Glymphatic, Structural, and Cognitive Changes During Breast Cancer Chemotherapy: A Longitudinal MRI Study.

The glymphatic system maintains brain homeostasis through cerebrospinal fluid transport and waste clearance. Its potential involvement in chemotherapy-related cognitive impairment remains largely unexplored due to limited in vivo evidence. In this prospective longitudinal study, 126 female breast cancer patients underwent multiparametric brain MRI and neuropsychological assessments at three time points: baseline (bc1), after the first cycle of neoadjuvant chemotherapy (bc2), and upon completion of neoadjuvant chemotherapy (bc3).

CT derived myocardial extracellular volume predict major adverse cardiovascular events in patients with prostate cancer.

Background: Prostate cancer (PCa) patients with androgen deprivation therapy (ADT) are at high risk for cardiotoxicity and major adverse cardiovascular events (MACE). It is unclear whether the myocardial extracellular volume (ECV) derived from chest contrast-enhanced CT (CECT) can detect cardiotoxicity and predict MACE in these patients. This work aimed to assess the value of chest CECT derived myocardial ECV for detecting cardiotoxicity and the association of ECV with MACE in PCa patients receiving ADT.

Habitat imaging based on dual-energy computed tomography for predicting axillary lymph node metastasis in breast cancer.

BackgroundQuantitative analysis with habitat clustering represents an innovative, non-invasive approach to quantify tumor heterogeneity.PurposeTo characterize intratumoral spatial heterogeneity using dual-energy computed tomography (DECT) in breast cancer patients and investigate the performance of habitat imaging in predicting axillary lymph node (ALN) metastasis compared with radiomics.Material and MethodsA total of 135 patients were randomly assigned to a training group (n = 95) and a testing group (n = 40).

Differentiating Benign Thyroid Nodules and Papillary Thyroid Carcinoma Using Time-Dependent Diffusion MRI: A Feasibility Study.

Background: Differentiating benign and malignant thyroid nodules is important for treatment planning and prognostic, yet an ideal method is lacking.

Purpose: To investigate whether microstructural parameters from time-dependent diffusion MRI (td-dMRI) can accurately distinguish between benign and malignant thyroid nodules.

Study Type: Single-center, prospective.

Time-Dependent Diffusion MRI-Based Microstructural Mapping for Characterizing HER2-Zero, -Low, -Ultra-Low, and -Positive Breast Cancer.

Background: With breast cancer treatment advances, accurate non-invasive methods are needed to distinguish its human epidermal growth factor receptor 2 (HER2) subtypes. Recently developed time-dependent diffusion MRI (t-dMRI) has potential in characterizing cellular tissue microstructures in breast cancer. However, its role in identifying HER2 subtypes is unknown.

The value of a radiomics model in predicting ovarian malignancy: a retrospective multi-center comparison with O-RADS and radiologists.

Objectives: To develop an MRI-based radiomics model for ovarian masses categorization and to compare the model performance to Ovarian-Adnexal Reporting and Data System (O-RADS) and radiologists' assessments.

Materials And Methods: This retrospective multicenter study included 497 patients (249 benign, 248 malignant) allocated to training, internal, and external validation sets (293/124/80 masses, respectively). Radiomics features were extracted from preoperative MRI.

Comparing Multi-Value Diffusion MRI Models for Predicting Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.

Background Multi-value diffusion MRI models have been used to predict pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) for breast cancer. However, there is a lack of longitudinal comparative research. Purpose To compare the performance of various diffusion MRI-derived longitudinal parameters during NAC for prediction of pCR in breast cancer.

Prediction of induction chemotherapy response in locoregionally advanced nasopharyngeal carcinoma based on three pretreatment non-Gaussian diffusion MRI models.

Objectives: To explore the value of continuous-time random walk (CTRW), fractional order calculus (FROC), and stretched exponential model (SEM) in predicting for response to induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC).

Methods: This prospective study included the NPC participants (n = 79) who underwent non-Gaussian (CTRW, FROC, and SEM) model from December 2023 to October 2024. Eight diffusion parameters, namely α, β, Dm, β, µ, D, α, and DDC of the primary tumor, were derived from three diffusion models before treatment.

CT-based radiomics models for predicting spread through air space in lung cancer: A systematic review and meta-analysis.

