Feature selection based on unsupervised clustering evaluation for predicting neoadjuvant chemoradiation response for patients with locally advanced rectal cancer.

Accurate response prediction allows for personalized cancer treatment of locally advanced rectal cancer (LARC) with neoadjuvant chemoradiation. In this work, we designed a convolutional neural network (CNN) feature extractor with switchable 3D and 2D convolutional kernels to extract deep learning features for response prediction. Compared with radiomics features, convolutional kernels may adaptively extract local or global image features from multi-modal MR sequences without the need of feature predefinition.

A subregion-based survival prediction framework for GBM via multi-sequence MRI space optimization and clustering-based feature bundling and construction.

Aiming at accurate survival prediction of Glioblastoma (GBM) patients following radiation therapy, we developed a subregion-based survival prediction framework via a novel feature construction method on multi-sequence MRIs. The proposed method consists of two main steps: (1) a feature space optimization algorithm to determine the most appropriate matching relation derived between multi-sequence MRIs and tumor subregions, for using multimodal image data more reasonable; (2) a clustering-based feature bundling and construction algorithm to compress the high-dimensional extracted radiomic features and construct a smaller but effective set of features, for accurate prediction model construction. For each tumor subregion, a total of 680 radiomic features were extracted from one MRI sequence using Pyradiomics.

Biomarkers of joint metabolism and bone mineral density are associated with early knee osteoarthritis in premenopausal females.

Introduction: Biomarkers of bone and cartilage metabolism were proposed as early diagnosis indicators for knee osteoarthritis (OA), however, which were influenced by disease stage, age, and menopause state. Accurate diagnosis indicators are eagerly awaited. The current study aims to investigate associations of joint metabolism biomarkers and bone mineral density (BMD) with early knee OA in males and premenopausal females before age 50 years.

A hybrid feature selection-based brain tumor detection and segmentation in multiparametric magnetic resonance imaging.

Purpose: To develop a novel method based on feature selection, combining convolutional neural network (CNN) and ensemble learning (EL), to achieve high accuracy and efficiency of glioma detection and segmentation using multiparametric MRIs.

Methods: We proposed an evolutionary feature selection-based hybrid approach for glioma detection and segmentation on 4 MR sequences (T2-FLAIR, T1, T1Gd, and T2). First, we trained a lightweight CNN to detect glioma and mask the suspected region to process large batch of MRI images.

A hybrid feature selection-based approach for brain tumor detection and automatic segmentation on multiparametric magnetic resonance images.

Purpose: To develop a novel method based on feature selection, combining convolutional neural network (CNN) and ensemble learning (EL), to achieve high accuracy and efficiency of glioma detection and segmentation using multiparametric MRIs.

Methods: We proposed an evolutionary feature selection-based hybrid approach for glioma detection and segmentation on 4 MR sequences (T2-FLAIR, T1, T1Gd, and T2). First, we trained a lightweight CNN to detect glioma and mask the suspected region to process large batch of MRI images.

Clinical Applications of DSC-MRI Parameters Assess Angiogenesis and Differentiate Malignant From Benign Soft Tissue Tumors in Limbs.

Objective: To investigate the correlation between dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) parameters and angiogenesis and to explore prospectively the feasibility of using DSC-MRI to differentiate malignant from benign soft tissue tumors (STTs) in limbs.

Methods: This prospective study included 33 patients with STTs in limbs who underwent DSC-MRI after bolus Gd-DTPA infusion. All STTs were confirmed by pathological examination after surgery and microvessel density (MVD), vascular endothelial growth factor (VEGF) expression, were evaluated by immune-histochemical analysis.

Lung cancer therapy using doxorubicin and curcumin combination: Targeted prodrug based, pH sensitive nanomedicine.

Lung cancer is the leading cause of cancer death worldwide. To overcome the toxic side effects and multidrug resistance (MDR) during doxorubicin (DOX) chemotherapy, a urokinase plasminogen activator receptor (uPAR) targeting U11 peptide decorated, pH-sensitive, dual drugs co-encapsulated nanoparticles (NPs) system is employed in this study. A U11 peptide conjugated, pH-sensitive DOX prodrug (U11-DOX) was synthesized and used as materials to produce NPs.

