A multi-institutional study to predict the benefits of DEB-TACE and molecular targeted agent sequential therapy in unresectable hepatocellular carcinoma using a radiological-clinical nomogram.

OBJECTIVE: Exploring the efficacy of a Radiological-Clinical (Rad-Clinical) model in predicting prognosis of unresectable hepatocellular carcinoma (HCC) patients after drug eluting beads transcatheter arterial chemoembolization (DEB-TACE) to optimize the targeted sequential treatment. METHODS: In this retrospective analysis, we included 202 patients with unresectable HCC who received DEB-TACE treatment in 17 institutions from June 2018 to December 2022. Progression-free survival (PFS)-related radiomics features were computationally extracted from HCC patients to build a radiological signature (Rad-signature) model with least absolute shrinkage and selection operator regression. A Rad-Clinical model for postoperative PFS was further constructed according to the Rad-signature and clinical variables by Cox regression analysis. It was presented as a nomogram and evaluated by receiver operating characteristic curves, calibration curves, and decision curve analysis. And further evaluate the application value of Rad-Clinical model in clinical stages and targeted sequential therapy of HCC. RESULTS: Tumor size, Barcelona Clinic Liver Cancer (BCLC) stage, and radiomics score (Rad-score) were found to be independent risk factors for PFS after DEB-TACE treatment for unresectable HCC, with the Rad-Clinical model being the greatest predictor of PFS in these patients (hazard ratio: 2.08; 95% confidence interval: 1.56-2.78; P < 0.001) along with high 6 months, 12 months, 18 months, and 24 months area under the curves of 0.857, 0.810, 0.843, and 0.838, respectively. In addition, compared to the radiomics and clinical nomograms, the Radiological-Clinical nomogram also significantly improved the classification accuracy for PFS outcomes, based on the net reclassification improvement (45.2%, 95% CI 0.260-0.632, p < 0.05) and integrated discrimination improvement (14.9%, 95% CI 0.064-0.281, p < 0.05). Based on this model, low-risk patients had higher PFS than high-risk patients in BCLC-B and C stages (P = 0.021). Targeted sequential therapy for patients with high and low-risk HCC in BCLC-B stage exhibited significant benefits (P = 0.018, P = 0.012), but patients with high-risk HCC in BCLC-C stage did not benefit much (P = 0.052). CONCLUSION: The Rad-Clinical model may be favorable for predicting PFS in patients with unresectable HCC treated with DEB-TACE and for identifying patients who may benefit from targeted sequential therapy.

Rotundic acid improves nonalcoholic steatohepatitis in mice by regulating glycolysis and the TLR4/AP1 signaling pathway.

BACKGROUND: Steatosis and inflammation are the hallmarks of nonalcoholic steatohepatitis (NASH). Rotundic acid (RA) is among the key triterpenes of Ilicis Rotundae Cortex and has exhibited multipronged effects in terms of lowering the lipid content and alleviating inflammation. The study objective is to systematically evaluate the potential mechanisms through which RA affects the development and progression of NASH. METHODS: Transcriptomic and proteomic analyses of primary hepatocytes isolated from the control, high-fat diet-induced NASH, and RA treatment groups were performed through Gene Ontology analysis and pathway enrichment. Hub genes were identified through network analysis. Integrative analysis revealed key RA-regulated pathways, which were verified by gene and protein expression studies and cell assays. RESULTS: Hub genes were identified and enriched in the Toll-like receptor 4 (TLR4)/activator protein-1 (AP1) signaling pathway and glycolysis pathway. RA reversed glycolysis and attenuated the TLR4/AP1 pathway, thereby reducing lipid accumulation and inflammation. Additionally, lactate release in L-02 cells increased with NaAsO2-treated and significantly decreased with RA treatment, thus revealing that RA had a major impact on glycolysis. CONCLUSIONS: RA is effective in lowering the lipid content and reducing inflammation in mice with NASH by ameliorating glycolysis and TLR4/AP1 pathways, which contributes to the existing knowledge and potentially sheds light on the development of therapeutic interventions for patients with NASH.

