The Relationship Between Pain Intensity and Pain-Related Activity Patterns in Older Adults with Chronic Musculoskeletal Pain: Mediating Roles of Pain Resilience and Pain Catastrophizing.

Purpose: To explore the relationship between pain intensity, pain resilience, pain catastrophizing, and pain-related activity patterns in older adults with chronic musculoskeletal pain (CMP). Patients and Methods: A total of 220 elderly Chinese with chronic musculoskeletal pain were recruited from a tertiary general hospital. Participants completed several measures including a demographic questionnaire, Brief Pain Inventory (BPI), Pain Resilience Scale (PRS), Pain Catastrophizing Scale (PCS), and Patterns of Activity Measure-Pain (POAM-P). Moreover, Process version 3.5 plug-in SPSS26 was used to test the mediation effect between variables. Results: The scores of POAM-P in older adults with CMP from high to low were: avoidance (27.39 ± 8.10), pacing (24.25 ± 9.48), and overdoing (16.65 ± 10.95). Mediation analysis revealed that pain resilience and pain catastrophizing mediated the relationship between pain intensity and pain-related activity patterns (avoidance and pacing) in older adults with CMP. Conclusion: These results provide evidence for the role of pain resilience and pain catastrophizing in the relationship between pain intensity and pain-related activity patterns. Interventions targeting these factors should be included in activity management programs for elderly CMP patients. It may be possible to reduce the negative impact of pain intensity on activity patterns by improving pain resilience and reducing pain catastrophizing.

Quantitative parameters of enhanced dual-energy computed tomography for differentiating lung cancers from benign lesions in solid pulmonary nodules.

Objectives: This study aimed to investigate the ability of quantitative parameters of dual-energy computed tomography (DECT) and nodule size for differentiation between lung cancers and benign lesions in solid pulmonary nodules. Materials and Methods: A total of 151 pathologically confirmed solid pulmonary nodules including 78 lung cancers and 73 benign lesions from 147 patients were consecutively and retrospectively enrolled who underwent dual-phase contrast-enhanced DECT. The following features were analyzed: diameter, volume, Lung CT Screening Reporting and Data System (Lung-RADS) categorization, and DECT-derived quantitative parameters including effective atomic number (Zeff), iodine concentration (IC), and normalized iodine concentration (NIC) in arterial and venous phases. Multivariable logistic regression analysis was used to build a combined model. The diagnostic performance was assessed by area under curve (AUC) of receiver operating characteristic curve, sensitivity, and specificity. Results: The independent factors for differentiating lung cancers from benign solid pulmonary nodules included diameter, Lung-RADS categorization of diameter, volume, Zeff in arterial phase (Zeff_A), IC in arterial phase (IC_A), NIC in arterial phase (NIC_A), Zeff in venous phase (Zeff_V), IC in venous phase (IC_V), and NIC in venous phase (NIC_V) (all P < 0.05). The IC_V, NIC_V, and combined model consisting of diameter and NIC_V showed good diagnostic performance with AUCs of 0.891, 0.888, and 0.893, which were superior to the diameter, Lung-RADS categorization of diameter, volume, Zeff_A, and Zeff_V (all P < 0.001). The sensitivities of IC_V, NIC_V, and combined model were higher than those of IC_A and NIC_A (all P < 0.001). The combined model did not increase the AUCs compared with IC_V (P = 0.869) or NIC_V (P = 0.633). Conclusion: The DECT-derived IC_V and NIC_V may be useful in differentiating lung cancers from benign lesions in solid pulmonary nodules.

Improvement of image quality of laryngeal squamous cell carcinoma using noise-optimized virtual monoenergetic image and nonlinear blending image algorithms in dual-energy computed tomography.

