AIMC Topic: Breath Holding

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Intra- and inter-field strength reproducibility of deep-learning based real-time cardiac MRI cine sequences with breath hold and in free breathing.

Scientific reports Oct 29, 2025
To assess intra- and inter-field strength reproducibility of volumetric parameters using deep-learning-based real-time cardiac cine MRI during breath-hold (BH) and free-breathing (FB). In this prospective single-center study, 56 healthy adults underw...
Female Reproducibility of Results Young Adult Adult Humans Heart Prospective Studies Heart Ventricles Male Respiration Stroke Volume Breath Holding Middle Aged Magnetic Resonance Imaging, Cine Deep Learning
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Optimized deep learning-accelerated single-breath-hold abdominal HASTE with and without fat saturation improves and accelerates abdominal imaging at 3 Tesla.

BMC medical imaging Sep 18, 2025
BACKGROUND: Deep learning-accelerated single-shot turbo-spin-echo techniques (DL-HASTE) enable single-breath-hold T2-weighted abdominal imaging. However, studies evaluating the image quality of DL-HASTE with and without fat saturation (FS) remain lim...
Image Interpretation, Computer-Assisted Breath Holding Adult Abdomen Humans Prospective Studies Magnetic Resonance Imaging Male Female Feasibility Studies Middle Aged Aged Healthy Volunteers Deep Learning Young Adult
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Data-efficient generalization of AI transformers for noise reduction in ultra-fast lung PET scans.

European journal of nuclear medicine and molecular imaging Feb 26, 2025
PURPOSE: Respiratory motion during PET acquisition may produce lesion blurring. Ultra-fast 20-second breath-hold (U2BH) PET reduces respiratory motion artifacts, but the shortened scanning time increases statistical noise and may affect diagnostic qu...
Time Factors Image Processing, Computer-Assisted Positron Emission Tomography Computed Tomography Positron-Emission Tomography Humans Lung Deep Learning Artifacts Signal-To-Noise Ratio Breath Holding
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Machine learning model for predicting DIBH non-eligibility in left-sided breast cancer radiotherapy: Development, validation and clinical impact analysis.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Jan 31, 2025
OBJECTIVE: Multi-day assessments accurately identify patients with left-sided breast cancer who are ineligible for irradiation in Deep Inspiration Breath Hold (DIBH) and minimise on-couch treatment time in those who are eligible. The challenge of imp...
Algorithms Prospective Studies Female Aged Breast Neoplasms Middle Aged Breath Holding Unilateral Breast Neoplasms Humans Machine Learning
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Development of a machine learning tool to predict deep inspiration breath hold requirement for locoregional right-sided breast radiation therapy patients.

Biomedical physics & engineering express Jan 22, 2025
. This study presents machine learning (ML) models that predict if deep inspiration breath hold (DIBH) is needed based on lung dose in right-sided breast cancer patients during the initial computed tomography (CT) appointment.. Anatomic distances wer...
Logistic Models Radiotherapy Planning, Computer-Assisted Inhalation Breath Holding Adult Breast Neoplasms Middle Aged Lung Unilateral Breast Neoplasms Humans Machine Learning Algorithms Retrospective Studies Tomography, X-Ray Computed Female Aged
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Improved Image Quality Through Deep Learning Acceleration of Gradient-Echo Acquisitions in Uterine MRI: First Application with the Female Pelvis.

Academic radiology Jan 21, 2025
RATIONALE AND OBJECTIVES: The aim of this study was to compare the image quality of a deep learning (DL)-accelerated volumetric interpolated breath-hold examination (VIBE) sequence with a standard (ST) VIBE sequence in assessing the uterus.
Breath Holding Uterus Pelvis Image Interpretation, Computer-Assisted Prospective Studies Middle Aged Artifacts Female Deep Learning Adult Contrast Media Magnetic Resonance Imaging Humans
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Deep-Learning-Based Reconstruction of Single-Breath-Hold 3 mm HASTE Improves Abdominal Image Quality and Reduces Acquisition Time: A Quantitative Analysis.

Current oncology (Toronto, Ont.) Jan 3, 2025
Breath-hold T2-weighted half-Fourier acquisition single-shot turbo spin echo (HASTE) magnetic resonance imaging (MRI) of the upper abdomen with a slice thickness below 5 mm suffers from high image noise and blurring. The purpose of this prospective ...
Image Processing, Computer-Assisted Abdomen Magnetic Resonance Imaging Signal-To-Noise Ratio Adult Breath Holding Humans Male Prospective Studies Middle Aged Female Deep Learning Aged
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Attention incorporated network for sharing low-rank, image and k-space information during MR image reconstruction to achieve single breath-hold cardiac Cine imaging.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Dec 28, 2024
Cardiac Cine Magnetic Resonance Imaging (MRI) provides an accurate assessment of heart morphology and function in clinical practice. However, MRI requires long acquisition times, with recent deep learning-based methods showing great promise to accele...
Image Interpretation, Computer-Assisted Humans Breath Holding Magnetic Resonance Imaging, Cine Deep Learning Image Processing, Computer-Assisted Heart
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Breath-hold diffusion-weighted MR imaging (DWI) using deep learning reconstruction: Comparison with navigator triggered DWI in patients with malignant liver tumors.

Radiography (London, England : 1995) Dec 11, 2024
INTRODUCTION: This study investigated the feasibility of single breath-hold (BH) diffusion-weighted MR imaging (DWI) using deep learning reconstruction (DLR) compared to navigator triggered (NT) DWI in patients with malignant liver tumors.
Signal-To-Noise Ratio Retrospective Studies Breath Holding Liver Neoplasms Female Diffusion Magnetic Resonance Imaging Liver Aged Humans Feasibility Studies Adult Aged, 80 and over Image Interpretation, Computer-Assisted Male Middle Aged Deep Learning
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Estimation of heart dose in left breast cancer radiotherapy: Assessment of vDIBH feasibility using the supervised machine learning algorithm.

Journal of applied clinical medical physics Dec 6, 2024
BACKGROUND AND OBJECTIVE: The volunteer deep inspiration breath hold (vDIBH) technique is used to reduce the heart dose in left breast cancer radiotherapy. Many times, it is faced that despite rigorous exercise and training, not all patients get bene...
Breath Holding Unilateral Breast Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Humans Radiotherapy, Intensity-Modulated Middle Aged Algorithms Heart Female Feasibility Studies Adult Supervised Machine Learning Breast Neoplasms
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