Comparative study of instrumental measurement and sensory evaluation methods for the repairing effect of mildly damaged hair bundles.

OBJECTIVE: This study explores the applicability and scientific accuracy of instrument measurements in repairing hair products on slightly damaged hair bundles. MATERIALS AND METHOD: Sixty hair bundles mildly damaged with hydrogen peroxide and ammonia standards were divided into two groups: the treatment and control groups (30 hair bundles each). The treatment group used commercial hair care essential oil, whereas the control group used tap water to treat the damage. The two groups were measured using an instrument before and after the product application. The objective indicators included the gloss of hair, along with hair cuticle dynamic friction coefficient, and against hair cuticle dynamic friction coefficient. At the same time, two evaluators conducted sensory evaluations on the gloss and frizz levels of the hair bundles. Therefore, data comparison and verification were carried out together with instrumental measurement data. RESULTS: We verified that the instrumental measurement methods could obtain data trends that are consistent with sensory assessment methods; hence, they have the advantages of accuracy, convenience, and quantifiability. CONCLUSION: Thus, the instrumental measurement methods we verified can provide objective evidence for the efficacy of hair care products in repairing hair.

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.

A CT-based radiomics nomogram for predicting the progression-free survival in small cell lung cancer: a multicenter cohort study.

PURPOSE: To develop a radiomics nomogram based on computed tomography (CT) to estimate progression-free survival (PFS) in patients with small cell lung cancer (SCLC) and assess its incremental value to the clinical risk factors for individual PFS estimation. METHODS: 558 patients with pathologically confirmed SCLC were retrospectively recruited from three medical centers. A radiomics signature was generated by using the Pearson correlation analysis, univariate Cox analysis, and multivariate Cox analysis. Association of the radiomics signature with PFS was evaluated. A radiomics nomogram was developed based on the radiomics signature, then its calibration, discrimination, reclassification, and clinical usefulness were evaluated. RESULTS: In total, 6 CT radiomics features were finally selected. The radiomics signature was significantly associated with PFS (hazard ratio [HR] 4.531, 95% confidence interval [CI] 3.524-5.825, p < 0.001). Incorporating the radiomics signature into the radiomics nomogram resulted in better performance for the estimation of PFS (concordance index [C-index] 0.799) than with the clinical nomogram (C-index 0.629), as well as high 6 months and 12 months area under the curves of 0.885 and 0.846, respectively. Furthermore, the radiomics nomogram also significantly improved the classification accuracy for PFS outcomes, based on the net reclassification improvement (33.7%, 95% CI 0.216-0.609, p < 0.05) and integrated discrimination improvement (22.7%, 95% CI 0.168-0.278, p < 0.05). Decision curve analysis demonstrated that in terms of clinical usefulness, the radiomics nomogram outperformed the clinical nomogram. CONCLUSION: A CT-based radiomics nomogram exhibited a promising performance for predicting PFS in patients with SCLC, which could provide valuable information for individualized treatment.

Effects of oleanolic acid on hair growth in mouse dorsal skin mediated via regulation of inflammatory cytokines.

Oleanolic acid (OA) is a pentacyclic triterpenoid with favourable physiological activity. It is widely distributed in more than 200 species of plants. OA has garnered significant interest because of its potential biological activities, such as antioxidant, bacteriostatic, and hair growth-promoting effects. To study the effect of OA on hair growth and related mechanisms, we investigated hair growth in mice with testosterone-induced androgenetic alopecia (AGA) that were treated with three different concentrations of OA. The antioxidant, bacteriostatic, and cytotoxic effects of OA were evaluated. We found that mice with testosterone-induced AGA treated with 1% or 0.5% OA showed significantly enhanced hair growth and increased vascular endothelial growth factor/glyceraldehyde-3-phosphate dehydrogenase ratio and levels of fibroblast growth factor receptor and insulin-like growth factor 1. Using an immunofluorescence staining assay, we demonstrated that ß-catenin, a key Wnt signalling transducer, was highly expressed in the OA-treated groups. These results suggest that OA may promote hair growth by stimulating hair matrix cell proliferation via the Wnt/ß-catenin pathway and lowering the levels of tumour necrosis factor-alpha, and transforming growth factor-beta 1, dihydrotestosterone, and 5α-reductase.

