| Computer # |
| 1451.
 | 49 | Clinical study on distinguishing Triple-Negative Breast Cancer from Non-Triple-Negative Breast Cancer using 3D-APT and DWI Saiqun Lyu1, Tao Peng1, Jianming Xiao1, Lin Li1, Miaoqi Zhang2, Lizhi Xie2, and Huilou Liang2
1Department of Radiology, Affiliated Hospital of Chengdu University, Chengdu, China, 2GE Healthcare, MR Research, Beijing, China Keywords: Cancer, Breast, Triple-negative breast cancer; Non-triple-negative breast cancer; Amide proton transfer imaging; DWI Motivation: Triple-negative breast cancer (TNBC) is a highly malignant and prognostically challenging subtype of breast cancer often elusive in conventional MRI scans [1.4.5]. Three-Dimensional Amide Proton Transfer Imaging (3D-APT), a non-invasive molecular imaging technique, shows promise in improving TNBC diagnosis. Goal(s): This study aimed toinvestigate the diagnostic potential of 3D-APT, alone and in conjunction with diffusion-weighted imaging (DWI), in distinguishing TNBC from non-TNBC. Approach: Quantitative analysis and comparison of APTw and DWI were conducted. Results: Results revealed higher APTw and ADC values in TNBC compared to non-TNBC. Both APTw and DWI exhibit commendable diagnostic efficiency individually, while their combined application demonstrates superior discriminatory power. Impact: These findings provide
essential insights for tailoring individualized treatment strategies and
assessing prognosis in clinical practice. |
| 1452.
 | 50 | Different MRI-based radiomics models for distinguishing misdiagnosed or ambiguous pleomorphic adenoma and Warthin tumor: A multicenter study jing yang1, qiu bi1, kunhua wu1, and Yunzhu wu2
1The First People’s Hospital of Yunnan Provence, kunming, China, 2MR Research Collaboration Team, Siemens Healthineers Ltd, shanghai, China Keywords: Cancer, Cancer Motivation: Enhance the accuracy of distinguishing misdiagnosed or ambiguous cases of pleomorphic adenoma (PA) and Warthin tumor (WT). Goal(s): This study aims to construct various MRI-based radiomics models employing different machine learning classifiers to determine the optimal models for identifying misdiagnosed or ambiguous PA and WT cases. Approach: we evaluate the effectiveness of various MRI-based radiomics models. Results: A nomogram demonstrates exceptional and consistent diagnostic performance. In routine practice, combining clinical parameters is essential for distinguishing between PA and WT. Impact: MRI-based radiomics models can effectively differentiate misdiagnosed or ambiguous cases of PA and WT. The nomogram is a valuable tool for preoperatively and non-invasively distinguishing between PA and WT, a task often challenging for clinicians and radiologists before surgery. |
| 1453.
 | 51 | The quantitative parameters based on IVIM andDCE-MRI in predicting the efficacy in patients with nasopharyngeal carcinoma Nan Wang1, Lijun Wang1, and Haonan Guan2
1Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China, 2GE Healthcare, MR Research China, Beijing, China Keywords: Cancer, fMRI Motivation: This study aims to establish a predictive model based on IVIM and DCE-MRI that could ultimately improve the prognosis of nasopharyngeal carcinoma (NPC) patients. Goal(s): This research paves the way for more effective and tailored treatment approaches for NPC patients. Approach: Patients in the CR group and the NCR group underwent IVIM and DCE-MRI experiments and their quantitative parameters were compared. Results: The CR group exhibited higher Ktrans value and lower D and ADC values compared to the NCR group. ROC analysis showed that the AUC values of Ktrans, D and ADC before treatment were approximately 0.772, 0.751, and 0.699, respectively. Impact: Early prediction of the efficacy of NPC patients can optimize the treatment plans, functional MRI techniques can offer insights into the pathological and physiological state of living tissues before morphological changes, prolong their survival, and hold immense clinical significance. |
| 1454.
