Gu, Chunming

Abstract Objective. Four-dimensional CT (4DCT) enables visualization of dynamic wrist joint pathology but may be compromised by motion artifacts. Deep learning (DL)-assisted motion correction has the potential to enhance wrist 4DCT quality, but model development is hindered by scarce training data. To address this, we developed a model-based motion simulation framework that generated realistic 4DCT data with paired static ground truth images to demonstrate wrist motion correction using a physics-informed DL model trained with simulated data. Approach. Wrist motion was simulated by synchronizing rotational and translational movements of carpal bones and connective tissues. Elastic deformation guided by analytically-derived motion vector fields was applied to static wrist scans at neutral positions to create artifact-free images at multiple angular positions. Virtual motion-corrupted 4DCT images were produced via forward projection and reconstruction with synchronized gantry and wrist motion. Experimental data from 4DCT cadaver scans were collected to validate simulation quality. Low-intensity region score (LIRS), positivity, and entropy were used to assess simulated motion artifacts. A physics-informed motion correction network was adapted exclusively using simulated training data and subsequently deployed on simulated, real cadaveric, and in vivo 4DCT scans. LIRS and structural similarity index (SSIM) were used to evaluate motion correction quality. Wilcoxon signed-rank tests were conducted ( α = 0.05). Results. The simulation method created realistic motion artifacts compared to real scan reference ( p > 0.05). Motion artifacts were effectively mitigated across testing cases demonstrating generalizability. In simulated scans, LIRS improved from 0.55 ± 0.12–0.75 ± 0.04 and SSIM from 0.87 ± 0.08–0.95 ± 0.03 at bone regions (each p < 0.01). In experimental cadaveric scans, LIRS improved from 0.05 ± 0.01–0.31 ± 0.17 in marker regions and from 0.58 ± 0.19–0.77 ± 0.14 in bone regions (each p < 0.01). Significance. Our simulation method facilitates training DL-assisted motion correction algorithms by providing high-quality training data, effectively supporting 4DCT image quality enhancement.

Abstract Objective . The use of Feraheme (ferumoxytol) as a contrast agent in MR-guided focused ultrasound (MRgFUS) tumor ablations could enhance treatment safety and efficacy by improving vascular visualization through strong T1 and T2 shortening effects. However, Feraheme impact on MR thermometry and tissue heating is unclear. This study evaluates the feasibility of incorporating Feraheme into MRgFUS by assessing its impact on MR imaging contrast, MR thermometry, and thermal response in tissue-mimicking phantoms. Approach . Tissue-mimicking phantoms with 0 (baseline), 0.25, and 0.5 mM Feraheme concentrations were prepared using a validated recipe. Acoustic attenuation was measured with a commercial diagnostic ultrasound scanner. MR imaging at 1.5 T was performed to assess gradient-recalled-echo (GRE)-based thermometry signal-to-noise-ratio (SNR), relaxation rates, and relaxivities. MRgFUS system integrated with 1.5 T MRI was used to perform multiple sonications in the phantoms. Temperature elevations and focal heating areas were quantified from proton resonance frequency (PRF) shift thermometry. Experiments were repeated three times over the period of eight-weeks. Separately, temperature-dependent nuclear magnetic resonance (NMR) spectroscopy was performed at 3.0 T in saline-diluted Feraheme phantoms (0, 0.25, 0.5, and 1.0 mM) to assess the influence of Feraheme concentration on PRF coefficients used in MR thermometry. Main results . Phantoms showed nuclear relaxation times ( T 1: 1178.1 ± 77.8, T 2: 103.21 ± 2.45 ms) and attenuation coefficients (0.34–0.36 dB cm −1 MHz −1 ) within expected biological tissue ranges. Relaxivities demonstrated a strong linear dependence on Feraheme concentration ( r 1: 17.5 ± 0.2, r 2: 209.2 ± 2.6 s −1 mM −1 ). Relative to baseline (0 mM) phantom, the SNR of GRE-based thermometry increased by 12.6% at 0.25 mM and decreased by 27.1% at 0.5 mM. Sonications in Feraheme-containing phantoms resulted in statistically higher temperature elevations ( p < 0.001 ) although no statistically significant difference was observed between 0.25 and 0.5 mM. All NMR measurements demonstrated stable, linear PRF temperature dependence ( R 2 = 0.996–0.999), with PRF coefficients (between −0.0074 and −0.0082 ppm °C −1 ). The resulting thermometry bias was small and predictable (+0.67 and +1.73 per 20 °C at 3.0 T for 0.25 and 0.5 mM). Significance . These findings demonstrate that MR thermometry remains feasible at moderate Feraheme concentrations and support its potential use to enhance visualization of critical vasculature near targeted tissues during MRgFUS.

