodules (SPNs) and other lung diseases remains a substantial challenge. The latest generation of dual-energy computed tomography (CT), which realizes dual-energy technology at the detector level, has clinical potential for distinguishing lung cancer from other benign SPNs. This study aimed to evaluate the performance of dual-layer spectral detector CT (SDCT) for the differentiation of SPNs. METHODS: Spectral images of 135 SPNs confirmed by pathology were retrospectively analyzed in both the arterial phase (AP) and the venous phase (VP). Patients were classified into two groups [the malignant group (n=93) and the benign group (n=42)], with the malignant group further divided into small cell lung cancer (SCLC, n=30) and non-small cell lung cancer (NSCLC, n=63) subtypes. The slope of the spectral Hounsfield Unit (HU) curve (λHU), normalized iodine concentration (NIC), CT values of 40 keV monochromatic images (CT40keV), and normalized arterial enhancement fraction (NAEF) in contrast-enhanced images were calculated and compared between the benign and malignant groups, as well as between the SCLC and NSCLC subgroups. ROC curve analysis was performed to assess the diagnostic performance of the above parameters. Seventy cases were randomly selected and independently measured by two radiologists, and intraclass correlation coefficient (ICC) and Bland-Altman analyses were performed to calculate the reliability of the measurements. RESULTS: Except for NAEF (P=0.23), the values of the parameters were higher in the malignant group than in the benign group (all P<0.05). NIC, λHU, and CT40keV performed better in the VP (NICVP, λVPHU, and CTVP40keV) (P<0.001), with an area under the ROC curve (AUC) of 0.93, 0.89, and 0.89 respectively. With respective cutoffs of 0.31, 1.83, and 141.00 HU, the accuracy of NICVP, λVPHU, and CTVP40keV was 91.11%, 85.19%, and 88.15%, respectively. In the subgroup differentiating NSCLC and SCLC, the diagnostic performances of NICAP (AUC =0.89) were greater than other parameters. NICAP had an accuracy of 86.02% when the cutoff was 0.14. ICC and Bland-Altman analyses indicated that the measurement of SDCT has great reproducibility. CONCLUSIONS: Quantitative measures from SDCT can help to differentiate benign from malignant SPNs and may help with the further subclassification of malignant cancer into SCLC and NSCLC.

Elastin Biomaterials in Dermal Repair.

Wound healing has historically relied on endogenous processes, but engineered materials are increasingly being used to assist tissue repair. Elastin is an essential functional component of the dermal extracellular matrix and is an important part of skin wound repair that encompasses an elastic dermis. Advances in modern technology have better elucidated the specific signaling factors and cells that contribute to the physiological process and have led to new developments in wound care technology. We review elastin-based materials that are used to encourage wound repair. Elastin-related biomaterials, particularly those based on tropoelastin, are particularly promising because tropoelastin is assembled to make elastin. We present insights into the roles of elastin-related biomaterials and their associated in vitro and in vivo benefits on wound healing.

Theta-gamma coupling in the prelimbic area is associated with heroin addiction.

The medial prefrontal cortex (mPFC) is implicated in the regulation of drug-seeking behavior, but the specific contributions of the mPFC prelimbic (PL) subdivision and the precise mechanisms underlying heroin abuse remain largely unclear. In the present study, we examined changes in the rhythmic ensemble activity of PL neurons after induction of heroin addiction in rats. Rats were injected daily with saline (control group) or heroin (addiction group) in the light chamber of a light-dark shuttle box, and a video tracking system was used to measure conditioned place preference (CPP) as a sign of addiction. A wireless telemetry system was used to record local field potentials (LFPs) from the PL area during expression of CPP. Before treatment, there was no difference in CPP between groups (P > 0.05). However, rats in the experimental group exhibited significant CPP (P < 0.05) in the light chamber after heroin treatment compared to before treatment and compared to control rats. During CPP, addicted rats demonstrated substantial alterations in relative θ and γ frequency band power (Ps < 0.05); moreover, the θ wave alteration was strongly coupled to γ waves in heat map analyses (P < 0.05). Collectively, these findings implicate heroin-induced alterations in PL area neural activity and θ-γ coupling in heroin addiction.