Unraveling Residual Stress Distribution Characteristics of 6061-T6 Aluminum Alloy Induced by Laser Shock Peening.

Laser shock peening (LSP) is a powerful technique for improving the fatigue performance of metallic components by customizing compressive residual stresses in the desired near-surface regions. In this study, the residual stress distribution characteristics of 6061-T6 aluminum alloy induced by LSP were identified by the X-ray diffraction method, and their dependent factors (i.e.

MRI Manifestations of Breast Cancer Stroma and their Role in Predicting Molecular Subtype: A Case-control Study.

Objective: This study explored whether breast MRI manifestations could be used to predict the stroma distribution of breast cancer (BC) and the role of tumor stroma-based MRI manifestations in molecular subtype prediction.

Methods: 57 patients with pathologically confirmed invasive BC (non-special type) who had lumpy BC on MRI within one week before surgery were retrospectively collected in the study. Stroma distributions were classified according to their characteristics in the pathological sections.

Effects of MRI radiomics combined with clinical data in evaluating lymph node metastasis in mrT1-3a staging rectal cancer.

Objective: To investigate the value of a clinical-MRI radiomics model based on clinical characteristics and T2-weighted imaging (T2WI) for preoperatively evaluating lymph node (LN) metastasis in patients with MRI-predicted low tumor (T) staging rectal cancer (mrT1, mrT2, and mrT3a with extramural spread ≤ 5 mm).

Methods: This retrospective study enrolled 303 patients with low T-staging rectal cancer (training cohort, n = 213, testing cohort n = 90). A total of 960 radiomics features were extracted from T2WI.

Comparison of the clinical value of MRI and plasma markers for cognitive impairment in patients aged ≥75 years: a retrospective study.

Background: Dementia has become the main cause of disability in older adults aged ≥75 years. Cerebral small vessel disease (CSVD) is involved in cognitive impairment (CI) and dementia and is a cause of vascular CI (VCI), which is manageable and its onset and progression can be delayed. Simple and effective markers will be beneficial to the early detection and intervention of CI.

Prognostic predictors of radical resection of stage I-IIIB non-small cell lung cancer: the role of preoperative CT texture features, conventional imaging features, and clinical features in a retrospectively analyzed.

Background: To investigate the value of preoperative computed tomography (CT) texture features, routine imaging features, and clinical features in the prognosis of non-small cell lung cancer (NSCLC) after radical resection.

Methods: Demographic parameters and clinically features were analyzed in 107 patients with stage I-IIIB NSCLC, while 73 of these patients received CT scanning and radiomic characteristics for prognosis assessment. Texture analysis features include histogram, gray size area matrix and gray co-occurrence matrix features.

Deep Learning Radiomics of Preoperative Breast MRI for Prediction of Axillary Lymph Node Metastasis in Breast Cancer.

The objective of this study is to develop a radiomic signature constructed from deep learning features and a nomogram for prediction of axillary lymph node metastasis (ALNM) in breast cancer patients. Preoperative magnetic resonance imaging data from 479 breast cancer patients with 488 lesions were studied. The included patients were divided into two cohorts by time (training/testing cohort, n = 366/122).

Preoperative Cervical Lymph Node Metastasis Prediction in Papillary Thyroid Carcinoma: A Noninvasive Clinical Multimodal Radiomics (CMR) Nomogram Analysis.

This study aimed to evaluate the feasibility of applying a clinical multimodal radiomics nomogram based on ultrasonography (US) and multiparametric magnetic resonance imaging (MRI) for the prediction of cervical lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) preoperatively. We performed retrospective evaluations of 133 patients with pathologically confirmed PTC, who were assigned to the training cohort and validation cohort (7 : 3), and extracted radiomics features from the preoperative US, T2-weighted (T2WI),diffusion-weighted (DWI), and contrast-enhanced T1-weighted (CE-T1WI) images. Optimal subsets were selected using minimum redundancy, maximum relevance, and recursive feature elimination in the support vector machine (SVM).

Shoulder MRI-based radiomics for diagnosis and severity staging assessment of surgically treated supraspinatus tendon tears.

Objective: To develop and validate MRI-based radiomics models capable of evaluating supraspinatus tendon tears within the shoulder joints by using arthroscopy as the reference standard.

