Intratumoral and peritumoral MRI radiomics nomogram for predicting parametrial invasion in patients with early-stage cervical adenocarcinoma and adenosquamous carcinoma.

OBJECTIVE: To develop a comprehensive nomogram based on MRI intra- and peritumoral radiomics signatures and independent risk factors for predicting parametrial invasion (PMI) in patients with early-stage cervical adenocarcinoma (AC) and adenosquamous carcinoma (ASC). METHODS: A total of 460 patients with IB to IIB cervical AC and ASC who underwent preoperative MRI examination and radical trachelectomy/hysterectomy were retrospectively enrolled and divided into primary, internal validation, and external validation cohorts. The original (Ori) and wavelet (Wav)-transform features were extracted from the volumetric region of interest of the tumour (ROI-T) and 3mm- and 5mm-peritumoral rings (ROI-3 and ROI-5), respectively. Then the Ori and Ori-Wav feature-based radiomics signatures from the tumour (RST) and 3 mm- and 5 mm-peritumoral regions (RS3 and RS5) were independently built and their diagnostic performances were compared to select the optimal ones. Finally, the nomogram was developed by integrating optimal intra- and peritumoral signatures and clinical independent risk factors based on multivariable logistic regression analysis. RESULTS: FIGO stage, disruption of the cervical stromal ring on MRI (DCSRMR), parametrial invasion on MRI (PMIMR), and serum CA-125 were identified as independent risk factors. The nomogram constructed by integrating independent risk factors, Ori-Wav feature-based RST, and RS5 yielded AUCs of 0.874 (0.810-0.922), 0.885 (0.834-0.924), and 0.966 (0.887-0.995) for predicting PMI in the primary, internal and external validation cohorts, respectively. Furthermore, the nomogram was superior to radiomics signatures and clinical model for predicting PMI in three cohorts. CONCLUSION: The nomogram can preoperatively, accurately, and noninvasively predict PMI in patients with early-stage cervical AC and ASC. CLINICAL RELEVANCE STATEMENT: The nomogram can preoperatively, accurately, and noninvasively predict PMI and facilitate precise treatment decisions regarding chemoradiotherapy or radical hysterectomy in patients with early-stage cervical AC and ASC. KEY POINTS: The accurate preoperative prediction of PMI in early-stage cervical AC and ASC can facilitate precise treatment decisions regarding chemoradiotherapy or radical hysterectomy. The nomogram integrating independent risk factors, Ori-Wav feature-based RST, and RS5 can preoperatively, accurately, and noninvasively predict PMI in early-stage cervical AC and ASC. The nomogram was superior to radiomics signatures and clinical model for predicting PMI in early-stage cervical AC and ASC.

Interleaved imaging of cerebral hemodynamics and blood flow index to monitor ischemic stroke and treatment in rat by volumetric diffuse optical tomography.

Diffuse optical tomography (DOT) has been used by several groups to assess cerebral hemodynamics of cerebral ischemia in humans and animals. In this study, we combined DOT with an indocyanine green (ICG)-tracking method to achieve interleaved images of cerebral hemodynamics and blood flow index (BFI) using two middle cerebral artery occlusion (MCAO) rat models. To achieve volumetric images with high-spatial resolution, we first integrated a depth compensation algorithm (DCA) with a volumetric mesh-based rat head model to generate three-dimensional (3D) DOT on a rat brain atlas. Then, the experimental DOT data from two rat models were collected using interleaved strategy for cerebral hemodynamics and BFI during and after ischemic stroke, with and without a thrombolytic therapy for the embolic MCAO model. The acquired animal data were further analyzed using the integrated rat-atlas-guided DOT method to form time-evolving 3D images of both cerebral hemodynamics and BFI. In particular, we were able to show and identify therapeutic outcomes of a thrombolytic treatment applied to the embolism-induced ischemic model. This paper demonstrates that volumetric DOT is capable of providing high-quality, interleaved images of cerebral hemodynamics and blood perfusion in small animals during and after ischemic stroke, with excellent 3D visualization and quantifications.