Full-length annotation with multistrategy RNA-seq uncovers transcriptional regulation of lncRNAs in cotton.

Long noncoding RNAs (lncRNAs) are crucial factors during plant development and environmental responses. To build an accurate atlas of lncRNAs in the diploid cotton Gossypium arboreum, we combined Isoform-sequencing, strand-specific RNA-seq (ssRNA-seq), and cap analysis gene expression (CAGE-seq) with PolyA-seq and compiled a pipeline named plant full-length lncRNA to integrate multi-strategy RNA-seq data. In total, 9,240 lncRNAs from 21 tissue samples were identified. 4,405 and 4,805 lncRNA transcripts were supported by CAGE-seq and PolyA-seq, respectively, among which 6.7% and 7.2% had multiple transcription start sites (TSSs) and transcription termination sites (TTSs). We revealed that alternative usage of TSS and TTS of lncRNAs occurs pervasively during plant growth. Besides, we uncovered that many lncRNAs act in cis to regulate adjacent protein-coding genes (PCGs). It was especially interesting to observe 64 cases wherein the lncRNAs were involved in the TSS alternative usage of PCGs. We identified lncRNAs that are coexpressed with ovule- and fiber development-associated PCGs, or linked to GWAS single-nucleotide polymorphisms. We mapped the genome-wide binding sites of two lncRNAs with chromatin isolation by RNA purification sequencing. We also validated the transcriptional regulatory role of lnc-Ga13g0352 via virus-induced gene suppression assay, indicating that this lncRNA might act as a dual-functional regulator that either activates or inhibits the transcription of target genes.

[Medical image instance segmentation: from candidate region to no candidate region].

In recent years, the task of object detection and segmentation in medical image is the research hotspot and difficulty in the field of image processing. Instance segmentation provides instance-level labels for different objects belonging to the same class, so it is widely used in the field of medical image processing. In this paper, medical image instance segmentation was summarized from the following aspects: First, the basic principle of instance segmentation was described, the instance segmentation models were classified into three categories, the development context of the instance segmentation algorithm was displayed in two-dimensional space, and six classic model diagrams of instance segmentation were given. Second, from the perspective of the three models of two-stage instance segmentation, single-stage instance segmentation and three-dimensional (3D) instance segmentation, we summarized the ideas of the three types of models, discussed the advantages and disadvantages, and sorted out the latest developments. Third, the application status of instance segmentation in six medical images such as colon tissue image, cervical image, bone imaging image, pathological section image of gastric cancer, computed tomography (CT) image of lung nodule and X-ray image of breast was summarized. Fourth, the main challenges in the field of medical image instance segmentation were discussed and the future development direction was prospected. In this paper, the principle, models and characteristics of instance segmentation are systematically summarized, as well as the application of instance segmentation in the field of medical image processing, which is of positive guiding significance to the study of instance segmentation.

Development of a sensitive and reliable ELISA kit of urinary haptoglobin to predict progress of diabetic kidney disease.

AIMS: Urinary haptoglobin (UHp) is a potential biomarker for predicting progress of diabetic kidney disease (DKD) to remedy the defects of currently used urinary albumin. The clinical application of UHp is however limited, owing to the extremely low level in urine. This study aims to establish an enzyme-linked immunosorbent assay (ELISA) kit specifically for detecting UHp in urine samples of patients with diabetes and DKD. MATERIALS AND METHODS: Supersensitive human haptoglobin antibodies were generated for ELISA kit development, and the sensitivity, specificity and reproducibility of the kit was evaluated. This kit was used to detect UHp in 246 healthy individuals and 83 patients with type 2 diabetes (T2D). The interference of blood haptoglobin genotypes on UHp measurement was analysed. RESULTS: The UHp ELISA kit had a standard curve ranging from 5 to 200 ng/ml. The low detection limit was 0.11 ng/ml. The coefficients of variation of intra- and interassay were 5.5% and 8.3%, respectively. The kit showed high accuracy with 100.9% mean recovery rate, and linearity R2  = 0.999. The reference range of UHp was 0-42.3 ng/g creatinine (0-Q95) in the healthy individuals. UHp level was significantly higher in T2D patients with microalbuminuria and macroalbuminuria than that in T2D without microalbuminuria (p < 0.01). The UHp concentration measured by this kit was not affected by haptoglobin genotypes. CONCLUSIONS: We have generated an ELISA kit to accurately detect UHp levels, which is potentially a reliable biomarker of DKD.

