Thoracic Surgery

The Impact of AI on Eye Gaze Patterns in Chest X-Ray Interpretation: An Eye Tracking Study of Novice and Expert Radiologists.

PURPOSE: To investigate how artificial intelligence-assisted chest radiograph interpretation influences eye gaze patterns in novice and expert radiologists. MATERIALS AND METHODS: This prospective eye tracking study included 6 novice radiology residents and 6 expert cardiothoracic radiologists. Fifty anonymized posteroanterior chest radiographs were interpreted under 3 conditions: Before AI, With ...

Clinical evaluation of a motion correction software based on partial angle reconstruction in coronary CT angiography.

To evaluate a new deep learning (DL) motion correction (MC) software based on partial angle reconstruction (PAR) to reduce motion artifacts in patients with increased heart rate (HR) in coronary CT angiography (CCTA). This retrospective single-center study included consecutive patients with HR > 70 bpm who underwent single-beat wide-area-detector CCTA over a 6-month period. A DL PAR-based MC softw...

Association of Artificial Intelligence Derived Cardiothoracic Ratio Assessment on Non-Cardiac Chest CT with Heart Failure and All-Cause Mortality: A Retrospective Single Center Study.

BACKGROUND: The cardiothoracic ratio (CTR) is estimated by dividing cardiac width by thoracic width. The Area Deprivation Index (ADI) is a metric to q...

Exploration of Different Machine Learning Methods and Domains of Predictors for Chronic Postsurgical Pain After Video-Assisted Thoracoscopic Surgery.

OBJECTIVES: Chronic postsurgical pain (CPSP) is a significant burden affecting ∼30% of patients after video-assisted thoracoscopic surgery (VATS). The...

Preface for Symposium on Artificial Intelligence in Cardiothoracic Imaging.

Comparable survival after lobectomy and total thyroidectomy for T3b differentiated thyroid carcinoma: A population-based study.

BACKGROUND: The 2025 American Thyroid Association guidelines recommend total thyroidectomy for all T3b differentiated thyroid carcinoma (DTC). However...

Objective assessment of surgical skill using artificial intelligence hand tracking in cardiothoracic training: A feasibility study.

OBJECTIVES: Measuring surgical competency is essential for surgical residents to ensure patient safety. Traditional assessment tools, rely on subjecti...

LungSurg: A Generative AI System for Segmentation and Phase Classification in Thoracoscopic Lobectomy.

The integration of artificial intelligence (AI) into surgical practices is advancing towards greater intelligence and precision. This study assesses t...

Development and Validation of an Artificial Intelligence Surgical Video Analysis Model for Predicting Visceral Pleural Invasion in Lung Cancer Surgery: A Multicenter Study.

BACKGROUND: Intraoperative diagnosis of visceral pleural invasion (VPI) during video-assisted thoracoscopic surgery (VATS) remains challenging. This s...

Artificial intelligence-based prediction of cardiothoracic intensive care unit length of stay: A comparative machine learning approach.

BACKGROUND: Predicting prolonged intensive care unit (ICU) length of stay (LOS) remains challenging, and traditional statistical models often fail to ...

Artificial intelligence in cardiothoracic monitoring and echocardiography.

PURPOSE OF REVIEW: This review describes the recent advancements of artificial intelligence (AI) in cardiothoracic anesthesia monitoring. RECENT FINDI...

Noninvasive follicular thyroid neoplasm with papillary-like nuclear features: an update.

PURPOSE OF REVIEW: Noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) has been recognized as a diagnostic entity sin...

Utility of multimodal deep learning model to diagnose lymph node metastasis in esophageal cancer using computed tomography and positron emission tomography images.

PURPOSE: This study aimed to assess the performance of a deep learning model using multimodal imaging for detecting lymph node metastasis in esophagea...

Interpretable artificial intelligence to predict preoperative risk factors for failure to rescue after coronary artery bypass grafting.

OBJECTIVE: Failure to rescue (FTR) is a significant quality indicator for postoperative cardiothoracic care. We developed an interpretable artificial ...

Surgeon Perception of Artificial Intelligence in Thoracic Surgery: Insights From an International Survey.

BACKGROUND: The use of artificial intelligence (AI) in medicine has increased dramatically. Its use will expand in cardiothoracic (CT) surgery and alt...

Evaluation of AI-based detection of incidental pulmonary emboli in cardiac CT angiography scans.

Incidental pulmonary embolism (PE) is detected in 1% of cardiac CT angiography (CCTA) scans, despite the targeted aortic opacification and limited fie...

Impact of Artificial Intelligence on the Timing of Recurrent Laryngeal Nerve Recognition during Robot-Assisted Minimally Invasive Esophagectomy.

BACKGROUND: As a first step to prevent recurrent laryngeal nerve (RLN) palsy, we have developed an artificial intelligence (AI)-based anatomical recog...

Real-time AI-based detection of excessive traction on the recurrent laryngeal nerve during robotic-assisted minimally invasive esophagectomy: a proof-of-concept study.

Recurrent laryngeal nerve (RLN) palsy often occurs due to excessive traction (ET) on the nerve during esophagectomy. Use of a nerve integrity monitor ...

The Year in Graduate Medical Education: Selected Highlights from 2024.

This special article is the fourth in an annual series for the Journal of Cardiothoracic and Vascular Anesthesia that highlights significant literatur...

Role of VATS-US in identifying and characterizing pulmonary nodules: a narrative review.

The aim of this study was to show the efficacy described in the scientific literature of lung ultrasound (LU) during video-assisted thoracic surgery (...