Hybrid Approach to Classifying Histological Subtypes of Non-small Cell Lung Cancer (NSCLC): Combining Radiomics and Deep Learning Features from CT Images.

This study aimed to develop a hybrid model combining radiomics and deep learning features derived from computed tomography (CT) images to classify histological subtypes of non-small cell lung cancer (NSCLC). We analyzed CT images and radiomics features from 235 patients with NSCLC, including 110 with adenocarcinoma (ADC) and 112 with squamous cell carcinoma (SCC). The dataset was split into a training set (75%) and a test set (25%).

A device-dependent auto-segmentation method based on combined generalized and single-device datasets.

Background: Although generalized-dataset-based auto-segmentation models that consider various computed tomography (CT) scanners have shown great clinical potential, their application to medical images from unseen scanners remains challenging because of device-dependent image features.

Purpose: This study aims to investigate the performance of a device-dependent auto-segmentation model based on a combined dataset of a generalized dataset and single CT scanner dataset.

Method: We constructed two training datasets for 21 chest and abdominal organs.

Study of a plastic scintillating plate-based quality assurance system for pencil beam scanning proton beams.

Introduction: The purpose of this study was to evaluate a plastic scintillating plate-based beam monitoring system to perform quality assurance (QA) measurements in pencil beam scanning proton beam.

Methods: Single spots and scanned fields were measured with the high-resolution dosimetry system, consisting of a plastic scintillation plate coupled to a camera in a dark box at the isocenter. The measurements were taken at 110-190 MeV beam energies with 30° gantry angle intervals at each energy.

Synergistic effect of TTF and 5-FU combination treatment on pancreatic cancer cells.

The present study investigated the therapeutic potential of combining tumor-treating fields (TTF), a novel cancer treatment modality that employs low-intensity, alternating electric fields, with 5-fluorouracil (5-FU), a standard chemotherapy drug used for treating pancreatic cancer. The HPAF-II and Mia-Paca II pancreatic cancer cell lines were treated with TTF, 5-FU, or their combination. Combination treatment produced a significantly greater inhibitory effect on cancer cell proliferation than each single modality.

Study of multistep Dense U-Net-based automatic segmentation for head MRI scans.

Background: Despite extensive efforts to obtain accurate segmentation of magnetic resonance imaging (MRI) scans of a head, it remains challenging primarily due to variations in intensity distribution, which depend on the equipment and parameters used.

Purpose: The goal of this study is to evaluate the effectiveness of an automatic segmentation method for head MRI scans using a multistep Dense U-Net (MDU-Net) architecture.

Methods: The MDU-Net-based method comprises two steps.

Technical note: Evaluation of methods for reducing edge current density under electrode arrays for tumor-treating fields therapy.

Background: Tumor-treating fields (TTFields) therapy is increasingly utilized clinically because of its demonstrated efficacy in cancer treatment. However, the risk of skin burns must still be reduced to improve patient safety and posttreatment quality of life.

Purpose: The purpose of this study was to evaluate the methods of constructing electrode arrays that reduce current density exceeding threshold values, which can cause skin burns during TTFields therapy.

The combination of tumor treating fields and hyperthermia has synergistic therapeutic effects in glioblastoma cells by downregulating STAT3.

Glioblastoma multiforme (GBM), the most common type of brain tumor, is a very aggressive and treatment-refractory cancer, with a 5-year survival rate of approximately 5%. Hyperthermia (HT) and tumor treating fields (TTF) therapy have been used to treat cancer, either alone or in combination with other treatment methods. Both treatments have been reported to increase the efficacy of other treatment techniques and to improve patient prognosis.

Tumor treating fields (TTF) treatment enhances radiation-induced apoptosis in pancreatic cancer cells.

Purpose: Tumor treating fields (TTF) therapy is a noninvasive method that uses alternating electric fields to treat various types of cancer. This study demonstrates the combined effect of TTF and radiotherapy (RT) in vitro on pancreatic cancer, which is known to be difficult to treat.

Materials And Methods: In CFPAC-I and HPAF-II pancreatic cancer cell lines, the combined in vitro effect of TTF and RT was evaluated by measuring cell counts, markers of apoptosis, and clonogenic cell survival.