Digital Poster
New DWI Techniques in the Body
ISMRM & ISMRT Annual Meeting & Exhibition • 10-15 May 2025 • Honolulu, Hawai'i
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Computer Number: 17
2884. Motion-robust,
time-efficient, whole-liver DWI using Diffusion PLUS
(Physiology-Led Unique Slice ordering)
M. Yoneyama, D. Murayama, T. Sakai, Y. Goto, M. Nagao, J.
Prince, N. Blanken, S. Zhang, I. Ball, M. Van Cauteren, J.
Peeters
Philips Japan, Tokyo, Japan
Impact: Diffusion PLUS improves liver DWI by providing
fast scans with reliable image quality. It offers a
practical option in the clinical environment and may enhance
diagnostic accuracy for liver lesions, particularly in the
left lobe.
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Computer Number: 18
2885. Volumetric
T1 and ADC Mapping Aids in Lung Nodule Detection: An MRI-Based
Approach
C. Wu, K. Dollar, W. Chua, H-L Lee, C. Gao, C. Lee, P.
Thompson, D. Li, Y. Xie, S. Ghandehari
Cedars-Sinai Medical Center, Los Angeles, United States
Impact: MRI with T1 and ADC mapping shows promise as a
radiation-free alternative for lung nodule detection,
potentially improving screening safety and accuracy in
high-risk individuals.
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Computer Number: 19
2886. Based
on ADC histogram for distinguishing benign and malignant thyroid
nodules: A small FNA-indeterminate cohort exploratory
investigation
X. Ren, H. Junhao, R. Huanhuan, L. Daihong, H. Weiting
Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
Impact: The prediction model based on ADC and
morphological features shows a higher specificity than
ultrasound TIRADS standards. ADC parameter histogram
features can evaluate the benign and malignant nodules,
especially nodules with uncertain FNA, assist clinicians in
reducing unnecessary biopsy rates.
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Computer Number: 20
2887. Agreement
of vendor software tools for placental diffusion coefficient
maps in normal and hypertensive pregnancies
Y. Xi, C. Herrera, Q. Do, D. Owen, C. Spong, B. Fei, D.
Twickler, M. Lewis
UT Southwestern Medical Center, Dallas, United States
Impact: Choice of diffusion models significantly affects
diffusion coefficients estimation. Consistent methodologies
in placental diffusion imaging are crucial for reliable
comparisons and generalizable clinical interpretation.
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Computer Number: 21
2888. Diffusion
Kurtosis Imaging-based Deep Learning Classification Model in
Histological Subtyping of Cervical Carcinoma
M. Wang, Y. Deng, J. Gong, E. Lee
Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, China
Impact:
The proposed uAInnovation research platform designed for clinicians is efficient and helpful in deep learning deployment. DKI-based CNN classification model demonstrated good performance in differentiating histological subtypes, suggesting the potential clinicopathological value of DKI in cervical carcinoma. |
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Computer Number: 22
2889. Time-Dependent
Diffusion MRI Parameters for Non-invasive Assessment of PARVA
Expression in Breast Cancer
M. Iima, H. Imai, M. Akamatsu, D. LeBihan, M. Kim, N. Gotoh,
Y. Takeuchi, T. W. Nobashi, M. Kataoka, A. Otani, M. Honda,
H. Satake, S. Naganawa, Y. Nakamoto
Nagoya University Graduate School of Medicine, Nagoya, Japan
Impact: Advanced DWI parameters (Kurtosis, S-index,
sADC) enables non-invasive assessment of the expression of
biological markers linked to stromal organization in breast
cancer.
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Computer Number: 23
2890. Histogram
Analysis of Multiplexed Sensitivity Encoding in the
Differentiation of Benign and Malignant Breast Lesions as
Compared to BI-RADS
J. Liu, M. Tang, X. Ge, Z. Wang, F. Jia, Y. Xiong, J. Zhang
The Second Hospital of Lanzhou University, Lanzhou, China
Impact: ADC histogram analysis is an emerging image
analysis technology that can analyze the entire tumor tissue
component, which has been widely applied for many systems
and has shown good diagnostic performance.