Atlas-guided volumetric diffuse optical tomography enhanced by generalized linear model analysis to image risk decision-making responses in young adults.

Diffuse optical tomography (DOT) is a variant of functional near infrared spectroscopy and has the capability of mapping or reconstructing three dimensional (3D) hemodynamic changes due to brain activity. Common methods used in DOT image analysis to define brain activation have limitations because the selection of activation period is relatively subjective. General linear model (GLM)-based analysis can overcome this limitation. In this study, we combine the atlas-guided 3D DOT image reconstruction with GLM-based analysis (i.e., voxel-wise GLM analysis) to investigate the brain activity that is associated with risk decision-making processes. Risk decision-making is an important cognitive process and thus is an essential topic in the field of neuroscience. The Balloon Analog Risk Task (BART) is a valid experimental model and has been commonly used to assess human risk-taking actions and tendencies while facing risks. We have used the BART paradigm with a blocked design to investigate brain activations in the prefrontal and frontal cortical areas during decision-making from 37 human participants (22 males and 15 females). Voxel-wise GLM analysis was performed after a human brain atlas template and a depth compensation algorithm were combined to form atlas-guided DOT images. In this work, we wish to demonstrate the excellence of using voxel-wise GLM analysis with DOT to image and study cognitive functions in response to risk decision-making. Results have shown significant hemodynamic changes in the dorsal lateral prefrontal cortex (DLPFC) during the active-choice mode and a different activation pattern between genders; these findings correlate well with published literature in functional magnetic resonance imaging (fMRI) and fNIRS studies.

Downsizing and soft X-ray tomography for cellular uptake of interpenetrated metal-organic frameworks.

Metal-organic frameworks (MOFs) are porous materials with potential in biomedical applications such as sensing, drug delivery, and radiosensitization. However, how to tune the properties of the MOFs for such applications remains challenging. Herein, we synthesized two MOFs, Zr-PEB and Hf-PEB. Zr-PEB can be classified as porous interpenetrated zirconium frameworks (PIZOFs) and Hf-PEB is its analogue. We controlled their sizes while maintaining their crystal structure by employing a coordination modulation strategy. They were designed to serve as sensitizer for X-ray therapy and as potential drug carriers. Comprehensive characterizations of the MOFs' properties have been conducted, and the in vitro biological impacts have been studied. Since viability assay showed that Hf-PEB was more biocompatible compared to Zr-PEB, the cellular uptake of Hf-PEB by cells was evaluated using both fluorescence microscopy and soft X-ray tomography (SXT), and the three-dimensional structure of Hf-PEB in cells was observed. The results revealed the potential of Zr-PEB and Hf-PEB as nanomaterials for biomedical applications and demonstrated that SXT is an effective tool to assist the development of such materials.

Correlation between connexin 43 expression in circulating tumor cells and biological characteristics of breast cancer.

Background: Connexin 43 (Cx43) has been closely linked to the occurrence and progression of breast cancer. Distant metastasis of breast cancer is aided by the epithelial-mesenchymal transition of circulating tumor cells (CTCs). However, the impact of Cx43 expression on CTCs and the extent of its role in the disease remain unclear. Methods: We determined CTCs in 156 patients, who had breast cancer with a disease course of two or more years. We also measured the expression of Cx43 in the CTCs. The CTCs were detected in the blood of 139 of these patients. These 139 patients were divided into two groups: the Cx43 group and the non-Cx43 group based on their Cx43 expression. Results: Overall, Cx43 expression was found in 83 of the 139 patients (59.7%, 83/139 cases). The two groups significantly differed in terms of the number of mixed biphenotypic type CTCs and the total number of CTCs (P < 0.05). There were significant correlations between Cx43 expression and Ki67 expression, tumor size, lymph node metastasis, and TNM stage (P < 0.05 for all). The data suggested that patients with Cx43 expression had a higher risk of distant metastasis and had later-stage disease. The difference in Cx43 expression between patients with and without epidermal growth factor receptor 2 (Her2) overexpression was statistically significant (P < 0.05). The difference in disease-free survival (DFS) between the two groups was statistically significant (P = 0.03), and the Cx43 group had a shorter duration of DFS. Univariate Cox regression analysis revealed that Cx43 expression, Her2 expression, and tumor size were significantly correlated with DFS (P = 0.03, 0.0023, and 0.01, respectively). Conclusion: Cx43 expression in the CTCs of patients with breast cancer is a cancer-promoting factor.