 | 52 | Dynamic contrast enhanced MRI and susceptibility-weighted imaging for diffierentiation of parotid gland tumors: a pilot study Yihua Wang1, Lijun Wang1, Qingwei Song2, and Ailian Liu2
1Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China, 2the First Affiliated Hospital of Dalian Medical University, Dalian, China Keywords: Cancer, Cancer Motivation: MRI is one of the major methods to diagnose parotid gland tumors. Substantial overlap in the appearance of tumors may be seen on anatomic MR images. Goal(s): To assess the usefulness of combined DCE with SWI in the differentiation of benign and malignant tumors. Approach: We assess the value of DCE and ITSS in the differential diagnosis between malignant and benign parotid tumors. Results: Results showed that the differences between malignant and benign tumors in Kep (p=0.024) and ITSS (p<0.01) were statistically significant. Combined with ITSS, the diagnostic performance of Kep was improved for differentiating malignant from benign tumor (AUC 0.718 vs 0.927). Impact: Our current study showed that DCE can elucidate perfusion characteristics of parotid tumors. SWI is a new complementary technique that can detect signal intensity changes from both T2WI and susceptibility differences between tissues. These fndings suggest that SWI and DCE quantitative parameters may facilitate the understanding of the pathophysiological characteristics of parotid tumors. |
| 1455.
 | 53 | Perfusion parameters of DCE-MRI using GRASP correlates with tumour cellularity of lung cancer. Lihua Chen1, Daihong Liu1, and Jiuquan Zhang1
1Department of Radiology, Chongqing University Cancer Hospital, Chongqing, China Keywords: Cancer, Perfusion Motivation: Tumour cellularity indicates tumour proliferation. Although perfusion MRI parameters have been proposed for non-invasive assessment of tumour cellularity, few studies have validated this theory, particularly in lung cancer. Previous studies provided a free-breathing perfusion MRI method using GRASP. Goal(s): Therefore, our aim is to investigate the relationship between tumour cellularity and perfusion parameters of MRI using GRASP. Approach: Pearson correlation coefficients were used to illustrate the relationship between perfusion parameters and cell density. Results: The findings indicated an inverse correlation between tumour cellularity and Ve. However, the study found no significant correlation between Ktrans and cell density. Impact: It suggests that GRASP
perfusion MRI has potential as a non-invasive technique to assess tumour
cellularity in lung cancer. |
| 1456.
 | 54 | Evaluation of Peritoneal Fluid Flow in Response to Respiratory Motion Using MRI-Based CFD Juan Pablo Gonzalez-Pereira1,2, Labib Shahid1,2, Lisa Barroilhet3, Pamela Kreeger4, and Alejandro Roldan-Alzate1,4,5
1Mechanical Engineering, University of Wisconsin-Madison, Madison, WI, United States, 2Radiology, University of Wisconsin-Madison, Madison, WI, United States, 3Obstetrics and Gynecology, University of Wisconsin-Madison, Madison, WI, United States, 4Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States, 5Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States Keywords: Cancer, Cancer, Peritoneal, MRI-Based-CFD Motivation: High-grade serous ovarian cancer (HGSOC) is hypothesized to initiate at fallopian tubes and ovaries, and then spreads by detaching and floating through the peritoneal fluid to the upper abdomen. Goal(s): Create a framework that could potentially assess HGSOC cell movement and deposition in the peritoneal cavity using MRI-based computational fluid dynamics. Approach: Under the assumption that ovarian cancer cells are already prevalent in peritoneal fluid, ovarian cancer cell displacement can be analyzed using MRI-based CFD. Results: Velocity maps and streamlines and WSS maps were created using CFD simulation results to predict cells transport to the lower peritoneum and diaphragm. Impact: MRI-based CFD allows temporal and volumetric analysis
of the peritoneal cavity and provides insight in ovarian cancer cell spread due
to peritoneal fluid flow. Velocities and wall shear stress analysis can be used
to identify stagnation points for cell deposition. |
| 1457.