Rationale And Objectives: Numerous studies have developed and validated models to predict spread through air space (STAS) in lung cancer using preoperative computed tomography (CT), yielding inconsistent results. We aimed to estimate the diagnostic accuracy of CT-based radiomics for predicting spread through air space (STAS) for preoperative prediction of lung cancer.

Materials And Methods: Original studies published prior to January 2024 were searched in various databases.

Comprehensive characterization of tumor therapeutic response via simultaneous mapping of cell size, density, and transcytolemmal water exchange.

The evaluation of tumor response to neoadjuvant chemotherapy is critical for the personalized management of cancer patients, aiming to minimize unnecessary toxicity, costs, and treatment delays. Current imaging techniques primarily depend on detecting tumor volume changes, which reflect downstream effects. In contrast, advanced microstructural diffusion MRI (dMRI) methods offer cellular-level insights but are limited by biased estimates of cell density due to oversimplified biophysical models.

Quantifying tumor morphological complexity based on pretreatment MRI fractal analysis for predicting pathologic complete response and survival in breast cancer: a retrospective, multicenter study.

Background: The tumor morphological complexity is closely associated with treatment response and prognosis in patients with breast cancer. However, conveniently quantifiable tumor morphological complexity methods are currently lacking.

Methods: Women with breast cancer who underwent NAC and pretreatment MRI were retrospectively enrolled at four centers from May 2010 to April 2023.

Biomechanical parameters quantified by MR elastography for predicting response to neoadjuvant chemotherapy and disease-free survival in breast cancer: a prospective longitudinal study.

Background: Little is known regarding biomechanical properties derived from multifrequency MR elastography temporal changes during neoadjuvant chemotherapy (NAC) and associated with pathologic complete response (pCR) and disease-free survival (DFS) in breast cancer. We aimed to investigate temporal changes in NAC-associated biomechanical parameters and assess biomechanical parameters as a predictor of pCR and DFS in breast cancer.

Methods: In this prospective longitudinal study, participants with breast cancer who received NAC were enrolled from February 2021 to May 2023.

Predicting lymphovascular invasion in stage IA lung adenocarcinoma: a CT-based classification and regression tree model.

Background: Lymphovascular invasion (LVI) is a significant histopathological marker associated with poor prognosis in patients. However, there is a notable lack of reliable, non-invasive preoperative tools to predict LVI accurately.

Purpose: To develop and validate a computed tomography (CT)-based classification and regression tree (CART) model for the preoperative prediction of LVI in patients with clinical stage IA lung adenocarcinoma (LUAD).

Automatic Segmentation and Molecular Subtype Classification of Breast Cancer Using an MRI-based Deep Learning Framework.

Purpose To build a deep learning framework using contrast-enhanced MRI for lesion segmentation and automatic molecular subtype classification in breast cancer. Materials and Methods This retrospective multicenter study included patients with biopsy-proven invasive breast cancer between January 2015 and January 2021. An automatic breast lesion segmentation model was developed using three-dimensional (3D) ResU-Net as the backbone, and its accuracy was evaluated in an internal and two external testing datasets using the Dice score.

Nomogram for Predicting Neoadjuvant Chemotherapy Response in Breast Cancer Using MRI-based Intratumoral Heterogeneity Quantification.

Background Intratumoral heterogeneity (ITH) in breast cancer contributes to treatment failure and relapse. Noninvasive methods to quantify ITH are currently limited. Purpose To quantify ITH in breast cancer using pretreatment MRI, develop a nomogram to predict pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) and recurrence-free survival (RFS), and investigate biologic pathways associated with nomogram scores.

Altered Brain Functional Networks in Patients With Breast Cancer After Different Cycles of Neoadjuvant Chemotherapy.

Background: Cancer-related cognitive impairment (CRCI) impacts breast cancer (BC) patients' quality of life after chemotherapy. While recent studies have explored its neural correlates, single time-point designs cannot capture how these changes evolve over time.

Purpose: To investigate changes in the brain connectome of BC patients at several time points during neoadjuvant chemotherapy (NAC).

Nomograms Integrating MRI-derived Apparent Diffusion Coefficient and Clinicopathologic Features for Prediction of Axillary Lymph Node Metastasis in Breast Cancer.