Methods: A total of 432 patients (332 in the training set and 100 in the external validation set) with intact supraspinatus tendon (n = 202) and supraspinatus tendon tear (n = 230, 130 full-thickness tears and 100 partial-thickness tears) were enrolled. Radiomics features were extracted from fat-saturated T2-weighted coronal images.

Enhanced CT-based texture analysis and radiomics score for differentiation of pleomorphic adenoma, basal cell adenoma, and Warthin tumor of the parotid gland.

Objective: To evaluate the diagnostic performance of computed tomography (CT) radiomics analysis for differentiating pleomorphic adenoma (PA), Warthin tumor (WT), and basal cell adenoma (BCA).

Methods: A total of 189 patients with PA ( = 112), WT ( = 53) and BCA ( = 24) were divided into a training set ( = 133) and a test set ( = 56). The radiomics features were extracted from plain CT and contrast-enhanced CT images.

Histogram-based analysis of diffusion-weighted imaging for predicting aggressiveness in papillary thyroid carcinoma.

Background: To assess the potential of apparent diffusion coefficient (ADC) map in predicting aggressiveness of papillary thyroid carcinoma (PTC) based on whole-tumor histogram-based analysis.

Methods: A total of 88 patients with PTC confirmed by pathology, who underwent neck magnetic resonance imaging, were enrolled in this retrospective study. Whole-lesion histogram features were extracted from ADC maps and compared between the aggressive and non-aggressive groups.

Development and validation of CT-based radiomics nomogram for the classification of benign parotid gland tumors.

Purpose: Accurate preoperative diagnosis of parotid tumor is essential for the formulation of optimal individualized surgical plans. The study aims to investigate the diagnostic performance of radiomics nomogram based on contrast-enhanced computed tomography (CT) images in the differentiation of the two most common benign parotid gland tumors.

Methods: One hundred and ten patients with parotid gland tumors including 76 with pleomorphic adenoma (PA) and 34 with adenolymphoma (AL) confirmed by histopathology were included in this study.

Predicting coronary artery calcified plaques using perivascular fat CT radiomics features and clinical risk factors.

Objective: The purpose of this study was to develop a combined radiomics model to predict coronary plaque texture using perivascular fat CT radiomics features combined with clinical risk factors.

Methods: The data of 200 patients with coronary plaques were retrospectively analyzed and randomly divided into a training group and a validation group at a ratio of 7:3. In the training group, The best feature set was selected by using the maximum correlation minimum redundancy method and the least absolute shrinkage and selection operator.

Prognostic and predictive value of radiomic signature in stage I lung adenocarcinomas following complete lobectomy.

Background: The overall survival (OS) of stage I operable lung cancer is relatively low, and not all patients can benefit from adjuvant chemotherapy. This study aimed to develop and validate a radiomic signature (RS) for prediction of OS and adjuvant chemotherapy candidates in stage I lung adenocarcinoma.

Methods: A total of 474 patients from 2 centers were divided into 1 training (n = 287), 1 internal validation (n = 122), and 1 external validation (n = 65) cohorts.

A novel clinical radiomics nomogram at baseline to predict mucosal healing in Crohn's disease patients treated with infliximab.

Objectives: Mucosal healing (MH) is currently the gold standard in Crohn's disease (CD) management. Noninvasive assessment of MH in CD patients is increasingly a concern of clinicians.

Methods: This retrospective study included 106 patients with confirmed CD who were divided into a training cohort (n = 73) and a testing cohort (n = 33).

MRI whole-lesion texture analysis on ADC maps for the prognostic assessment of ischemic stroke.

Background: This study aims is to explore whether it is feasible to use magnetic resonance texture analysis (MRTA) in order to distinguish favorable from unfavorable function outcomes and determine the prognostic factors associated with favorable outcomes of stroke.

Methods: The retrospective study included 103 consecutive patients who confirmed unilateral anterior circulation subacute ischemic stroke by computed tomography angiography between January 2018 and September 2019. Patients were divided into favorable outcome (modified Rankin scale, mRS ≤ 2) and unfavorable outcome (mRS > 2) groups according to mRS scores at day 90.

Usefulness of Noncontrast MRI-Based Radiomics Combined Clinic Biomarkers in Stratification of Liver Fibrosis.

Purpose: To develop and validate a radiomic nomogram based on texture features from out-of-phase T1W images and clinical biomarkers in prediction of liver fibrosis.