 | 55 | Investigation of Texture Features in Head and Neck Cancer: Preliminary Results for Early Radiation Therapy induced Changes Victor Fritz1,2,3, Martin Schwartz1,4, Jens Kübler5, Jonas Habrich6, Simon Böke7, Daniela Thorwarth6, Konstantin Nikolaou5, and Fritz Schick1
1Department of Diagnostic and Interventional Radiology, University of Tuebingen, Section on Experimental Radiology, Tübingen, Germany, 2Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Centre Munich at the University of Tuebingen, Tübingen, Germany, 3German Center for Diabetes Research (DZD), Neuherberg, Germany, 4Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany, 5Department of Diagnostic and Interventional Radiology, University of Tuebingen, University Hospital Tuebingen, Tübingen, Germany, 6Department of Radiation Oncology, University Hospital Tübingen, Section for Biomedical Physics, Tübingen, Germany, 7Department of Radiation Oncology, University Hospital Tübingen, University Hospital and Medical Faculty, Tübingen, Germany Keywords: Cancer, Head & Neck/ENT Motivation: Radiomic texture features are considered promising biomarkers for tumor’s response to therapy. Goal(s): To identify texture features that can enhance predictive accuracy regarding tumor treatment outcomes. Approach: The study included 13 patients with head and neck cancer undergoing radiation therapy, with MRI (T2w, DWI) conducted before treatment and during early-treatment phase. Image processing, tumor segmentation, and feature extraction are performed. Results: Wilcoxon signed-rank tests with a Holm-Bonferroni correction reveals that Skewness in T2w-images exhibits significant changes during early treatment. This finding suggests that this feature may hold promise for predicting therapeutic responses, although larger studies are needed to confirm these results. Impact: The study's preliminary findings suggest that Skewness in T2w images may have the potential to provide useful information for early response assessment in head and neck cancer patients undergoing radiation therapy, warranting further investigation to confirm its clinical significance. |
| 1458.
 | 56 | A magnetic resonance imaging-based lymph node regression grading scheme for nasopharyngeal carcinoma after radiotherapy Di Cao1, Zhiying Liang1, Kan Deng2, and Siyu Zhu1
1Sun Yat-sen University Cancer Center, Guangzhou, China, 2Philips Healthcare, Guangzhou, China Keywords: Treatment Response, Cancer Motivation: After curative radiotherapy (RT), there is no commonly accepted method to distinguish between patients with residual disease that may eventually cause disease progression and those who are already cured of the disease in nasopharyngeal carcinoma (NPC). Goal(s): We proposed a four-category MRI-based lymph node regression (MRI-LRG) grading system to investigate its prognostic value for NPC after RT. Approach: 387 NPC patients were included in this retrospective study. Lymph node regression grade was assessed on MRI based on the areal analysis of RT-induced fibrosis and the residual tumor. Results: Our results showed that MRI-based LRG was an independent prognostic factor for progression-free survival. Impact: A nomogram, based on LRG-sum, pretreatment EBV DNA,
post-RT EBV DNA, sex and N stage factors, was proved to be useful to facilitate
risk stratification in NPC. This approach might help to stratify treatment
modalities and develop a more effective tailored surveillance program in
patients with NPC. |
| 1459.