Comparison of neural correlates of risk decision making between genders: an exploratory fNIRS study of the Balloon Analogue Risk Task (BART).

Functional magnetic resonance imaging (fMRI) research rarely reports gender differences in the neural correlates of risk decision making due to small sample sizes. In this functional near-infrared spectroscopy (fNIRS)-based imaging study of active and passive risk decision making, gender differences in oxygenated hemoglobin (HbO) concentration changes were investigated in the prefrontal cortex (PFC) of healthy adults. Forty adult participants (25-44 years; males=23) completed two sets of 15 balloon trials in active and passive decision making modes of the Balloon Analogue Risk Task (BART). In active mode, participants chose the number of balloon inflations, decided when to collect money, or risked accrued money if balloons exploded. BART is psychometrically well established and has predictive validity to real-world risk taking. The blocked experimental design and modification of BART for fNIRS were guided by a previous fMRI study that examined the neural correlates of risk decision making in young adults [Rao, H., Korczykowski, M., Pluta, J., Hoang, A., Detre, J.A., 2008. Neural correlates of voluntary and involuntary risk taking in the human brain: An fMRI study of the Balloon Analog Risk Task (BART). NeuroImage 42, 902-910]. Our findings were consistent with the previous fMRI study: no or little PFC activation during passive mode but strong PFC activation during active wins and losses among total sample. Active losses in females were associated with more significant bilateral activation in dorsal lateral prefrontal cortex (DLPFC) than males; no significant gender differences were found in DLPFC activation during active wins. Gender differences existed in direction and strength of correlations between BART behavioral and hemodynamic data. This study shows that use of fNIRS is a feasible, accessible, and less costly way to achieve adequate study power and investigate gender differences in neural correlates of risk decision making.

MRI Texture Analysis for Preoperative Prediction of Lymph Node Metastasis in Patients with Nonsquamous Cell Cervical Carcinoma.

RATIONALE AND OBJECTIVES: To preoperatively predict lymph node metastasis (LNM) in patients with cervical nonsquamous cell carcinoma (non-SCC) based on magnetic resonance imaging (MRI) texture analysis. MATERIALS AND METHODS: This retrospective study included 104 consecutive patients (mean age of 47.2 ± 11.3 years) with stage IB-IIA cervical non-SCC. According to the ratio of 7:3, 72, and 32 patients were randomly divided into the training and testing cohorts. A total of 272 original features were extracted. In the process of feature selection, features with intraclass correlation coefficients (ICCs) less than 0.8 were eliminated. The Pearson correlation coefficient (PCC) and analysis of variance (ANOVA) were applied to reduce redundancy, overfitting, and selection biases. Further, a support vector machine (SVM) with linear kernel function was applied to select the optimal feature set with a high discrimination power. RESULTS: The T2WI + DWI-based, T2WI + DWI + CE-T1WI-based and T2WI + DWI + LNS-MRI (LN status on MRI)-based SVM models yielded an AUC and accuracy of 0.78 and 0.79; 0.79 and 0.69; 0.79 and 0.81 for predicting LNM in the training cohort, and 0.82 and 0.78; 0.82 and 0.69; 0.79 and 0.72 in the testing cohort. The T2WI + DWI-based, T2WI + DWI + CE-T1WI-based and T2WI + DWI + LNS-MRI-based SVM models performed better than morphologic criteria of LNS-MRI and yield similar discrimination abilities in predicting LNM in the training and testing cohorts (all p-value > 0.05). In addition, the T2WI + DWI-based and T2WI + DWI + LNS-MRI-based SVM models showed robust performance in the AC and ASC subgroups (all p-value > 0.05). CONCLUSION: The T2WI + DWI-based, T2WI + DWI + CE-T1WI-based and T2WI+DWI+LNS-MRI-based SVM models showed similar good discrimination ability and performed better than the morphologic criteria of LNS-MRI in predicting LNM in patients with cervical non-SCC. The inclusion of the CE-T1WI sequence and morphologic criteria of LNS-MRI did not significantly improve the performance of the T2WI + DWI-based model. The T2WI + DWI-based and T2WI + DWI + LNS-MRI-based SVM models showed robust performance in the subgroup analysis.

