Computer Number: 65

S. Li, M. Gao, Z. Zhou, Z. Li
Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

Impact: This study provides valuable insights into the utility of multi-b-value DWI models for grading ccRCC, suggesting that advanced models offer limited additional benefits over mono-exponential DWI. It enables more efficient imaging choices and informs clinical decision-making in ccRCC management.

Computer Number: 66

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S. Che, K. Ma, Y. Jiang, F. Thorsten, J. Li, X. Zhao, C. Zhou
Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

Impact: This study highlights time-dependent diffusion MRI's potential for accurate, non-invasive breast cancer grading, enhancing clinical decision-making and treatment planning, and paving the way for further research into microstructural changes and applications in other cancer types.

Computer Number: 67

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Q. Zhang, Y. Jiang, X. Yu, X. Zhao
Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

Impact: Time-dependent diffusion MRI, as a non-invasive technique, could provide cell microstructure parameters for differentiating tumor grade of CC from a histological point of view, which may further assist in preoperative clinical decision-making and prognosis prediction for CC.

Computer Number: 68

H. Liu, Q. Wang, Z. Mao, H. Liu, M. Wang, Y. Song, C. zhang, G. Yang
Department of Radiology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China

Impact:

This study demonstrates that diffusion kurtosis imaging can non-invasively predict estrogen receptor expression by characterizing tumor microenvironments, revealing significant relationships between tumor habitats and their microstructural properties.

Computer Number: 69

Q. Bi, K. Wu, S. Wang, Y. Wu
The First People’s Hospital of Yunnan Province, Kunming, China

Impact: Together, diffusion parameters and the combined model could become a new and non-invasive diagnostic biomarker for differentiating benign and malignant endometrial lesions.

Computer Number: 70

W. Tang, Y. Guo, Z. Zhong, X. Xu, Y. Chen, Y. Xu, X. Wei
Guangzhou First People’s Hospital, Guangzhou, China

Impact: Oscillating gradient DWI, with shorter diffusion times, complements conventional pulsed gradient DWI by revealing additional tumor microstructural details. Combined OGSE and PGSE sequences may enable novel diffusion-based biomarkers for improved breast lesion characterization and stratification.

Computer Number: 71

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I. Guha, H. Ravi, R. Mohamed, C. Quarles, H-L Liu
MD Anderson Cancer Center, Houston, United States

Impact: Our study demonstrates the potential of DL to reduce DTI scan time for brain cancer patients by enabling accurate estimation of DTI metrics from only 6-direction DWI volumes; and enhancing their image quality and signal-to-noise ratio.

Computer Number: 72

Z. Mao, H. Liu, H. Liu, M. Wang, Y. Song, C. Zhang, G. Yang
The Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, China

Impact: The stable predictive performance of DKI/TILs can help clinicians make more accurate diagnoses; commercialization is expected.

Computer Number: 73

J. j. Li, Y. Xiao, K. Ai, Y. Zhu, Y. Hao, J. Guo
The First Affiliated Hospital of Xi'an Jiaotong University , Xi’an, China

Impact: TDD-MRI parameters, particularly cell diameter, demonstrate superior accuracy to ADC in differentiating pathological grades and stages in CSC, supporting their use for non-invasive cervical cancer assessment.

Computer Number: 74

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M. Li, L. Zhou, A. Abudulimu, H. Zhang, L. Qian, T. Feiweier, W. Li
Xiangya Hospital, Central South University, Changsha, Hunan Province, China

Impact: Td-dMRI is a potential tool for evaluating VETC status in HCC, which may contribute to the optimization of personalized treatment strategies for patients with HCC, thus leading to improved prognosis.

Computer Number: 75

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Z. Yuan, D. Shi, F. Liu, Z. Wang, Y. He, X. Gao, Y. Li, J. Chen, X. Liu, J. Ren, H. Guo, Z. Jin, H. Xue
Radiology Department, Peking Union Medical College Hospital, Beijing, China

Impact: The MRI cytometry parameters can distinguish cervical cancer from normal cervix by directly capturing the changes in the tissue microstructure. It may further assist in preoperative risk stratification and treatment efficacy evaluation in cervical cancer in the future.

Computer Number: 76

Z. Kang, S. Du, L. Zhang
The Fourth Affiliated Hospital of China Medical University, Shenyang, China

Impact: This research reveals the utilization of FROC model improved differentiation of the low Ki67 expression group (Ki67≤ 5%) in ER+/HER2- breast cancer, who frequently exhibit a favorable prognosis and do not require excessive adjuvant chemotherapy. 

Computer Number: 77

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Y. Li, C. Ren, J. Cheng, Y. Zhang, W. Zhang, L. Lin
The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China

Impact: This study revealed the changes in quantitative microstructural mapping across the spectrum of bone tumors. Intracellular volume fraction and cellularity are potential markers for differentiating benign and malignant bone tumors.

Computer Number: 78

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M. Marzetti, P. Robinson, L. Maguire, P. Duce, S. Klein, M. Starmans, A. Scarsbrook, D. Buckley
Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom

Impact:

This work uses quantitative MRI to differentiate benign from malignant soft-tissue lesions, aiming to reduce the need for soft-tissue biopsies. This could reduce the number of invasive procedures patients undergo and provide diagnoses faster, reducing patient anxiety, pain and discomfort.

Computer Number: 79

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Y. Lee, K-H Cho, C-H Tang, Y-C Chang, I-H Lee, Y-C Hsieh, S-C Chao, C-H Kuan, L-W Kuo
National Taiwan University Hospital, Taipei, Taiwan

Impact: This study provides a quantitative approach to delineate the tissue characteristics of lymphedema by utilizing diffusion kurtosis MRI, enabling a more precise and non-invasive way to assess the severity, which could be potentially helpful to the surgical planning of lymphedema.