Body Composition Changes in Hepatocellular Carcinoma: Prediction of Survival to Transcatheter Arterial Chemoembolization in Combination With Clinical Prognostic Factors.

Treatment-related toxicities and decreased levels of patient performance during cancer therapy might contribute to body composition changes (BCC) and thereby impact outcomes. This study investigated the association between BCC during transcatheter arterial chemoembolization (TACE) and outcome in patients with hepatocellular carcinoma (HCC), and developed a nomogram for predicting survival in combination with clinical prognostic factors (CPF). Pretreatment and posttreatment computed tomography (CT) images of 75 patients with HCC who were treated between 2015 and 2018 were analyzed. The bone mineral density (BMD), cross-sectional area of paraspinal muscles (CSAmuscle), subcutaneous fat area (SFA), and visceral fat area (VFA) were measured from two sets of CT images. Count the changes in body composition during treatment and sort out the CPF of patients. Using cox regression models, CSAmuscle change, SFA change, VFA change, child-push class, and portal vein thrombosis were independent prognostic factors for overall survival (OS) (HR=5.932, 2.384, 3.140, 1.744, 1.794, respectively. P < 0.05). Receiver operating characteristic curves (ROCs) showed the prediction model combination of BCC and CPF exhibited the highest predictive performance (AUC=0.937). Independent prognostic factors were all contained into the prognostic nomogram, the concordance index (C-index) of prognostic nomogram was 0.787 (95% CI, 0.675-0.887). Decision curve analysis (DCA) demonstrated that the prognostic nomogram was clinically useful. Nomogram-based risk classification systems were also constructed to facilitate risk stratification in HCC for optimization of clinical management. In conclusion, we identified CSAmuscle change, SFA change, VFA change, Child-Pugh class, and portal vein thrombosis were independent prognostic factors for HCC. The prognostic nomogram with a combination of BCC and CPF that can be applied in the individualized prediction of survival in patients with HCC after TACE.

LH upregulates connexin 43 expression in granulosa cells by activating the Wnt/ß-catenin signalling pathway.

Connexin (Cx) 43 is the most widely expressed gap junction protein in follicle granulosa cells and plays an important role in follicle development and growth. The aims of this study were to investigate the effects of LH on the expression of Cx43 and key proteins in the downstream Wnt-ß/catenin signalling pathway and to explore the mechanism underlying the regulation of Cx43 expression in granulosa cells. Primary culture granulosa cells were obtained from 21-day-old Sprague-Dawley rats, and were treated with different concentrations of LH (150, 300 and 600 IU L-1). Cx43 expression in granulosa cells was detected using immunofluorescence. Western blotting was used to detect the expression of Cx43, ß-catenin and Axin2 proteins (Axin2 is a protein that in humans is encoded by the AXIN2 gene, which presumably plays an important role in the regulation of the stability of ß-catenin in the Wnt signaling pathway) in granulosa cells with and without FH535 treatment (a Wnt/ß-catenin signalling pathway inhibitor). Cx43 expression was detected in the cytoplasm and cell membrane of granulosa cells. Treatment with a high concentration of LH (300 IU L-1) increased the expression of ß-catenin and Axin2, as well as that of Cx43. FH535 treatment reduced the LH-induced increases in Cx43, ß-catenin and Axin2. These results indicate that LH upregulates Cx43 expression in granular cells by activating the Wnt/ß-catenin signalling pathway.