BACKGROUND: Dual-energy computed tomography (DECT) has been used to improve image quality of head and neck squamous cell carcinoma (SCC). This study aimed to assess image quality of laryngeal SCC using linear blending image (LBI), nonlinear blending image (NBI), and noise-optimized virtual monoenergetic image (VMI+) algorithms. METHODS: Thirty-four patients with laryngeal SCC were retrospectively enrolled between June 2019 and December 2020. DECT images were reconstructed using LBI (80 kV and M_0.6), NBI, and VMI+ (40 and 55 keV) algorithms. Contrast-to-noise ratio (CNR), tumor delineation, and overall image quality were assessed and compared. RESULTS: VMI+ (40 keV) had the highest CNR and provided better tumor delineation than VMI+ (55 keV), LBI, and NBI, while NBI provided better overall image quality than VMI+ and LBI (all corrected p < 0.05). CONCLUSIONS: VMI+ (40 keV) and NBI improve image quality of laryngeal SCC and may be preferable in DECT examination.

Accuracy of Pulmonary Nodule Volumetry Using Noise-Optimized Virtual Monoenergetic Image and Nonlinear Blending Image Algorithms in Dual-Energy Computed Tomography: A Phantom Study.

OBJECTIVE: The aim of the study was to assess accuracy of pulmonary nodule volumetry using noise-optimized virtual monoenergetic image (VMI+) and nonlinear blending image (NBI) algorithms in dual-energy computed tomography (DECT). METHODS: An anthropomorphic chest phantom with 10 simulated nodules (5 solid nodules and 5 ground-glass opacities) was scanned using DECT80/Sn140kV, DECT100/Sn140kV, and single-energy CT (SECT120kV/200mAs), respectively. The dual-energy images were reconstructed using VMI+ (70 keV) and NBI algorithms. The contrast-to-noise ratio and absolute percentage error (APE) of nodule volume were measured to assess image quality and accuracy of nodule volumetry. The radiation dose was also estimated. RESULTS: The contrast-to-noise ratio of SECT120kV/200mAs was significantly higher than that of NBI80/Sn140kV and VMI+80/Sn140kV (both corrected P < 0.05), whereas there were no significant differences between NBI100/sn140kV and SECT120kV/200mAs and between VMI+100/sn140kV and SECT120kV/200mAs (both corrected P > 0.05). The APE of SECT120kV/200mAs was significantly lower than that of NBI80/Sn140kV and VMI+80/Sn140kV in both types of nodules (all corrected P < 0.05), whereas there were no significant differences between VMI+100/sn140kV and SECT120kV/200mAs in solid nodules and between NBI100/Sn140kV and SECT120kV/200mAs in ground-glass opacities (both corrected P > 0.05). The radiation dose of DECT100/Sn140kV and DECT80/Sn140kV were significantly lower than that of SECT120kV/200mAs (both corrected P < 0.05). CONCLUSIONS: The DECT100/sn140kV can ensure image quality and nodule volumetry accuracy with lower radiation dose compared with SECT120kV/200mAs. Specifically, the VMI+ algorithm could be used in solid nodules and NBI algorithm in ground-glass opacities.

Screening baseline characteristics of early lung cancer on low-dose computed tomography with computer-aided detection in a Chinese population.

OBJECTIVES: This study investigated appropriate baseline characteristics for screening a Chinese population at high risk of early lung cancer, assisted by low-dose computed tomography (LDCT) with computer-aided detection (CAD). Included is a discussion of the viability of using LDCT in the screening guideline and optimizing the guideline. METHODS: In 2014, 1016 individuals from Sichuan Province were enrolled who satisfied the criteria for high risk according to the 2013 National Comprehensive Cancer Network (NCCN) Guidelines for Non-Small Cell Lung Cancer. From 2014 to 2018, each subject was followed using LDCT with CAD, and pathologically confirmed lung cancers and baseline nodule characteristics (size and density) were recorded. Positive risk was considered a non-calcified solid or part-solid nodule on LDCT with diameter ≥5 mm and ground-glass nodule ≥8 mm, as newly recommended by the China National Lung Cancer Screening Guideline. RESULTS: From 2014-2018, 13 cases of lung cancer were detected; 5 of these were early stage (38.5%). According to the NCCN criteria, 54 women were included and one of these (1.8%) developed lung cancer. The prevalence of lung cancer was 0.7% at baseline. For the entire population (excluding subjects with a tumor mass at baseline, n = 4), the rate of positivity was 20.4% at baseline; applying the Chinese criteria, the false positive rate was 19.5% (197/1012). CONCLUSIONS: Further studies are warranted to establish appropriate eligible criteria and management strategies for Chinese populations.