Salivary glands are common organs at risk in both head and neck external beam radiotherapy (EBRT) and radiopharmaceutical therapy (RPT), but incidences of xerostomia in RPT are inconsistent with the EBRT Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) limits. In EBRT, salivary glands are usually assumed to be parallel organs, with QUANTEC guidelines based on Dmean, but this is known to be a gross over-simplification of the full complexity of the underlying functional organization. The goal of this work is to combine machine learning of EBRT dose–outcome data with stylized small-scale RPT dosimetry to discover more reliable normal tissue complication probability (NTCP) models of xerostomia across both modalities. A retrospective cohort of 211 EBRT patients was analyzed using a custom-designed in-house machine learning workflow. From this, a hierarchy of three models of increasing complexity was trained, evaluated for performance and generalization, and coupled with stylized small-scale salivary gland dosimetry to assess the influence of model complexity on the predicted NTCP for plausible patterns of RPT dose nonuniformity. The three models in the hierarchy (A, B, C), in increasing order of complexity, associate xerostomia with the following: the mean dose to the whole contralateral parotid (model A), the mean dose to a ductally localized region (model B) and a serial interaction dose term between two ductal sub-compartments (model C). While the difference between the three models for EBRT p-values and AUCs is rather marginal, for physiologically driven ductal dose distributions in RPT, the predicted reduction in TD50 can be as large as a factor of 10. These results provide hints towards a plausible reconciliation of the observed inconsistency of xerostomia in RPT with EBRT dose limits.

AbstractPurposeThe inflow‐based vascular‐space‐occupancy (iVASO) MRI was originally developed in a single‐slice mode to measure arterial cerebral blood volume (CBVa). When vascular crushers are applied in iVASO, the signals can be sensitized predominantly to small pial arteries and arterioles. The purpose of this study is to perform a systematic optimization and evaluation of a 3D iVASO sequence on both 3 T and 7 T for the quantification of CBVa values in the human brain.MethodsThree sets of experiments were performed in three separate cohorts. (1) 3D iVASO MRI protocols were compared to single‐slice iVASO, and the reproducibility of whole‐brain 3D iVASO MRI was evaluated. (2) The effects from different vascular crushers in iVASO were assessed. (3) 3D iVASO MRI results were evaluated in arterial and venous blood vessels identified using ultrasmall‐superparamagnetic‐iron‐oxides–enhanced MRI to validate its arterial origin.Results3D iVASO scans showed signal‐to‐noise ratio (SNR) and CBVa measures consistent with single‐slice iVASO with reasonable intrasubject reproducibility. Among the iVASO scans performed with different vascular crushers, the whole‐brain 3D iVASO scan with a motion‐sensitized‐driven‐equilibrium preparation with two binomial refocusing pulses and an effective TE of 50 ms showed the best suppression of macrovascular signals, with a relatively low specific absorption rate. When no vascular crusher was applied, the CBVa maps from 3D iVASO scans showed large CBVa values in arterial vessels but well‐suppressed signals in venous vessels.ConclusionA whole‐brain 3D iVASO MRI scan was optimized for CBVa measurement in the human brain. When only microvascular signals are desired, a motion‐sensitized‐driven‐equilibrium–based vascular crusher with binomial refocusing pulses can be applied in 3D iVASO.