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Computer Number: 24
2891. Diagnostic
and predictive potential of multiple b-value DWI for allograft
dysfunction after kidney transplantation during follow-up
L. Chen, P. Yang, J. Cui, S. Xie, Y. Lu, D. Sun, J. Zhu, R.
Grimm
Tianjin First Central Hospital, Tianjin, China
Impact: The parameters generated from multi-b-value DWI
may help to improve the monitoring ability for follow-up of
allograft function. The parameters in the early stage can
provide a certain complementary role for predict
dysfunction and adjustment of the follow-up program.
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Computer Number: 25
2892. Evaluating
MRI Response in Breast Tumours Treated with Radiotherapy – Can
Apparent Diffusion Co-efficient (ADC) Predict Long Term
Response?
E. Durie, M. Morris, S. Salehi, N. Healy, A. Seth, N.
Tunariu, S. Allen, M. Barta, A. Chandra, C. Rakesh, P. Borg,
S. Sahu, P. Haria, M. Tang, N. Somaiah, M. Blackledge
The Institute of Cancer Research, Sutton, United Kingdom
Impact: Early assessment of ADC on DW-MRI after
radiotherapy treatment could predict long term responses in
breast tumours. This could allow future personalisation of
radiotherapy doses based on baseline ADC values of tumours.
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Computer Number: 26
2893. Deep
Learning-Based Inversion for Diffusion-Relaxation Correlation
Spectrum and its Application in Prostate Cancer Diagnosis
Y. Yi, G. Wu, C. Wang, Y. Song, G. Yang
Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China
Impact: Deep learning can accelerates the inversion
substantially and increase the robustness of results, which
can facilitate the application of sub-voxel analysis based
on DR-CSI.
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Computer Number: 27
2894. Multiparametric
magnetic resonance imaging in determining disease activity of
thyroid-associated ophthalmopathy: Added value from DCE and DWI
X-Y Pu, H. Hu, J. Zhou, J-L Lu, X-Q Xu, F-y Wu
Jiangsu Province Hospital (The First Affiliated Hospital of Nanjing Medical University), Nanjing, China
Impact: DCE-MRI, which provides information on
microcirculatory perfusion and permeability, and DWI, which
evaluates water diffusion properties of EOMs in different
stages of TAO. Therefore, DCE-MRI and DWI may serve as
reliable supplementary techniques to the conventional T2WI
in staging TAO.
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Computer Number: 28
2895. Predicting
Postoperative Pancreatic Fistula after Pancreatoduodenectomy
using Continuous-Time Random-Walk DWI and Virtual MR
Elastography
W. Cai, Y-J Zhu, X-m Zhao, Y. Jiang, D-F Li
National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy, Beijing, China
Impact: Non-Gaussian diffusion model CTRW and vMRE
techniques exhibited the ability in predicting CR-POPF
preoperatively, and their combination could improve the
predictive performance. Our prediction model may help
clinicians adopt appropriate prevention or mitigation
strategies to reduce the probability of CR-POPF.
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Computer Number: 29
2896. Diagnostic
value of synthetic MRI combined with MUSE-DWI in cystic solid
tumors of the ovary
C. HUI, T. WEI, T. FU, L. YAN, Y. YAO, Z. QI, D. Pylypenko
Women's Hospital Of Nanjing Medical University, Nanjing, China
Impact: This study demonstrates that combining synthetic
MRI, MUSE-DWI parameters, and morphological features
significantly improves diagnostic accuracy for ovarian
cystic-solid tumors, offering a valuable tool to distinguish
malignant from nonmalignant lesions, potentially reducing
misdiagnosis and improving patient outcomes.
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Computer Number: 30
2897. Multi-shot
DWI alone may be sufficient for HCC surveillance
R. Brunsing, S. Miller
Stanford University, Stanford, United States
Impact: Multi-shot DWI offers superior CNR over T2
weighted imaging methods. In this small cohort all lesions
were visible on msDWI. Thus msDWI alone may be sufficient
for HCC surveillance and warrants further analysis in larger
studies.
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