Association of obesity status and metabolic syndrome with site-specific cancers: a population-based cohort study.

BACKGROUND: Obesity and metabolic syndrome (MetS) appear in clusters and are both associated with an increased risk of cancer. However, it remains unknown whether obesity status with or without MetS increases the risk of site-specific cancers. METHODS: We used data derived from 390,575 individuals (37-73 years old) from the UK Biobank who were enrolled from 2006-2016 with a median of 7.8 years of follow-up. Obesity was defined by BMI ≥ 30 kg/m2 and MetS was defined by the criteria of the Adult Treatment Panel-III (ATP-III). Cox proportional hazards models were used to investigate the associations of BMI and MetS with 22 cancers. RESULTS: Metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) phenotypes represented 6.7% and 17.9% of the total analytic samples and 27.1% and 72.9% of the included subpopulation with obesity, respectively. Obesity was independently associated with higher risks of 10 of 22 cancers. Stratified by metabolic status, the MUO phenotype was consistently associated with 10 obesity-related cancers. In contrast, the MHO phenotype was only associated with increased risks of five cancers: endometrium, oesophagus, kidney, pancreas and postmenopausal breast cancers. CONCLUSION: Even in metabolically healthy individuals, obesity was associated with increased risks of five cancers, whereas we did not find that these individuals were associated with increased risks of several other obesity-related cancers.

Exogenous luteinizing hormone promotes ovarian survival and function during cryopreservation and transplantation.

Cryopreservation and transplantation of the ovarian tissue is an alternative method by which malignant tumor survivors can recover fertility. Previously, it was reported that follicle stimulating hormone (FSH) promoted the survival and functioning of the ovarian tissue after in vitro cultivation. In this study, the expression of the luteinizing hormone receptor (LHR) was observed on the granule cell membrane after luteinizing hormone (LH) (0.3 IU/mL) was supplied as an exogenous hormone into the cultivation medium during ovarian vitrification in the postnatal period (PND) (1, 7, 14, 21, 28, 42, and 56 days PND). The expression of vascular endothelial growth factor (VEGF) and Connexins (Cx), and the recovery of ovarian functions were then assessed in mice models. The results showed that LH increased the production of normal follicles, and upregulated the expression of VEGF, Cx37, and Cx43 in vitrified ovaries. LH administration also shortened the recovery time of the estrus cycle in mice models. Additionally, no difference was observed in the rate of pregnancy and size of the first litter between the experimental and control groups. In conclusion, LH could promote the survival and functioning of the ovaries by upregulating the expression of VEGF, Cx43, and Cx37 during ovarian cryopreservation and transplantation.

Impact of setup errors on multi-isocenter volumetric modulated arc therapy for craniospinal irradiation.

Multi-isocenter volumetric modulated arc therapy (VMAT) is recommended for craniospinal irradiation (CSI) to smooth the dose distribution in the junction regions relying solely on inverse optimization. However, few studies have measured the dosimetric impact of setup errors on this multi-isocenter VMAT in the junction areas. The purpose of this study is to evaluate the impact of positional errors during VMAT CSI with two-dimension (2D) and three-dimension (3D) dosimetric measurements. A total of 20 patients treated by three-isocenter VMAT CSI were retrospectively reviewed and analyzed. A 3D diode array ArcCHECK and radiochromic film EBT3 were applied to measure the percentage gamma passing rates (%GPs) and dose distributions in the junction areas between the cranial/upper-spinal and the upper/lower-spinal fields with intentionally introduced setup errors of ± 1 mm, ±2 mm, ±3 mm, ±5 mm, and ± 8 mm, respectively. The length and volume of planning target volume (PTV) for these CSI patients ranged from 50.14 to 80.8 cm, and 1572.3 to 2114.5 cm3 , respectively. The %GPs for ±3 mm, ±5 mm, and ±8 mm positional errors were around 95%, 90%, and 85%, respectively, in the junction areas. The dosimetric verification results with EBT3 films indicated that cold and hot areas were observed with the increase of introduced setup errors. In conclusion, the dosimetric verification with intentionally introduced setup errors demonstrated that positional errors within 3 mm have a little impact for VMAT CSI, although setup errors should be minimized. Relying on the inverse optimization of VMAT to smooth the dose distribution in the junction areas is feasible for CSI.