Purpose To develop three nomograms integrating apparent diffusion coefficients (ADCs) derived from diffusion-weighted imaging to predict the status of pretreatment axillary lymph nodes (ALNs) (task 1), nonsentinel lymph nodes (task 2), and ALNs after neoadjuvant chemotherapy treatment (task 3) in patients with breast cancer. Materials and Methods Pretreatment MRI scans, including diffusion-weighted images, were retrospectively acquired from patients with breast cancer at multiple centers from May 2019 to May 2023. ADC values and clinicopathologic features were measured.

Evaluation of induction chemotherapy response using multiphasic dual-energy CT in nasopharyngeal carcinoma.

Objectives: To develop a nomogram that assists in selecting nasopharyngeal carcinoma (NPC) patients suitable for induction chemotherapy.

Materials And Methods: This retrospective study included NPC patients who underwent multiphasic contrast‑enhanced DECT (comprising non-contrast, arterial, and venous phase scanning) between May 2019 and December 2023. The relationships between quantitative DECT-derived parameters and treatment response to induction chemotherapy were analyzed using logistic regression analysis.

Nomogram based on dual-energy computed tomography to predict the response to induction chemotherapy in patients with nasopharyngeal carcinoma: a two-center study.

Background: Previous studies utilizing dual-energy CT (DECT) for evaluating treatment efficacy in nasopharyngeal cancinoma (NPC) are limited. This study aimed to investigate whether the parameters from DECT can predict the response to induction chemotherapy in NPC patients in two centers.

Methods: This two-center retrospective study included patients diagnosed with NPC who underwent contrast-enhanced DECT between March 2019 and November 2023.

CT-based intratumoral and peritumoral radiomics nomogram to predict spread through air spaces in lung adenocarcinoma with diameter ≤ 3 cm: A multicenter study.

Purpose: The aim of this study was to explore and develop a preoperative and noninvasive model for predicting spread through air spaces (STAS) status in lung adenocarcinoma (LUAD) with diameter ≤ 3 cm.

Methods: This multicenter retrospective study included 640 LUAD patients. Center I included 525 patients (368 in the training cohort and 157 in the validation cohort); center II included 115 patients (the test cohort).

Structural and functional connectivity coupling as an imaging marker for bone metastasis pain in lung cancer patients.

Background: Cancer pain is a common symptom in patients with malignant tumors and associated with poor prognosis and a high risk of death. Structural connectivity (SC) and functional connectivity (FC) couplings have not yet been explored in lung cancer patients with bone metastasis pain.

Methods: In total, 51 patients with lung cancer without bone metastasis pain (BMP-), 52 patients with lung cancer with bone metastasis pain (BMP+), and 28 healthy controls (HC) were prospectively enrolled in our study.

Left ventricular trabecular complexity for risk stratification of cancer therapy-related cardiac dysfunction in breast cancer.

The left ventricular trabecular fractal dimension (LVTFD) derived from cardiac magnetic resonance reflects myocardial trabecular complexity, which is associated with cardiovascular disease risk. Baseline risk stratification of cancer therapy-related cardiac dysfunction (CTRCD) in patients with breast cancer who received anthracycline is a very important clinical issue. In this study, we used the Cox model to derive and validate a new score system based on LVTFD for baseline risk stratification of CTRCD in breast cancer patients receiving anthracycline.

Assessment of Prostate MR Image and Predictive Value for Benign Prostate Disease among Different DWI Sequences.

Background: Early diagnosis of prostate cancer can improve the survival rate of patients on the premise of high-quality images. The prerequisite for early diagnosis is high-quality images. ZOOMit is a method for high-resolution, zoomed FOV imaging, allowing diffusion-weighted images with high contrast and resolution in short acquisition times.

Coronary computed tomography angiography for assessing the coronary artery and predicting adverse cardiovascular events in patients with thoracic malignancies.

Background: It is unclear whether the parameters derived from coronary computed tomography angiography (CCTA) can identify the impairments of coronary arteries and if they are associated with major adverse cardiovascular events (MACEs) in patients with thoracic malignancies receiving chemotherapy or chemoradiotherapy. This study aimed to investigate the longitudinal changes in coronary arteries using CCTA and to determine their association with MACEs in patients with thoracic malignancies receiving chemotherapy or chemoradiotherapy.

Methods: This cross-sectional study included consecutive patients with thoracic malignancies who received chemotherapy or chemoradiotherapy and who underwent CCTA between June 2013 and May 2019 at Chongqing University Cancer Hospital.