The Value of Magnetic Resonance Imaging in Assessing Immediate Efficacy After Microwave Ablation of Lung Malignancies.

PURPOSE: To investigate the imaging performance and parametric analysis of magnetic resonance imaging (MRI) immediately after microwave ablation (MWA) of lung malignancies. MATERIALS AND METHODS: We retrospectively analyzed the MRI performance immediately after MWA of 34 cases of lung malignancies. The ablation zone parameters of lung malignancies were measured, including the long diameter (L), short diameter (S), and safety margin of the ablation zone on plain computed tomography (CT), T1-weighted imaging (T1WI), and T2-weighted imaging (T2WI) after MWA. The study calculated the tumor volume (V0), the ablation zone volume (V1), and the ratio of V0 to V1 (V%). Statistical differences between the parameters were analyzed. RESULTS: The ablation area of the lesion exhibited central low signal and peripheral high signal on T2WI, central high signal and peripheral equal or high signal on T1WI, and circumferential enhancement in the periphery. The safety margin measured on T2WI was greater than that measured on plain CT and T1WI. On plain CT, the L, S, and V1 were smaller in the effective treatment group than in the ineffective treatment group (P<0.05). On T1WI, the V% and safety margin were greater in the effective treatment group than in the ineffective treatment group (P=0.009 and P=0.016, respectively). CONCLUSIONS: MRI may be a new, valuable method to assess immediate efficacy after MWA for lung malignancies using the ablation zone parameters V% on T1WI and safety margin on T2WI.

The value of intratumoral and peritumoral radiomics features in differentiating early-stage lung invasive adenocarcinoma (≤3 cm) subtypes.

Background: The identification of different subtypes of early-stage lung invasive adenocarcinoma before surgery contributes to the precision treatment. Radiomics could be one of the effective and noninvasive identification methods. The value of peritumoral radiomics in predicting the subtypes of early-stage lung invasive adenocarcinoma perhaps clinically useful. Methods: This retrospective study included 937 lung adenocarcinomas which were randomly divided into the training set (n=655) and testing set (n=282) with a ratio of 7:3. This study used the univariate and multivariate analysis to choose independent clinical predictors. Radiomics features were extracted from 18 regions of interest (1 intratumoral region and 17 peritumoral regions). Independent and conjoint prediction models were constructed based on radiomics and clinical features. The performance of the models was evaluated using receiver operating characteristic (ROC) curves, accuracy (ACC), sensitivity (SEN), and specificity (SPE). Significant differences between areas under the ROC (AUCs) were estimated using in the Delong test. Results: Patient age, smoking history, carcinoembryonic antigen (CEA), lesion location, length, width and clinic behavior were the independent predictors of differentiating early-stage lung invasive adenocarcinoma (≤3 cm) subtypes. The highest AUC value among the 19 independent models was obtained for the PTV0~+3 radiomics model with 0.849 for the training set and 0.854 for the testing set. As the peritumoral distance increased, the predictive power of the models decreased. The radiomics-clinical conjoint model was statistically significantly different from the other models in the Delong test (P<0.05). Conclusions: The intratumoral and peritumoral regions contained a wealth of clinical information. The diagnostic efficacy of intra-peritumoral radiomics combined clinical model was further improved, which was particularly important for preoperative staging and treatment decision-making.

Radiogenomics for predicting microsatellite instability status and PD-L1 expression with machine learning in endometrial cancers: A multicenter study.

