Cecilia Liang¹, Isabelle Loster², Thomas Küstner^1,3, Brigitte Gückel¹, Bernd Kühn⁴, Fritz Schick³, Ferdinand Seith¹, and Petros Martirosian^3
1Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Tuebingen, Germany, ²University Tuebingen, Tuebingen, Germany, ³Section on Experimental Radiology, University Hospital Tuebingen, Tuebingen, Germany, ⁴Siemens Healthineers, Erlangen, Germany

Keywords: Kidney, Kidney

Motivation: Multiparametric MRI of the kidneys is a promising technique for renal diagnostics, but the diversity of imaging protocols and analysis strategies hinders clinical translation.

Goal(s): Our goal was to assess the repeatability of a multiparametric MRI protocol comparing ROI-based and tissue segmentation based analysis.

Approach: Ten volunteers were examined with a multiparametric MRI protocol including ASL, IVIM, BOLD, T1 and T2 mapping twice with one week between visits.

Results: Good repeatability of the multiparametric protocol could be achieved. T1 and T2 values showed less variability compared to perfusion and diffusion related functional parameters. Tissue segmentation showed better repeatability compared to ROI-based analysis.

Impact: Our study demonstrates relatively high repeatability of multiparametric functional MRI of the kidneys. The results of the image analysis methods suggest, that manual segmentation is to be preferred over ROI-based analysis, if automated segmentation is not available.

Yongjian Zhu¹, Peng Wang¹, Wei Cai¹, Bingzhi Wang², Xuan Meng³, Sicong Wang⁴, and Xiaohong Ma^1
1Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, ²Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, ³Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, ⁴GE Healthcare, MR Research China, Beijing, China

Keywords: Liver, Liver

Motivation: Accurately predicting microvascular invasion (MVI) risk in hepatocellular carcinoma before surgery could aid clinicians in selecting appropriate surgical approaches to improve the patient’s prognosis.

Goal(s): To construct DCE-MRI based nomogram for predicting MVI, and to assess its ability for stratifying the risk of recurrence after hepatectomy and guiding surgical approaches.

Approach: Quantitative DCE-MRI parameters from both intra-tumoral region (ITR) and peritumoral region (PTR), along with clinical-radiological (CR) features, were utilized to establish the nomogram.

Results: The nomogram presented AUC values of 0.966 in the training and 0.937 in the validation set for predicting MVI. High-risk patients could obtain survival benefit from anatomical resection.

Impact: We constructed and evaluated the performance of the bi-regional quantitative DCE-MRI based nomogram for predicting MVI risk in HCC. Our predictive model effectively predicts MVI risk and assists clinicians in selecting appropriate therapeutic strategies for patients.

Kai Li¹, HaiYan Chen¹, Lei Shi¹, Rong Li Tang¹, and Shan Huang^2
1Zhejiang Cancer Hospital, Hangzhou City,Zhejiang Province, China, ²Philips Healthcare, Shanghai, China

Keywords: Cancer, Relaxometry, T1-mapping

Motivation: MRI quantitative technique T1 mapping can reflect the change of intrinsic information of tissues

Goal(s): To explore the value of T1 mapping in PDCA with different degrees of differentiation

Approach: Comparison of PDCA with different degrees of differentiation, the T1 relaxation time before and after enhancement

Results: by  comparing the T1 mapping values before and after enhancement of PDAC with different degrees of differentiation, it was found that as the degree of differentiation of PDAC was getting higher, the Native T1 value showed a tendency to increase. The Native T1 was moderately positively correlated with the degree of pathological differentiation

Impact: T1 mapping may serve as a noninvasive means of predicting the degree of pathologic differentiation of PDAC before surgery.Give clinicians earlier information.

Eamon C Doyle¹ and John C Wood^2
1Radiology, Children's Hospital of Los Angeles-USC KSOM, Los Angeles, CA, United States, ²Pediatrics and Radiology, Children's Hospital of Los Angeles-USC KSOM, Los Angeles, CA, United States

Keywords: Liver, Relaxometry, Iron Overload

Motivation: Estimation of liver iron concentration by R2* relaxation (LIC_R2*) is a powerful and widely used technique, however, it may fail from signal loss at high liver iron concentration.  

Goal(s): To estimate LIC from a single-TE liver-muscle signal intensity ratio (LIC_SIR) and validate at 1.5 and 3.0 Tesla.  

Approach: Using LIC_R2* estimates collected at 1.5T as a reference, we compared LIC_SIR estimates in 15 subjects who had undergone MRI examination at both 1.5T and 3.0T.

Results: We were able to derive field-independent scaling constants that allow LIC_SIR estimation at 1.5 and 3.0T, more than doubling the effective dynamic range of LIC_R2* estimation.

Impact: This generalized framework for LIC_SIR estimation allows reasonable LIC values to be reported (and trended) in patients for whom traditional relaxometry has failed. It also allows approximate LIC calculation from commonly used single and dual echo gradient echo acquisitions.