Severity and distribution of cartilage damage and bone marrow edema in the patellofemoral and tibiofemoral joints in knee osteoarthritis determined by MRI.

The aim of the present study was to analyze the distribution and severity of cartilage damage (CD) and bone marrow edema (BME) of the patellofemoral and tibiofemoral joints (PFJ and TFJ, respectively) in patients with knee osteoarthritis (OA), and to determine whether a correlation exists between BME and CD in knee OA, using magnetic resonance imaging (MRI). Forty-five patients diagnosed with knee OA (KOA group) and 20 healthy individuals (control group) underwent sagittal multi-echo recalled gradient echo sequence scans, in addition to four conventional MR sequence scans. Knee joints were divided into 15 subregions by the whole-organ MRI scoring method.

Computerized segmentation of pulmonary nodules depicted in CT examinations using freehand sketches.

Purpose: To aid a consistent segmentation of pulmonary nodules, the authors describe a novel computerized scheme that utilizes a freehand sketching technique and an improved break-and-repair strategy.

Methods: This developed scheme consists of two primary parts. The first part is freehand sketch analysis, where the freehand sketching not only serves a natural way of specifying the location of a nodule, but also provides a mechanism for inferring adaptive information (e.

The height for screw index (HSI) predicts the development of C2 nerve dysfunction associated with C1 lateral mass screw fixation for atlantoaxial instability.

Purpose: To propose a new measure, the height for screw index (HSI), as a predictor of C2 nerve dysfunction in patients who have received posterior C1 lateral mass screw (C1LMS) fixation for atlantoaxial instability and to examine whether the HSI scores correlated with the development of C2 nerve dysfunction through retrospective analysis of 104 C1LMS inserted in 52 patients with atlantoaxial instability.

Methods: The medical records of patients who underwent C1LMS fixation were retrospectively reviewed. C1LMS, 3.

EADC Values in Diagnosis of Renal Lesions by 3.0 T Diffusion-Weighted Magnetic Resonance Imaging: Compared with the ADC Values.

Exponential apparent diffusion coefficient (EADC) is an indicator of diffusion-weighted imaging (DWI) and reflects the pathological changes of tissues quantitatively. However, no study has been investigated in the space-occupying kidney disease using EADC values. This study aims to evaluate the diagnostic role of EADC values at a high magnetic field strength (3.

Illustration of the obstacles in computerized lung segmentation using examples.

Purpose: Automated lung volume segmentation is often a preprocessing step in quantitative lung computed tomography (CT) image analysis. The objective of this study is to identify the obstacles in computerized lung volume segmentation and illustrate those explicitly using real examples. Awareness of these "difficult" cases may be helpful for the development of a robust and consistent lung segmentation algorithm.

Age and sex related measurement of craniofacial soft tissue thickness and nasal profile in the Chinese population.

The purpose of this study was to acquire accurate data of craniofacial soft tissue thickness (CFSTT) and nasal profile in Chinese people of Han population. A total of 31 anatomical landmarks and 4 nasal profile parameters were determined using magnetic resonance imaging (MRI) in 425 subjects (233 males and 192 females). In the present study, the mean CFSTT values of male subjects exceeded those of female subjects at most anatomical landmarks except at seven (22.

A meta-analysis of the accuracy of prostate cancer studies which use magnetic resonance spectroscopy as a diagnostic tool.

Objective: We aimed to do a meta-analysis of the existing literature to assess the accuracy of prostate cancer studies which use magnetic resonance spectroscopy (MRS) as a diagnostic tool.

Materials And Methods: Prospectively, independent, blind studies were selected from the Cochrane library, Pubmed, and other network databases. The criteria for inclusion and exclusion in this study referenced the criteria of diagnostic research published by the Cochrane center.

Paramagnetic particles carried by cell-penetrating peptide tracking of bone marrow mesenchymal stem cells, a research in vitro.

The ability to track the distribution and differentiation of stem cells by high-resolution imaging techniques would have significant clinical and research implications. In this study, a model cell-penetrating peptide was used to carry gadolinium particles for magnetic resonance imaging of the mesenchymal stem cells. The mesenchymal stem cells were isolated from rat bone marrow by Percoll and identified by osteogenic differentiation in vitro.