Purpose: To evaluate the effectiveness of machine learning model based on magnetic resonance imaging (MRI) in identifying microsatellite instability (MSI) status and PD-L1 expression in endometrial cancer (EC). Methods: This retrospective study included 82 EC patients from 2 independent centers. Radiomics features from the intratumoral and peritumoral regions, obtained from four conventional MRI sequences (T2-weighted images; contrast-enhanced T1-weighted images; diffusion-weighted images; apparent diffusion coefficient), were combined with clinicopathologic characteristics to develop machine learning model for predicting MSI status and PD-L1 expression. 60 patients from center 1 were used as the training set for model construction, while 22 patients from center 2 were used as an external validation set for model evaluation. Results: For predicting MSI status, the clinicopathologic model, radscore model, and combination model achieved area under the curves (AUCs) of 0.728, 0.833, and 0.889 in the training set, respectively, and 0.595, 0.790, and 0.848 in the validation set, respectively. For predicting PD-L1 expression, the clinicopathologic model, radscore model, and combination model achieved AUCs of 0.648, 0.814, and 0.834 in the training set, respectively, and 0.660, 0.708, and 0.764 in the validation set, respectively. Calibration curve analysis and decision curve analysis demonstrated good calibration and clinical utility of the combination model. Conclusion: The machine learning model incorporating MRI-based radiomics features and clinicopathologic characteristics could be a potential tool for predicting MSI status and PD-L1 expression in EC. This approach may contribute to precision medicine for EC patients.

Sleep characteristics before assisted reproductive technology treatment predict reproductive outcomes: a prospective cohort study of Chinese infertile women.

Sleep disorders affect mental and physical health. Infertile women undergoing assisted reproductive technology (ART) treatment are prone to sleep disorders. Sleep condition, its influencing factors, and the association between sleep condition and ART treatment outcomes before treatment have not been explored within a population with a large sample size. Therefore, we investigated the sleep characteristics of 1002 Chinese infertile women before ovulation induction and investigated the influencing factors (negative and positive psychological factors, demographics, and fertility characteristics). We also examined whether sleep conditions before treatment predicted reproductive outcomes. We found that 24.1% of participants reported poor sleep quality. Women with primary infertility reported poorer sleep than women with secondary infertility. Negative psychological factors, including depression, anxiety, and perceived stress were associated with poor sleep, whereas positive affect was linked with good sleep. Adverse sleep characteristics, including poor subjective sleep quality, sleep disturbances, and poor sleep efficiency, decreased the quantity and quality of oocytes retrieved, fertilization rates, and clinical pregnancy rates. This study indicates that before ART treatment, a large number of females with infertility suffer from sleep problems, which are affected by psychological factors and infertility type, and unhealthy sleep characteristics may impair treatment outcomes. Our findings highlight the importance of screening and treatment for sleep disorders before the enrollment of ART treatment in infertile women.

An organ-effective modulation for non-contrast chest computed tomography imaging: effect on image quality and thyroid exposure reduction.

We investigate the efficacy of organ-effective modulation (OEM) technique for thyroid dose reduction among various body habitus and its impact on image quality in chest non-contrast computed tomography (CT). We prospectively enrolled 64 patients who underwent non-contrast chest CT from January to May 2022. The skin-absorbed radiation dose over the thyroid (Dthyroid) was obtained using a thermoluminescence dosemeter. Signal-to-noise ratio and image noise was also quantitatively assessed. In subjective analyses, two radiologists independently evaluated images based on a 5-point scale. The OEM group showed a markedly decrease in Dthyroid when compared with the non-OEM group (p < 0.05). No significant difference was observed regarding the image noise (p < 0.05), except for the ventral air space. The subjective scores of two radiologists showed no significant differences between the non-OEM and OEM groups. OEM can effectively reduce the radiation exposure of thyroid without compromising on image quality in non-contrast chest CT.

Theta-Burst Stimulation Combined With Virtual-Reality Reconsolidation Intervention for Methamphetamine Use Disorder: Study Protocol for a Randomized-Controlled Trial.

