Screening Candidates for Conversion Therapy in Unresectable Hepatocellular Carcinoma Patients After Tyrosine Kinase Inhibitor Plus PD-1/PD-L1 Antibody Therapy: A Multicenter Retrospective Study.

Background: Conversion therapies after immune checkpoint inhibitors (ICIs) plus tyrosine-kinase inhibitors (TKIs) provide curative surgery chance and prolong survival for unresectable hepatocellular carcinoma (uHCC). However, only some patients have the opportunity to receive conversion therapies. To this end, we aimed to develop and validate a machine-learning model to identify patients who may have the chance to undergo conversion therapy.

Use of virtual simulation-based training platform on thyroid ultrasonography in medical students: a randomized controlled trial.

Rationale And Objectives: To compare the VR simulation to the traditional teaching method on thyroid ultrasound training for medical students.

Materials And Methods: A total of 106 medical students who had finished basic medical courses were recruited and randomly assigned to the VR group and control group. All participants received 2 theoretical lessons, followed by a practical class.

Imaging hypoxia for head and neck cancer: current status, challenges, and prospects.

Hypoxia can substantially impact clinical outcomes in patients with head and neck cancer (HNC) by promoting tumor invasion, metastasis, immune escape, and therapy resistance. Given the growing interest in targeting hypoxia for cancer therapy, noninvasive methods are needed to accurately detect hypoxia and evaluate the tumor response to treatment. This review summarizes recent advances in hypoxia-targeted probes and imaging techniques, emphasizing their imaging mechanisms, strengths, and limitations.

Artificial intelligence-augmented ultrasound diagnosis of follicular-patterned thyroid neoplasms: a multicenter retrospective study.

Background: Conventional diagnostic tools, including ultrasound, fine-needle aspiration cytology, and intraoperative frozen section pathology, may fail to reliably distinguish between benign and malignant FNs, leading to unnecessary or inadequate surgical interventions. We aimed to develop and validate a deep learning (DL) system for the preoperative diagnosis of follicular-patterned thyroid neoplasms (FNs) using routine ultrasound images, with the goal of improving diagnostic accuracy and reducing unnecessary procedures.

Methods: In this multicenter, retrospective study, we included 3817 patients (2877 [75.

Noninvasive Deep Learning System for Preoperative Diagnosis of Follicular-Like Thyroid Neoplasms Using Ultrasound Images: A Multicenter, Retrospective Study.

Objective: To propose a deep learning (DL) system for the preoperative diagnosis of follicular-like thyroid neoplasms (FNs) using routine ultrasound images.

Summary Background Data: Preoperative diagnosis of malignancy in nodules suspicious for an FN remains challenging. Ultrasound, fine-needle aspiration cytology, and intraoperative frozen section pathology cannot unambiguously distinguish between benign and malignant FNs, leading to unnecessary biopsies and operations in benign nodules.

Evaluation of the ultrasonic arterial measurement and analysis system for predicting 10-year atherosclerotic cardiovascular disease risk in patients with type 2 diabetes.

Background: Cardiovascular disease is a leading cause of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM). Carotid-femoral pulse wave velocity (cfPWV), a reliable indicator of arterial stiffness, predicts cardiovascular events. The arterial stiffness automated measurement system (AMAS) streamlines the measurement of cfPWV, potentially increasing its clinical utility.

Radiomic Model Associated with Tumor Microenvironment Predicts Immunotherapy Response and Prognosis in Patients with Locoregionally Advanced Nasopharyngeal Carcinoma.

No robust biomarkers have been identified to predict the efficacy of programmed cell death protein 1 (PD-1) inhibitors in patients with locoregionally advanced nasopharyngeal carcinoma (LANPC). We aimed to develop radiomic models using pre-immunotherapy MRI to predict the response to PD-1 inhibitors and the patient prognosis. This study included 246 LANPC patients (training cohort, = 117; external test cohort, = 129) from 10 centers.

Artificial Intelligence Can Predict Personalized Immunotherapy Outcomes in Cancer.

The rapid advancement of artificial intelligence (AI) technologies has opened new avenues for advancing personalized immunotherapy in cancer treatment. This review highlights current research progress in applying AI to optimize the use of immunotherapy for patients with cancer. Recent studies demonstrate that AI models can accurately diagnose cancers and discover biomarkers by integrating multi-omics and imaging data, establish predictive models to estimate treatment responses and adverse reactions, formulate personalized treatment plans integrating multiple modalities by considering various factors, and achieve precise patient stratification and clinical trial matching, thereby addressing specific obstacles throughout processes from diagnosis to treatment in personalized immunotherapy.

RhTSH in aiding dynamic assessment in patients with differentiated thyroid Cancer.

Purpose: To evaluate the efficacy of a novel recombinant human thyroid-stimulating hormone (ZGrhTSH) as an alternative to thyroid hormone withdrawal (THW) in dynamic assessment of DTC patients.