Cross verification of independent dose recalculation, log files based, and phantom measurement-based pretreatment quality assurance for volumetric modulated arc therapy.

Independent treatment planning system (TPS) check with Mobius3D software, log files based quality assurance (QA) with MobiusFX, and phantom measurement-based QA with ArcCHECK were performed and cross verified for head-and-neck (17 patients), chest (16 patients), and abdominal (19 patients) cancer patients who underwent volumetric modulated arc therapy (VMAT). Dosimetric differences and percentage gamma passing rates (%GPs) were evaluated and compared for this cross verification. For the dosimetric differences in planning target volume (PTV) coverage, there was no significant difference among TPS vs. Mobius3D, TPS vs. MobiusFX, and TPS vs. ArcCHECK. For the dosimetric differences in organs at risks (OARs), the number of metrics with an average dosimetric differences higher than ±3% for TPS vs Mobius3D, TPS vs MobiusFX, and TPS vs ArcCHECK were 1, 1, 7; 2, 1, 4; 1, 1, 5 for the patients with head-and-neck, abdomen, and chest cancer, respectively. The %GPs of global gamma indices for Mobius3D and MobiousFX were above 97%, while it ranged from 92% to 96% for ArcCHECK. The %GPs of individual volume-based gamma indices were around 98% for Mobius3D and MobiousFX, except for γPTV for chest and abdominal cancer (88.9% to 92%); while it ranged from 86% to 99% for ArcCHECK. In conclusion, some differences in dosimetric metrics and gamma passing rates were observed with ArcCHECK measurement-based QA in comparison with independent dosecheck and log files based QA. Care must be taken when considering replacing phantom measurement-based IMRT/VMAT QA.

Prediction of response after chemoradiation for esophageal cancer using a combination of dosimetry and CT radiomics.

PURPOSE: To investigate the treatment response prediction feasibility and accuracy of an integrated model combining computed tomography (CT) radiomic features and dosimetric parameters for patients with esophageal cancer (EC) who underwent concurrent chemoradiation (CRT) using machine learning. METHODS: The radiomic features and dosimetric parameters of 94 EC patients were extracted and modeled using Support Vector Classification (SVM) and Extreme Gradient Boosting algorithm (XGBoost). The 94-sample dataset was randomly divided into a 70-sample training subset and a 24-sample independent test set while keeping the class proportions intact via stratification. A receiver operating characteristic (ROC) curve was used to assess the performance of models using radiomic features alone and using combined radiomic features and dosimetric parameters. RESULTS: A total of 42 radiomic features and 18 dosimetric parameters plus the patients' characteristic parameters were extracted for these 94 cases (58 responders and 36 non-responders). XGBoost plus principal component analysis (PCA) achieved an accuracy and area under the curve of 0.708 and 0.541, respectively, for models with radiomic features combined with dosimetric parameters, and 0.689 and 0.479, respectively, for radiomic features alone. Image features of GlobalMean X.333.1, Coarseness, Skewness, and GlobalStd contributed most to the model. The dosimetric parameters of gross tumor volume (GTV) homogeneity index (HI), Cord Dmax, Prescription dose, Heart-Dmean, and Heart-V50 also had a strong contribution to the model. CONCLUSIONS: The model with radiomic features combined with dosimetric parameters is promising and outperforms that with radiomic features alone in predicting the treatment response of patients with EC who underwent CRT. KEY POINTS: • The model with radiomic features combined with dosimetric parameters is promising in predicting the treatment response of patients with EC who underwent CRT. • The model with radiomic features combined with dosimetric parameters (prediction accuracy of 0.708 and AUC of 0.689) outperforms that with radiomic features alone (best prediction accuracy of 0.625 and AUC of 0.412). • The image features of GlobalMean X.333.1, Coarseness, Skewness, and GlobalStd contributed most to the treatment response prediction model. The dosimetric parameters of GTV HI, Cord Dmax, Prescription dose, Heart-Dmean, and Heart-V50 also had a strong contribution to the model.