Background: Craving associated with drug-related memory is one of the key factors that induce the relapse of methamphetamine (MA). Disruption or modulation of the reconsolidation of drug-related memory may serve as an option for clinical treatment of MA addiction. This protocol proposes to use virtual reality (VR) to retrieve drug-associated memory and then use transcranial magnetic stimulation (TMS) at the neural circuit that encodes the reward value of drug cues to provide a non-invasive intervention during reconsolidation. We aim to evaluate the effectiveness of TMS treatment after VR retrieval on the reduction of cue reactivity and craving of MA. Methods: This is a randomized, double-blind, sham-controlled, parallel group trial, targeting participants with MA use disorder aged from 18 to 45 years old. Forty-five eligible volunteers in Shanxi Drug Rehabilitation Center will be recruited and be randomly allocated into three parallel groups, receiving either 1) MA-related cues retrieval in VR combined with active TMS (MA VR scene + TBS) or 2) sham TMS (MA VR scene + sham TBS), or 3) neutral cues retrieval in VR combined with active TMS (neutral VR scene + TBS). Two sessions of post-VR-retrieval TBS will be scheduled on two separate days within 1 week. The primary outcome will detect the memory-related activity by the electroencephalography (EEG) reactivity to drug cues in VR scenes. Secondary outcomes are the self-reported MA craving in VR scene, the physiological parameter (cue-induced heart rate) and the scores of psychological questionnaires including anxiety, depression, and mood. All primary and secondary outcomes will be assessed at baseline, 1-week, and 1-month post-intervention. Assessments will be compared between the groups of 1) MA VR scene + TBS, 2) MA VR scene + sham TBS and 3) neutral VR scene + TBS. Discussion: This will be the first study to examine whether the TMS modulation after VR retrieval can reduce self-reported craving and drug-related cue reactivity. It will promote the understanding of the neural circuit mechanism of the reconsolidation-based intervention and provide an effective treatment for MA use disorder patients. Clinical Trial Registration: [Chinese Clinical Trial Registry], identifier [ChiCTR1900026902]. Registered on 26 October 2019.

The Effects of Immediate vs Gradual Reduction in Nicotine Content of Cigarettes on Smoking Behavior: An Ecological Momentary Assessment Study.

Background: In recent years, much research has examined the effects of various interventions and treatments for smoking cessation. The results suggest that interventions targeting changes of nicotine content can help smokers reduce tobacco use or quit smoking. A number of clinical studies show that smokers who received an immediate reduction in nicotine content to very low levels have significantly greater reductions in the number of cigarettes smoked and toxic substance exposure compared to those with gradual reductions. However, from the perspective of smoking craving, whether the immediate and gradual reduction in nicotine content reduce smoking by reducing cravings needs further investigation. Methods: 74 eligible Participants were randomly allocated to one of the two experimental conditions: (1) immediate reduction to 0.1 mg of nicotine per cigarette (n = 40); (2) gradual reduction from 1.0 (0.8 g ~ 1.2 mg) to 0.1 mg of nicotine per cigarette (n = 34). All participants completed 1-week baseline period during which they smoked their usual cigarette, followed by 16-week of interventions. The primary outcomes included cigarette cravings and number of cigarettes smoked per day (CPD); secondary outcomes included the number of cigarette-free day and emotional states. Results: Among the 52 participants [51 (98.1%) men; mean (SD) age, 33.44 (6.71) years; mean (SD) CPD, 16.83 (9.94)] who completed the trial, significantly lower cravings for cigarettes were observed in the immediate (n = 25) vs. gradual nicotine reduction group (n = 27) in the morning (t = -2.072, p = 0.039) and after dinner (t = -2.056, p = 0.041). Compared with the baseline daily smoking, the number of cigarettes smoked per day was significantly reduced at the beginning of week 12 in the immediate nicotine reduction group (p = 0.001) and at week 16 in the gradual nicotine reduction group (p < 0.001). The number of participants with any cigarette-free day was not significantly different between the groups (p = 0.198). The number of cigarette-free days was significantly more in the immediate vs. gradual nicotine reduction group (p = 0.027). Conclusions: The significantly lower cravings were observed in the immediate vs. gradual nicotine reduction group, and led to faster reduction in the number of CPD, and a significant increase in the number of cigarette-free days. These findings add to the evidence base for reduced nicotine content in cigarettes. Clinical Trial Registration: ClinicalTrials.gov, identifier: ChiCTR2100048216.