Jialu Xu¹ and Jiejun Cheng^1
1Department of Radiology, Shanghai First Maternity and Infant Hospital , Tongji University, Shanghai, China

Keywords: Placenta, Placenta

Motivation: To evaluate virtual magnetic resonance elastography in healthy and preeclamptic(PE) pregnancies.

Goal(s):  To compare the stiffness value (μ_diff)  and apparent diffusion coeffificient (ADC) in healthy and PE pregnancies.

Approach: DWI(b-value of 50 ,200and 800 s/mm² ) were performed on all pregnant women using a 1.5 T MRI scanner. The value of μ_diff  and ADC were calculated and compared between groups.

Results: The mean ADC value of the control and PE groups were 1.414±0.228×10^-3 mm²/s and 1.737±0.107×10^-3 mm²/s, respectively.  The mean  μ_diff value of PE were 5.901±1.757 and 4.618±2.055 kPa, respectively. The area under the curve for μ_diff was 0.903 and ADC was 0.796, respectively. 

Impact: Placental  μdiff value was found to be more reliable than ADC in differentiating between normal and preeclampsia placentas.

Mami Iima^1,2, Marino Akamatsu³, Hirohiko Imai⁴, Hana Suzuki³, Noriko Gotoh⁵, Yasuto Takeuchi⁵, Maya Honda¹, Tomomi Nobashi¹, Masako Kataoka¹, Akihiko Yoshizawa⁶, hiroaki Ito⁷, Tomoe Nakagawa⁸, Minsoo Kim⁹, Denis Le Bihan^10,11, and Yuji Nakamoto^1
1Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan, ²Institute for Advancement of Clinical and Translational Science (iACT), Kyoto University Hospital, Kyoto, Japan, ³Faculty of Medicine, Kyoto University, Kyoto, Japan, ⁴Department of Systems science, Graduate School of Informatics, Kyoto University, Kyoto, Japan, ⁵Cancer Research Institute, Kanazawa University, Kanazawa, Japan, ⁶Diagnostic Pathology, Nara Medical University, Nara, Japan, ⁷Diagnostic Pathology, Kyoto University Graduate School of Medicine, Kyoto, Japan, ⁸Department of Pathology and Tumor Biology, Kyoto University Graduate School of Medicine, Kyoto, Japan, ⁹Laboratory of Integrative Molecular Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan, ¹⁰Human Brain Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan, ¹¹CEA-Saclay, Paris-Saclay University, NeuroSpin, Gif/Yvette, France

Keywords: Cancer, Breast

Motivation: The lack of reliable biomarkers for assessing tumor characteristics and the limitations of histological analysis due to tumor heterogeneity led to the exploration of  diffusion-weighted parameters.

Goal(s): To investigate the association between DW parameters and Ki-67 expression in triple-negative breast cancer, with a focus on whether they can serve as prognostic biomarkers.

Approach: Seventeen triple-negative breast cancer mice with a PDX model underwent 7T MRI scans, yielding DW images. Advanced analysis evaluated ADC and non-Gaussian diffusion parameters, validated through histological Ki-67 staining.

Results: DWI parameters (S-index, sADC, and ADC₀) show strong correlations with Ki67 levels,  at short and long diffusion times (9, 27.6ms).

Impact: Promising prognostic biomarkers for triple-negative breast cancer, DWI parameters (S-index, sADC, and ADC₀) displayed strong correlations with Ki-67 expression, at short and long diffusion times. This validation through accurate DWI-pathology comparison highlights imaging's pivotal role in advancing breast cancer diagnosis.

Ting-ting Lin^1
1The First Affiliated Hospital of USTC（Anhui Provincial Cancer Hospital）, Hefei, China

Keywords: Breast, Cancer, molecular subtypes

Motivation: To analyze the value of imaging examination in accurate diagnosis of breast cancer.

Goal(s): Provide an non-invasive examination for the prediction of molecular subtypes of breast cancer before treatment.

Approach: The quantitative parameters of IVIM-DWI and DCE-MRI in patients with breast cancer without any invasive examination and treatment were compared with pathological molecular subtypes, so as to analyze their diagnostic value in the prediction of molecular subtypes.

Results: DCE-MRI and IVIM-DWI were correlated with immune prognostic factors of breast cancer and had differential diagnostic value for different molecular subtypes.

Impact: DCE-MRI and IVIM-DWI could provide a non-invasive diagnostic method for predicting molecular subtypes of breast cancer and provide a reference for further development of personalized treatment plans.  

Veronica Wallaengen¹, Adrian L Breto¹, Isabella M Kimbel¹, Evangelia I Zacharaki¹, Ahmad Algohary¹, Nachiketh Soodana Prakash², Sandra M Gaston¹, Rosa P Castillo Acosta³, Oleksandr N Kryvenko⁴, Bruno Nahar², Dipen J Parekh², Alan Pollack¹, Sanoj Punnen², and Radka Stoyanova^1
1Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, United States, ²Department of Urology, University of Miami Miller School of Medicine, Miami, FL, United States, ³Department of Radiology, University of Miami Miller School of Medicine, Miami, FL, United States, ⁴Department of Pathology, University of Miami Miller School of Medicine, Miami, FL, United States

Keywords: Software Tools, Cancer

Motivation: Discrimination between true and false positive targets identified using PI-RADSv2 is needed to avoid unnecessary biopsies.