Dosimetric benefits of intensity-modulated radiotherapy and volumetric-modulated arc therapy in the treatment of postoperative cervical cancer patients.

As the advantage of using complex volumetric-modulated arc therapy (VMAT) in the treatment of gynecologic cancer has not yet been fully determined, the purpose of this study was to investigate the dosimetric advantages of VMAT by comparing directly with whole pelvic conformal radiotherapy (CRT) and intensity-modulated radiotherapy (IMRT) in the treatment of 15 postoperative cervical cancer patients. Four-field CRT, seven-field IMRT, and two-arc VMAT plans were generated for each patient with identical objective functions to achieve clinically acceptable dose distribution. Target coverage and OAR sparing differences were investigated through dose-volume histogram (DVH) analysis. Nondosimtric differences between IMRT and VMAT were also compared. Target coverage presented by V95% were 88.9% ± 3.8%, 99.9% ± 0.07%, and 99.9% ± 0.1% for CRT, IMRT, and VMAT, respectively. Significant differences on conformal index (CI) and conformal number (CN) were observed with CIs of 0.37 ± 0.07, 0.55 ± 0.04, 0.61 ± 0.04, and CNs of 0.33 ± 0.06, 0.55 ± 0.04, 0.60 ± 0.04 for CRT, IMRT, and VMAT, respectively. IMRT and VMAT decreased the dose to bladder and rectum significantly compared with CRT. No significant differences on the Dmean, V45, and V30 of small bowel were observed among CRT, IMRT, and VMAT. However, VMAT (10.4 ± 4.8 vs. 19.8 ± 11.0, P = 0.004) and IMRT (12.3 ± 5.0 vs. 19.8 ± 11.0, P = 0.02) decreased V40, increased the Dmax of small bowel and the irradiation dose to femoral heads compared with CRT. VMAT irradiated less dose to bladder, rectum, small bowel and larger volume of health tissue with a lower dose (V5 and V10) compared with IMRT, although the differences were not statistical significant. In conclusion, VMAT and IMRT showed significant dosimetric advantages both on target coverage and OAR sparing compared with CRT in the treatment of postoperative cervical cancer. However, no significant difference between IMRT and VMAT was observed except for slightly better dose conformity, slightly less MU, and significant shorter delivery time achieved for VMAT.

Individual volume-based 3D gamma indices for pretreatment VMAT QA.

Although gamma analysis is still a widely accepted quantitative tool to analyze and report patient-specific QA for intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT), the correlation between the 2D percentage gamma passing rate (%GP), and the clinical dosimetric difference for IMRT and VMAT has been questioned. The purpose of this study was to investigate the feasibility of individual volume-based 3D gamma indices for pretreatment VMAT QA. Percentage dosimetric errors (%DE) of dose-volume histogram metrics (includes target volumes and organ at risks) between the treatment planning system and QA-reconstructed dose distribution, %GPs for individual volume and global gamma indices, as well their correlations and sensitivities were investigated for one- and two-arc VMAT plans. The %GPs of individual volumes had a higher percent of correlation with individual 15 %DE metrics compared with global %GPs. For two-arc VMAT at 2%/2 mm, 3%/3 mm, and 4%/4 mm criteria, individual volume %GPs were correlated with 9, 12, and 9 out of 15 %DE metrics, while global %GPs were correlated with only 2 out of 15 %DE metrics, respectively. For one-arc VMAT at 2%/2 mm, 3%/3 mm, and 4%/4 mm criteria, individual volume %GPs were correlated with 18, 16, and 13 out of 23 %DE metrics, and global %GPs were correlated with 19, 12, and 1 out 23 %DE metrics, respectively. The area under curves (AUC) of individual volume %GPs were higher than those of global %GPs for two-arc VMAT plans, but with mixed results for one-arc VMAT plans. In a conclusion, the idea of individual volume %GP was created and investigated to better serve for VMAT QA and individual volume-based %GP had a higher percent of correlation with DVH 15 %DE metrics compared with global %GP for both one- and two-arc VMAT plans.