Materials And Methods: Patients clinically diagnosed with chronic liver fibrosis who underwent liver biopsy and noncontrast MRI were enrolled. All patients were assigned to the nonsignificant fibrosis group with fibrosis stage <2 and the significant fibrosis group with stage ≥2.

Associations between pericarotid fat density and image-based risk characteristics of carotid plaque.

Objectives: In this study, we aimed to evaluate the associations between pericarotid fat density (PFD) and various risk characteristics of carotid plaque.

Methods: We retrospectively evaluated consecutive patients who were subjected to both high-resolution MRI and carotid artery CT angiography CTA at our institution between January 2016 and April 2021. The section of the carotid artery with the most severe lumen stenosis was selected from each patient for analysis.

A Radiomics Nomogram for Distinguishing Benign From Malignant Round-Like Breast Tumors.

Objective: The objective of this study is to develop a radiomics nomogram for the presurgical distinction of benign and malignant round-like solid tumors.

Methods: This retrospective trial enrolled patients with round-like tumors who had received preoperative digital mammography (DM) no sooner than 20 days prior to surgery. Breast tumors were segmented manually on DM images in order to extract radiomic features.

Development of a PET/CT molecular radiomics-clinical model to predict thoracic lymph node metastasis of invasive lung adenocarcinoma ≤ 3 cm in diameter.

Background: To investigate the value of F-FDG PET/CT molecular radiomics combined with a clinical model in predicting thoracic lymph node metastasis (LNM) in invasive lung adenocarcinoma (≤ 3 cm).

Methods: A total of 528 lung adenocarcinoma patients were enrolled in this retrospective study. Five models were developed for the prediction of thoracic LNM, including PET radiomics, CT radiomics, PET/CT radiomics, clinical and integrated PET/CT radiomics-clinical models.

Computed Tomography Radiomics-Based Prediction of Microvascular Invasion in Hepatocellular Carcinoma.

Background: Due to the high recurrence rate in hepatocellular carcinoma (HCC) after resection, preoperative prognostic prediction of HCC is important for appropriate patient management. Exploring and developing preoperative diagnostic methods has great clinical value in treating patients with HCC. This study sought to develop and evaluate a novel combined clinical predictive model based on standard triphasic computed tomography (CT) to discriminate microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

Multimodality MRI-based radiomics for aggressiveness prediction in papillary thyroid cancer.

Objective: To investigate the ability of a multimodality MRI-based radiomics model in predicting the aggressiveness of papillary thyroid carcinoma (PTC).

Methods: This study included consecutive patients who underwent neck magnetic resonance (MR) scans and subsequent thyroidectomy during the study period. The pathological diagnosis of thyroidectomy specimens was the gold standard to determine the aggressiveness.

A Novel Multimodal Radiomics Model for Predicting Prognosis of Resected Hepatocellular Carcinoma.

Objective: To explore a new model to predict the prognosis of liver cancer based on MRI and CT imaging data.

Methods: A retrospective study of 103 patients with histologically proven hepatocellular carcinoma (HCC) was conducted. Patients were randomly divided into training (n = 73) and validation (n = 30) groups.

Computed Tomography-Based Radiomics Nomogram for Predicting the Postoperative Prognosis of Esophageal Squamous Cell Carcinoma: A Multicenter Study.

Objectives: The aim of this study was to evaluate and identify the predictive value of combining CT radiomics features and clinical features to determine recurrence-free survival (RFS) and overall survival (OS) after surgery in patients with esophageal squamous cell carcinoma (ESCC).

Materials And Methods: A total of 372 patients with surgically and pathologically confirmed ESCC from 2 institutions were retrospectively included. All patients from institution 1 were randomized at a 7:3 ratio into a training cohort (n=206) and an internal validation cohort (n=88), and patients from institution 2 were used as an external validation cohort (n=78).

The predictive value of conventional MRI combined with radiomics in the immediate ablation rate of HIFU treatment for uterine fibroids.

Objective: This study aimed to assess the predictive value of conventional magnetic resonance imaging (MRI) combined with radiomics in determining the nonperfused volume ratio (NPVR) following high-intensity focused ultrasound (HIFU) ablation for uterine fibroids.

Methods And Materials: A total of 216 symptomatic uterine fibroids in 216 women were subjected to HIFU ablation from October 2015 to March 2020. Baseline clinical and MR parameters acquired before and after HIFU ablation were analyzed, and the NPVR was calculated accordingly.