Methods: This phase 3, open-label, multicenter trial, conducted across 27 sites in China, employed a self-controlled design to enroll patients. Eligible patients had previously undergone total or near-total thyroidectomy, with or without RAI therapy.

Transformer-based skeletal muscle deep-learning model for survival prediction in gastric cancer patients after curative resection.

Background: We developed and evaluated a skeletal muscle deep-learning (SMDL) model using skeletal muscle computed tomography (CT) imaging to predict the survival of patients with gastric cancer (GC).

Methods: This multicenter retrospective study included patients who underwent curative resection of GC between April 2008 and December 2020. Preoperative CT images at the third lumbar vertebra were used to develop a Transformer-based SMDL model for predicting recurrence-free survival (RFS) and disease-specific survival (DSS).

Grading magnetic resonance imaging signs for diagnosing invasive placenta accreta spectrum disorders.

Introduction: Placenta accreta spectrum (PAS) disorders result from abnormal placental attachment, leading to varying degrees of myometrial invasion. Magnetic resonance imaging (MRI) plays a crucial role in assessing the depth and extent of placental invasion. This study aims to evaluate the correlation between quantified MRI findings and the diagnosis of PAS, as classified according to the FIGO system.

Letter to the editor: radiomics signature for dynamic monitoring of tumor-inflamed microenvironment and immunotherapy response prediction.

We read with great interest the article by Bernatowicz Despite the promising findings, we would like to highlight several concerns regarding the methodology and interpretation of the results that warrant further discussion, including the stability of radiomic features across pan-cancer types, the optimal threshold for CT-TIME (tumor immune microenvironment) scores, the biological interpretability of radiomic models, and the survival tail effect of immunotherapy responses.

Insights into Q-marker of Shensong Yangxin capsule in treating cardiac arrhythmias based on a linear substitution strategy in quantification of multiple components.

Background: The concept of a Quality marker (Q-marker) has emerged as a crucial tool for ensuring the safety and efficacy of Traditional Chinese Medicine (TCM) formulas. However, significant challenges remained in the identification and practical application of Q-marker, particularly due to the scarcity of reference standards.

Purpose: This study aimed to achieve a multidimensional integration of chemical profiling, target tissue distribution and in vivo high-throughput screening model to effectively identify the Q-marker of Shensong Yangxin Capsule (SSYX) and propose a linear substitution strategy for the quantification of multiple components.

Dexmedetomidine therapy promotes cardiac dysfunction and increases mortality in sepsis: A translational study.

Previous studies demonstrated that dexmedetomidine (Dex) posttreatment aggravated myocardial dysfunction and reduced survival in septic mice. Yet, whether Dex elicits similar effects in septic patients as defined by Sepsis-3 remains unknown. This study sought to assess the effects of Dex-based sedation on mortality and cardiac dysfunction in septic patients defined by Sepsis-3 and to further reveal the mechanisms in septic rats.

Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) combined with conventional MRI for the detection of skull-base invasion in nasopharyngeal carcinoma: comparison with F-sodium fluoride (F-NaF) positron emission tomography/computed tomography (PET/CT).

Background: The extent of skull base invasion (SBI) in nasopharyngeal carcinoma (NPC) directly impacts tumor staging, treatment strategies, and prognosis assessment for NPC patients, emphasizing the critical need for prompt diagnosis and precise assessment of invasion. Thus, we aimed to integrate the advantages of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and conventional magnetic resonance imaging (cMRI), and assess their combined diagnostic efficacy versus that of F-sodium fluoride (F-NaF) positron emission tomography/computed tomography (PET/CT) for detecting SBI in NPC patients.

Methods: The study prospectively and randomly recruited 62 patients newly diagnosed with NPC by pathological biopsy at the Cancer Center of Affiliated Hospital of Guangdong Medical University from January 2021 to September 2022.

Radiogenomics: bridging the gap between imaging and genomics for precision oncology.

Genomics allows the tracing of origin and evolution of cancer at molecular scale and underpin modern cancer diagnosis and treatment systems. Yet, molecular biomarker-guided clinical decision-making encounters major challenges in the realm of individualized medicine, consisting of the invasiveness of procedures and the sampling errors due to high tumor heterogeneity. By contrast, medical imaging enables noninvasive and global characterization of tumors at a low cost.

A hypoxia-derived gene signature to suggest cisplatin-based therapeutic responses in patients with cervical cancer.

Cervical cancer remains a significant global public health concern, often exhibits cisplatin resistance in clinical settings. Hypoxia, a characteristic of cervical cancer, substantially contributes to cisplatin resistance. To evaluate the therapeutic efficacy of cisplatin in patients with cervical cancer and to identify potential effective drugs against cisplatin resistance, we established a hypoxia-inducible factor-1 (HIF-1)-related risk score (HRRS) model using clinical data from patients treated with cisplatin.