 | 57 | Radiomics and Background Parenchymal Enhancement of Fibroglandular Tissue for Predicting Treatment Response in Triple-Negative Breast Cancer Rania M Mohamed1, Jong Bum Son2, Beatriz Adrada3, Tanya Moseley3, Gary Whitman3, Rosalind Candelaria3, Bikash Panthi4, Huiqin Chen5, Mary Guirguis3, Jessica Leung3, Ken-Pin Hwang2, Sanaz Pashapoor3, Miral Patel3, Marion Scoggins6, Huong Le-Petross3, Deanna Lane3, Frances Perez3, Peng Wei5, Zhan Xu2, Debu Tripathy7, Wei Yang3, Clinton Yam7, Jingfei Ma2, and Gaiane M Rauch8
1Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States, 2Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States, 3Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States, 4Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States, 5Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States, 6Radiology - Breast Imaging, UT Southwestern Medical Center, Dallas, TX, United States, 7Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States, 8Abdominal and Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States Keywords: Breast, Cancer, Treatment response, DCE-MRI, neoadjuvant therapy Motivation: No imaging biomarkers are currently available for predicting response to neoadjuvant systemic treatment (NAST) in triple negative breast cancer (TNBC), contributing to toxicity to patients from ineffective treatment regimens. Goal(s): To evaluate if quantitative analyses of breast parenchyma can serve as noninvasive biomarker of treatment response in TNBC. Approach: Mean background parenchymal enhancement (BPE) and radiomic features of fibroglandular tissue from longitudinal DCE-MRI were evaluated using AUC analysis on a prospective cohort of 273 TNBC patients. Results: Four first order radiomic features were predictive of pCR with AUC>0.6. Multivariable radiomic models and BPE changes had AUC<0.6 for pCR prediction in TNBC undergoing NAST. Impact: Radiomic features from fibroglandular tissue and background parenchymal enhancement changes in ipsilateral and contralateral breasts using DCE MRI during treatment of triple-negative breast cancer patients were evaluated as noninvasive biomarkers for prediction of pathologic complete response to neoadjuvant systemic therapy. |
| 1460.
 | 58 | Restriction Spectrum Imaging (RSI) Models for Cervical Cancer Ana Elvira Rodríguez-Soto1, Christopher Conlin2, Sheida Ebrahimi2, Alexandra Besser2, Stephan Jordan3, Elin Lundstrom2, Alexandra Schlein3, Joshua Kuperman3, Anders Dale4, Tyler Seibert5, Michael McHale6, and Rebecca Rakow-Penner2
1Radiology, University of California San Diego, San Diego, CA, United States, 2Radiology, University of California San Diego, La Jolla, CA, United States, 3University of California San Diego, La Jolla, CA, United States, 4Neurosciences, University of California San Diego, La Jolla, CA, United States, 5Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, United States, 6Ob/Gyn & Reproductive sciences, University of California San Diego, La Jolla, CA, United States Keywords: Cancer, Cancer Motivation: Restriction spectrum imaging (RSI) has demonstrated potential to isolate cervical cancer signal from that of surrounding tissues. Women with post-treatment disease progression wait 3-6 months post treatment to get PET/CT exam to allow for edema/inflammation to subside. Cervical cancer-specific RSI model may allow us to evaluate response-to-treatment earlier. Goal(s): The goal of this work was to develop an RSI cervical cancer model from a larger cohort of patients. Approach: We used RSI-derived information from normal cervixes to convert RSI outputs to Z-score maps in cancer patients. Results: Demonstrated the utility of RSI Z-score maps in differentiating cancers from healthy tissues without exogenous contrast. Impact: Standard of care evaluation of cervical cancer response-to-treatment is PET/CT 3-6 months post-treatment to allow for edema/inflammation to subside. Cervical cancer-specific RSI model may allow us to evaluate response-to-treatment earlier and better inform patient treatment response without unnecessary delay. |
| 1461.
