Lung Cancer

Off-Clamp Robot-Assisted Partial Nephrectomy: Is There Something More to Achieve Optimal Trifecta Outcomes?

To report trifecta outcomes of our "off-clamp" partial nephrectomy (PN) patients operated without main renal artery and/or any selective/superselective clamping. Between April 2008 and March 2020, 52 patients received "off-clamp" robot-assisted partial nephrectomy. Postoperative sixth month estimated glomerular filtration rate (eGFR) and eGFR decrease were considered for renal function evaluatio...

Laparoscopic cryoablation for small renal masses: Oncological outcomes at 5-year follow-up.

: To evaluate the oncological outcome at 5-year follow-up after laparoscopic cryoablation (LCA) for small renal masses (SRMs), as there is an increasing interest in ablative therapy for cT1a renal tumours due to the rising incidence of SRMs, the trend towards minimally invasive nephron-sparing treatments, and the ageing population. : Between 2004 and 2015, 233 consecutive LCA were performed in 219...

Perceptions of Canadian radiation oncologists, radiation physicists, radiation therapists and radiation trainees about the impact of artificial intelligence in radiation oncology - national survey.

BACKGROUND: Artificial Intelligence (AI) is making a continuous progression into the field of Radiation Oncology in Canada and globally. While this fi...

Weight-bearing CT in foot and ankle pathology.

Cone-beam scanners (CBCT) enable CT to be performed under weight-bearing - notably for the foot and ankle. The technology is not new: it has been used...

3D deep learning based classification of pulmonary ground glass opacity nodules with automatic segmentation.

Classifying ground-glass lung nodules (GGNs) into atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcin...

Predicting potential residues associated with lung cancer using deep neural network.

Lung cancer is a prominent type of cancer, which leads to high mortality rate worldwide. The major lung cancers lung adenocarcinoma (LUAD) and lung sq...

Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images.

Histopathological images are a rich but incompletely explored data type for studying cancer. Manual inspection is time consuming, making it challengin...

Immune profile of the tumor microenvironment and the identification of a four-gene signature for lung adenocarcinoma.

The composition and relative abundances of immune cells in the tumor microenvironment are key factors affecting the progression of lung adenocarcinoma...

Impacts of speciation and extinction measured by an evolutionary decay clock.

The hypothesis that destructive mass extinctions enable creative evolutionary radiations (creative destruction) is central to classic concepts of macr...

Leveraging multi-way interactions for systematic prediction of pre-clinical drug combination effects.

We present comboFM, a machine learning framework for predicting the responses of drug combinations in pre-clinical studies, such as those based on cel...

Development and Validation of a Machine Learning Model to Explore Tyrosine Kinase Inhibitor Response in Patients With Stage IV EGFR Variant-Positive Non-Small Cell Lung Cancer.

IMPORTANCE: An end-to-end efficacy evaluation approach for identifying progression risk after epidermal growth factor receptor (EGFR)-tyrosine kinase ...

Retinal Capillary Nonperfusion on OCT-Angiography and Its Relationship to Kidney Function in Patients with Diabetes.

BACKGROUND: Diabetic retinopathy and kidney disease share underlying mechanisms of microvascular damage and are often comorbid in people with diabetes...

Predicting spatial esophageal changes in a multimodal longitudinal imaging study via a convolutional recurrent neural network.

Acute esophagitis (AE) occurs among a significant number of patients with locally advanced lung cancer treated with radiotherapy. Early prediction of ...

Risk factors and socio-economic burden in pancreatic ductal adenocarcinoma operation: a machine learning based analysis.

BACKGROUND: Surgical resection is the major way to cure pancreatic ductal adenocarcinoma (PDAC). However, this operation is complex, and the peri-oper...

Artificial intelligence in image reconstruction: The change is here.

Innovations in CT have been impressive among imaging and medical technologies in both the hardware and software domain. The range and speed of CT scan...

Safety and effectiveness of ipragliflozin in Japanese patients with type 2 diabetes mellitus and impaired renal function: subgroup analysis of a 3-year post-marketing surveillance study (STELLA-LONG TERM).

STELLA-LONG TERM, a 3-year post-marketing surveillance study, evaluated the safety and effectiveness of the sodium-glucose cotransporter 2 inhibitor i...

Renal function in children infected with : a case-control study of an endemic Ghanaian community.

Schistosomiasis has been associated with kidney diseases leading to serious health problems especially in advanced cases. Most studies have used renal...

Improving Image Quality and Reducing Radiation Dose for Pediatric CT by Using Deep Learning Reconstruction.

Background CT deep learning reconstruction (DLR) algorithms have been developed to remove image noise. How the DLR affects image quality and radiation...

Dose-dependent effects of ultrasound therapy on hepatocellular carcinoma.

Non-invasive ischemic cancer therapy requires reduced blood flow whereas drug delivery and radiation therapy require increased tumor perfusion for a b...

Using Auto-Segmentation to Reduce Contouring and Dose Inconsistency in Clinical Trials: The Simulated Impact on RTOG 0617.

PURPOSE: Contouring inconsistencies are known but understudied in clinical radiation therapy trials. We applied auto-contouring to the Radiation Thera...