Goal(s): To investigate how quantitative analysis of prostate mpMRI through Habitat Risk Scoring (HRS) combined with PI-RADS can improve prostate lesion identification compared to using PI-RADS alone.

Approach: In prospective clinical trials lesions identified by PI-RADS and/or HRS were targeted through MRI/ultrasound fusion biopsies.

Results: Using HRS yields 100% NPV in the PI-RADS 3 cohort and increases PPV by 7.4% in the PI-RADS 4-5 cohort with respect to clinically significant cancer. Overall, the NPV and PPV increased by 21.4% and 13.2% respectively.

Impact: We present a quantitative imaging approach to complement the current standard for assessing prostate cancer risk in mpMRI data and demonstrate that the use of HRS strengthens fidelity in both positive and negative detections.

Rong He¹, Gesheng Song¹, Junyi Fu¹, Weiqiang Dou², Aiyin Li¹, and Jingbo Chen^3
1Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China, ²GE Healthcare,MR Research, Beijing, China, ³Department of General Surgery, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China

Keywords: fMRI Analysis, Diffusion/other diffusion imaging techniques, histogram analysis

Motivation: Currently, perineural invasion (PNI) of rectal cancer (RC) can only be confirmed by pathological examination of postoperative specimens. 

Goal(s): It aimed to investigate the intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) in diagnosing the PNI status of RC by histogram analysis.

Approach: We extracted histogram features from 7 parametric maps derived from IVIM-DWI. The independent predictive histogram features of rectal cancer PNI were combined with the percentage of rectal wall
enclosure（PCI ) reported by MRI to construct a combined model for preoperative diagnosis of PNI.

Results: The AUC of the combined model is higher than that of each single-parameter model and histogram model.

Impact: This study demonstrated that full-volume histogram parameters basing on IVIM-DWI can be used to assess PNI status in rectal cancer. Histogram analysis, as a non-invasive tool, may be more valuable not only in rectal cancer research in the future.

Brendan Moloney¹, Xin Li¹, Michael Hirano², Assim Saad Eddin³, Jeong Youn Lim¹, Debosmita Biswas², Anum S. Kazerouni², Alina Tudorica¹, Isabella Li², Mary Lynn Bryant², Courtney Wille³, Chelsea Pyle¹, Habib Rahbar², Su Kim Hsieh³, Travis Rice-Stitt¹, Suzanne Dintzis², Amani Bashir³, Evthokia Hobbs¹, Alexandra Zimmer¹, Jennifer Specht², Sneha Phadke³, Nicole Fleege³, James Holmes³, Savannah C. Partridge², and Wei Huang^1
1Oregon Health & Science University, Portland, OR, United States, ²University of Washington, Seattle, WA, United States, ³University of Iowa, Iowa City, IA, United States

Keywords: Treatment Response, Cancer, Multi-Center and Multi-Vendor platform, DCE-MRI, Therapy Response, Ktrans

Motivation: Validate Shutter-Speed model (SSM) DCE-MRI as a robust predictor of breast cancer (BC) response to neoadjuvant chemotherapy (NAC) in a multi-center and multi-vendor platform setting.

Goal(s): Compare tumor size, semi-quantitative, and quantitative DCE-MRI for early prediction of NAC response.

Approach: BC patients treated with NAC underwent longitudinal high spatiotemporal resolution DCE-MRI at three sites using a 3T Siemens, GE, or Philips system.  Semi-quantitative signal-enhancement-ratio (SER) and quantitative Tofts model (TM) and SSM pharmacokinetic (PK) parameters were derived from DCE time-course data.

Results: PK parameters outperformed size and SER while SSM was superior to TM in early prediction of pathologic response.

Impact: It is feasible to implement quantitative high spatiotemporal resolution SSM DCE-MRI in trials with multi-center and multi-vendor platform settings for robust assessment of BC response to NAC.

Yu Huang¹ and Chen ZHAO^2
1Radiology, The First Clinical Medical College of Guangxi Medical University, Nanning, China, ²MR Research Collaboration, Siemens Healthineers., Nanning, China

Keywords: Other Interventional, Quantitative Imaging

Motivation: Due to the internal heterogeneity of the nasopharyngeal carcinoma, conventional treatment fails to enhance the tumor microenvironment, ultimately leading to recurrence or metastasis.

Goal(s): To investigate whether quantitative values derived from T1, T2, and PD maps can serve as an assessment index for combined immunotherapy with chemotherapy in patients with newly diagnosed locally advanced NPC.

Approach: Synthetic MRI, non-invasive technique, can generate quantitative values for intrinsic tissue features.

Results: The study indicate the potential of PD and T2 values in distinguishing between two treatment. A larger sample size is required to further validate the value of SyMRI in evaluating immunotherapy for NPC.

Impact: Synthetic MRI can generate longitudinal relaxation time (T1), transverse relaxation time (T2), and proton density (PD).