Combined analysis of estradiol and ß-hCG to predict the early pregnancy outcome of FET: a retrospective study.

BACKGROUND: The accurate prediction of pregnancy outcomes in in vitro fertilization (IVF) cycles is crucial. While several studies have been conducted on the predictive power of serum estradiol (E2) and ß-hCG concentrations post-embryo transfer (ET) for pregnancy outcomes, there is debate on the predictive value of E2. The objective of this study was to investigate the predictive efficacy of combining serum E2 and ß-hCG levels on early reproductive outcomes 12 days after embryo transfer. METHODS: A total of 1521 patients with ß-hCG positive values on day 12 following frozen-thawed embryo transfer (FET) with natural endometrial preparation cycles (NCs) were gathered in affiliated Women's Hospital of Jiangnan University. Using logistic regression, the relationship between pregnancy outcome and early serum E2 and ß-hCG concentrations was examined. The receiver-operating characteristic (ROC) analysis was used to assess the predictive accuracy of the serum E2 and ß-hCG concentrations. RESULTS: Notable distinctions were observed in the serum E2 and ß-hCG levels on the twelfth day following FET with NCs between the groups classified as clinical pregnancy group (CP Group) and biochemical pregnancy group (BP Group). In addition, the cutoff values for E2 and ß-hCG on day 12 following FET with NCs in cleavage embryo group (CE Group) were 129.25 pg/mL and 156.60 mIU/mL, respectively. The threshold values for E2 and ß-hCG for the blastocyst group (B Group) were 174.45 pg/mL and 217.70 mIU/mL. Serum E2 day12 and ß-hCG day12 were found to be substantially linked with clinical pregnancy by logistic regression analysis. CONCLUSIONS: Serum E2 and ß-hCG concentrations were found to be significantly different between the CP Group and BP Group in infertility women underwent FET with NCs. Our retrospective cohort study's findings suggest that the combination of early E2 and ß-hCG levels on day 12 post-FET could be used as a predictive tool to evaluate the likelihood of both positive and negative pregnancy outcomes in FET with NCs.

Evaluation of Mucosal Healing in Crohn's Disease: Radiomics Models of Intestinal Wall and Mesenteric Fat Based on Dual-Energy CT.

This study aims to assess the effectiveness of radiomics signatures obtained from dual-energy computed tomography enterography (DECTE) in the evaluation of mucosal healing (MH) in patients diagnosed with Crohn's disease (CD). In this study, 106 CD patients with a total of 221 diseased intestinal segments (79 with MH and 142 non-MH) from two medical centers were included and randomly divided into training and testing cohorts at a ratio of 7:3. Radiomics features were extracted from the enteric phase iodine maps and 40-kev and 70-kev virtual monoenergetic images (VMIs) of the diseased intestinal segments, as well as from mesenteric fat. Feature selection was performed using the least absolute shrinkage and selection operator (LASSO) logistic regression. Radiomics models were subsequently established, and the accuracy of these models in identifying MH in CD was assessed by calculating the area under the receiver operating characteristic curve (AUC). The combined-iodine model formulated by integrating the intestinal and mesenteric fat radiomics features of iodine maps exhibited the most favorable performance in evaluating MH, with AUCs of 0.989 (95% confidence interval (CI) 0.977-1.000) in the training cohort and 0.947 (95% CI 0.884-1.000) in the testing cohort. Patients categorized as high risk by the combined-iodine model displayed a greater probability of experiencing disease progression when contrasted with low-risk patients. The combined-iodine radiomics model, which is built upon iodine maps of diseased intestinal segments and mesenteric fat, has demonstrated promising performance in evaluating MH in CD patients.