An NT-3-releasing bioscaffold supports the formation of TrkC-modified neural stem cell-derived neural network tissue with efficacy in repairing spinal cord injury.

The mechanism underlying neurogenesis during embryonic spinal cord development involves a specific ligand/receptor interaction, which may be help guide neuroengineering to boost stem cell-based neural regeneration for the structural and functional repair of spinal cord injury. Herein, we hypothesized that supplying spinal cord defects with an exogenous neural network in the NT-3/fibroin-coated gelatin sponge (NF-GS) scaffold might improve tissue repair efficacy. To test this, we engineered tropomyosin receptor kinase C (TrkC)-modified neural stem cell (NSC)-derived neural network tissue with robust viability within an NF-GS scaffold. When NSCs were genetically modified to overexpress TrkC, the NT-3 receptor, a functional neuronal population dominated the neural network tissue. The pro-regenerative niche allowed the long-term survival and phenotypic maintenance of the donor neural network tissue for up to 8 weeks in the injured spinal cord. Additionally, host nerve fibers regenerated into the graft, making synaptic connections with the donor neurons. Accordingly, motor function recovery was significantly improved in rats with spinal cord injury (SCI) that received TrkC-modified NSC-derived neural network tissue transplantation. Together, the results suggested that transplantation of the neural network tissue formed in the 3D bioactive scaffold may represent a valuable approach to study and develop therapies for SCI.

Development of a compensation algorithm for accurate depth localization in diffuse optical tomography.

Diffuse optical tomography endures poor depth localization, since its sensitivity decreases severely with increased depth. In this study, we demonstrate a depth compensation algorithm (DCA), which optimally counterbalances the decay nature of light propagation in tissue so as to accurately localize absorbers in deep tissue. The novelty of DCA is to directly modify the sensitivity matrix, rather than the penalty term of regularization. DCA is based on maximum singular values (MSVs) of layered measurement sensitivities; these MSVs are inversely utilized to create a balancing weight matrix for compensating the measurement sensitivity in increased depth. Both computer simulations and laboratory experiments were performed to validate DCA. These results demonstrate that one (or two) 3-cm-deep absorber(s) can be accurately located in both lateral plane and depth within the laboratorial position errors.

Decellularization optimizes the inhibitory microenvironment of the optic nerve to support neurite growth.

Allogeneic or homologous tissue transplantation is an effective strategy to repair tissue injury. However, the central nervous tissues like the brain, spinal cord, and optic nerve are not ideal materials for nervous tissue regeneration due to the excessive axonal inhibitor cues in their microenvironments. In the present study, we found that decellularization optimizes the function of the adult optic nerve in supporting the oriented outgrowth of dorsal root ganglion (DRG) neurites. The neurites growing on the decellularized optic nerve (DON) showed longer extension distances than those growing on the normal optic nerve (ON). Neurite branching was also significantly increased on the DON compared to on the ON. Decellularization selectively removed some axon-inhibitory molecules such as myelin-associated glycoprotein (basically not detected in DON) and chondroitin sulfate proteoglycans (detected in DON at a level less than 0.3 fold that in ON) and preserved some axon-promoted extracellular matrix (ECM) proteins, including collagen IV and laminin (detected at levels 6.0-fold higher in DON than in ON). Furthermore, collagen IV and laminin were shown to be preserved in DON, and their binding activities with integrin α1 were retained to promote the extension of DRG neurites. Together, the findings provide a feasible way to optimize the axon-inhibited microenvironment of central nervous tissues and establish a theoretical basis for the application of DON scaffolds in repairing central nervous injury.