Quantitative Applications in Body MRI: In Numbers We Trust
Digital Poster
Body
Tuesday, 12 May 2026
This session includes presentations that utilize quantitative imaging and related biomarkers in body applications.
Skill Level: Intermediate
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466-02-001.
Research on Quantitative MR in the Evaluation of Liver Function and Prediction of the First Decompensation Event in Patients
Impact: This non-invasive MR model, utilizing T1post-20min and T1rho, enables accurate liver function assessment and early prediction of decompensation in high-risk CHB patients, guiding timely clinical intervention.
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466-02-002.
Characterization of peri-renal adipose tissue T2* and PDFF: scanner vendor reproducibility & scan-rescan repeatability on 3T
Impact: Our findings may support using peri-renal fat T2* and PDFF to measure
abdominal brown adipose tissue repeatably and reproducibly. This could help elucidate pathophysiological
mechanisms of obesity-induced kidney disease and supports use of MRI in
clinical trials of obesity-targeting interventions.
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466-02-003.
Using a Respiratory Cushion in Renal Quantitative Susceptibility Mapping: A Way to Achieve High-Resolution Analysis?
Impact: This work demonstrates the feasibility of acquiring renal quantitative susceptibility mapping (QSM) during free-breathing while controlling acquisition time frames with a respiratory cushion. The free- breathing outcomes matched breath-hold results while enabling higher image resolution.
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466-02-004.
Profiling Lipid Composition from Multi-Gradient Echo MRI – Preliminary Evaluation Using Fat Models, Phantoms and In vivo Data
Impact: This work advances
non-invasive profiling of tissue fatty acid composition, extending MRI beyond
total fat quantification toward detailed compositional lipid mapping.
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466-02-005.
Synthetic DWI with contrast synthesis and T1/T2 estimates may improve PI RADS 3 discrimination and reduce unneeded biopsies
Impact: With only a 90-second
extension, the modified Synthetic DWI enables contrast synthesis and reliable T1/T2
estimates, supporting improved discrimination in PI‑RADS 3 lesions (T2 shows less
overlap than ADC). This suggests potential to reduce unnecessary biopsies in
prostate cancer care.
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466-02-006.
Multiparametric MRI combined with machine learning algorithm for Evaluating Disease Progression in Rats with NASH
Impact: This study demonstrates that multiparametric MRI integrated with machine learning enables accurate, non-invasive staging of NASH, offering a translational imaging framework that may guide diagnosis, monitor therapeutic response, and inspire further exploration of quantitative MRI biomarkers in metabolic liver disease.
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466-02-007.
Predicting esophageal cancer response to neoadjuvant therapy with diffusion MRI
Impact: Diffusion MRI may enable early, non-invasive prediction of therapeutic response in esophageal cancer, supporting a potential “watch-and-wait” strategy for good responders. This could reduce unnecessary surgeries, guide personalized treatment, and motivate broader validation of advanced diffusion models in clinical oncology.
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466-02-008.
Diagnostic Value of Magnetization Transfer and Diffusion MRI for Differentiating Fibroadenoma and Invasive Breast Carcinoma
Impact: Integrating MT and ADC enhances breast MRI specificity, enabling precise, early distinction of benign and malignant lesions. This quantitative approach supports personalized management, reduces unnecessary interventions, and translates advanced imaging into actionable clinical decision-making for improved patient outcomes.
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466-02-009.
Predicting Induction Chemotherapy Response Based on Tumor-stroma ratio Pretreatment Synthetic MRI in Nasopharyngeal Carcinoma
Impact: Using the nomogram were useful in selecting candidate
patients for induction chemotherapy based on pretreatment synthetic MRI, which
has potential clinical value in guiding clinical decision-making and improving
survival.
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466-02-010.
Accurate Quantification of Adipose Tissue at Both Morphological and Microscopic Levels Using DIXON Sequence
Impact: The T1-weighted two-point VIBE Dixon sequence
enables simultaneous quantification of adipose tissue at both morphological and
microscopic levels precisely, providing a novel and comprehensive approach
for fat segmentation and quantification.
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466-02-011.
Repeatability of Renal Magnetic Resonance Elastography Across Frequencies and Vendors
Impact: Renal
MRE stiffness demonstrates high between-day repeatability across frequencies
and vendors, with RC ≤ 15% and ICC ≥0.8. These findings establish practical
thresholds for distinguishing true biological change from measurement
variability and support longitudinal and multicenter applications of renal MRE.
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466-02-012.
Quantitative Evaluation of Prostate Cancer Using Hybrid Multidimensional MRI: Mapping Tissue Microstructure
Impact: Hybrid multidimensional MRI (HM-MRI) enables precise, non-invasive prostate tissue microstructure quantification, objectively differentiating various grades of prostate cancer. It reduces contrast use, surpasses diagnostic confidence of multiparametric MRI, and overcomes PI-RADS variability/subjectivity for reliable, personalized prostate cancer management.
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466-02-013.
Evaluation of hydration effect on water T1 across liver segments using accelerated water T1 mapping
Impact: This study demonstrates that wT1 is influenced
by both hydration status and spatial heterogeneity across the liver. These
findings underline the need to control for physiological and regional factors
to ensure accurate and reproducible liver wT1 quantification.
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466-02-014.
Reducing Fat–Water Swaps and Field Map Artifacts via Echo Dependent Phase Reconstruction for Liver QSM
Impact: Modeling non-chemical shift phase as a single frequency shift in conventional fat–water separation can cause swaps and inaccurate field maps. Incorporating echo-dependent residual phase into the signal model improves fat separation and yields more reliable tissue phase for liver QSM.
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466-02-015.
Validation and Exploratory Analysis of an Automated MRI Body Composition Analysis Tool in a WB-MRI Cancer Screening Cohort
Impact: This study validates and applies a fully automated framework
for quantitative MRI body composition analysis, enabling opportunistic
extraction of metabolic, oncologic, and physiological biomarkers and supporting
exploratory assessment of population-based body-composition trends in
asymptomatic individuals across clinical and research settings.
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