POSS Engineering of Multifunctional Nanoplatforms for Chemo-Mild Photothermal Synergistic Therapy.

Chemo-mild photothermal synergistic therapy can effectively inhibit tumor growth under mild hyperthermia, minimizing damage to nearby healthy tissues and skin while ensuring therapeutic efficacy. In this paper, we develop a multifunctional study based on polyhedral oligomeric sesquisiloxane (POSS) that exhibits a synergistic therapeutic effect through mild photothermal and chemotherapy treatments (POSS-SQ-DOX). The nanoplatform utilizes SQ-N as a photothermal agent (PTA) for mild photothermal, while doxorubicin (DOX) serves as the chemotherapeutic drug for chemotherapy.

A shortcut weighted fusion pyramid network for microcalcification detection in breast mammograms.

Background: High-precision detection for individual and clustered microcalcifications in mammograms is important for the early diagnosis of breast cancer. Large-scale differences between the two types and low-contrast images are major difficulties faced by radiologists when performing diagnoses.

Objective: Deep learning-based methods can provide end-to-end solutions for efficient detection.

Genomic Profiling and Response to Immune Checkpoint Inhibition plus Tyrosine Kinase Inhibition in FH-Deficient Renal Cell Carcinoma.

Background: FH-deficient renal cell carcinoma (RCC) is a rare and exceptionally aggressive RCC subtype. There is currently limited understanding of the molecular alterations, pathogenesis, survival outcomes, and systemic therapy efficacy for this cancer.

Objective: To perform a retrospective multicenter analysis of molecular profiling and clinical outcomes for patients with FH-deficient RCC, with an emphasis on treatment response to first-line immune checkpoint inhibitor plus tyrosine kinase inhibitor (ICI/TKI) versus bevacizumab plus erlotinib (Bev/Erlo) combination therapy in patients with advanced disease.

Using the apparent diffusion coefficient histogram analysis to predict response to neoadjuvant chemotherapy in patients with breast cancer: comparison among three region of interest selection methods.

Background: The apparent diffusion coefficient (ADC) value using histogram analysis is helpful to predict responses to neoadjuvant chemotherapy (NAC) in breast cancer. However, the measurement method has not reached a consensus. This study was to assess the diagnostic performance of the ADC histogram analysis at predicting patient response prior to NAC in breast cancer patients using different region of interest (ROI) selection methods.

The predictive value of DKI in breast cancer: Does tumour subtype affect pathological response evaluations?

Purpose: To explore the differences in quantitative parameters based on diffusion weighted imaging (DWI) and diffusion kurtosis imaging (DKI) between different immunohistochemical indicator statuses and their predictive value for neoadjuvant chemotherapy (NAC) among different phenotypes of breast cancer.

Methods: Eighty-one breast cancer patients who underwent NAC were enrolled in this retrospective study. Correlations between diffusion parameters and immunohistochemical indicators were determined using Spearman's test, and receiver operating characteristic (ROC) curves were constructed to assess the apparent diffusion coefficient (ADC), mean diffusivity (MD), and mean kurtosis (MK) in predicting the pathologic complete response (PCR).

Diffusion-weighted MRI for predicting pathologic response to neoadjuvant chemotherapy in breast cancer: evaluation with mono-, bi-, and stretched-exponential models.

Background: To investigate the performance of diffusion-weighted (DW) MRI with mono-, bi- and stretched-exponential models in predicting pathologic complete response (pCR) to neoadjuvant chemotherapy (NACT) for breast cancer, and further outline a predictive model of pCR combining DW MRI parameters, contrast-enhanced (CE) MRI findings, and/or clinical-pathologic variables.

Methods: In this retrospective study, 144 women who underwent NACT and subsequently received surgery for invasive breast cancer were included. Breast MRI including multi-b-value DW imaging was performed before (pre-treatment), after two cycles (mid-treatment), and after all four cycles (post-treatment) of NACT.

Dual Energy Spectral CT Imaging for Colorectal Cancer Grading: A Preliminary Study.

Objectives: To assess the diagnostic value of dual energy spectral CT imaging for colorectal cancer grading using the quantitative iodine density measurements in both arterial phase (AP) and venous phase (VP).

Methods: 81 colorectal cancer patients were divided into two groups based on their pathological findings: a low grade group including well (n = 13) and moderately differentiated cancer (n = 24), and a high grade group including poorly differentiated (n = 42) and signet ring cell cancer (n = 2). Iodine density (ID) in the lesions was derived from the iodine-based material decomposition (MD) image and normalized to that in the psoas muscle to obtain normalized iodine density (NID).

Characterization of breast masses as benign or malignant at 3.0T MRI with whole-lesion histogram analysis of the apparent diffusion coefficient.

Purpose: To investigate the utility of whole-lesion apparent diffusion coefficient (ADC) histogram analysis in capturing breast lesion heterogeneity and determine which ADC metric may help best differentiate benign from malignant breast mass lesions at 3.0T magnetic resonance imaging (MRI).

Materials And Methods: We retrospectively included 101 women with breast mass lesions (benign:malignant = 36:65) who underwent 3.