 | 59 | Associations Between Prostate Cancer Lesion Location on mpMRI and Upgrading from Biopsy-Confirmed Histopathology to Final Pathology Vishnu Murthy1, Sohaib Naim1, Sara Babapour1, Steven Raman1, and Kyung Sung1
1Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States Keywords: Cancer, Prostate, mpMRI, Gleason Score, Upgrading Motivation: Given discrepancies in biopsy-confirmed histopathology and final pathology in prostate cancer, there is a clinical need to improve diagnosis and treatment planning using multiparametric MRI (mpMRI). Goal(s): To assess associations between mpMRI lesion location and upgrading of prostate cancer from biopsy-confirmed histopathology to final pathology. Approach: 191 patients who underwent both MRI-ultrasound fusion biopsy and prostatectomy were included. A modified χ² test assessed associations between mpMRI lesion location and upgrading from biopsy-confirmed histopathology to final pathology. Results: mpMRI lesions in the peripheral zone and posterior region were more likely to be upgraded than lesions in the transition zone and anterior region respectively. Impact: In patients who undergo MRI-ultrasound fusion biopsy and prostatectomy, mpMRI lesions in the peripheral zone and posterior region were more likely to be upgraded from biopsy-confirmed histopathology to final pathology than lesions in the transition zone and anterior region respectively. |
| 1462.
 | 60 | Weakly Supervised Learning for Prostate Cancer Detection from Co-registered bi-parametric MRI and Patient’s Clinal Data Fatemeh Zabihollahy1,2, Emerson Paul Grabke1,2,3,4, and Masoom A. Haider1,2
1Joint Department of Medical Imaging, University Health Network, Sinai Health System and University of Toronto, Toronto, ON, Canada, 2Lunenfeld-Tanenbaum Research Institute, Sinai Health System, University of Toronto, Toronto, ON, Canada, 3KITE Research Institute, University Health Network and University of Toronto, Toronto, ON, Canada, 4Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada Keywords: Cancer, Prostate, Image Registration Motivation: Bi-parametric MRI (bpMRI) is now part of the diagnostic workup for prostate cancer (PCa). Radiologists cognitively coregister bpMRI sequences when interpreting MRI. Conversely, machine learning (ML) algorithms have difficulty learning this implicit coregistration because of the distortion often present in diffusion-weighted images. Goal(s): Introduce a novel method for automated 1) bpMRI coregistration; and 2) detection of csPCa. Approach: A weakly supervised learning paradigm was employed for bpMRI co-registration. A combination of co-registered bpMRI and the patient’s clinical data was used for automated csPCa detection. Results: The proposed method achieved a true and false positive rate of 86% and 41% on 100 test cases. Impact: The obtained results demonstrated the value of
co-registration and including patient clinical data for designing ML-based
methods for automated csPCa detection. The proposed algorithm might improve the
accuracy of reading bpMRI, thereby beneficial for patients with prostate
cancer. |
| 1463.
 | 61 | The value of amide proton transfer imaging in the diagnosis of malignant and benign urinary bladder lesions: comparison with DWI Jinglu Li1, Yun Xu1, Yongshen Xiang1, Peng Wu2, Aijun Shen1, Peijun Wang1, and Fang Wang1
1Department of Radiology, Tongji Hospital, Shanghai, China, 2Philips Healthcare, Shanghai, China Keywords: Cancer, Bladder, APT, DWI Motivation: Conventional MRI has certain limitations in distinguishing between malignant and benign urinary bladder (UB) lesions. Goal(s): Compare the diagnostic value of Amide proton transfer (APT) imaging with diffusion-weighted imaging (DWI). Approach: Participants with confirmed UB lesions underwent preoperative multiparametric MRI. The APT signal intensity (represented by asymmetric magnetization transfer ratio, MTRasym), and apparent diffusion coefficient (ADC) values were compared between malignant and benign UB lesions, and their diagnostic performance was evaluated with receiver operating characteristic (ROC) curve analysis. Results: The MTRasym value was significantly better in differentiating urothelial carcinoma from benign UB lesions than the ADC value. Impact: Conventional MRI
exhibits limitations in accurately distinguishing between malignant and benign
urinary bladder (UB) lesions. Amide Proton Transfer (APT) imaging shows promise
in effectively discriminating between malignant and benign UB lesions,
surpassing the performance of Diffusion-Weighted Imaging (DWI). |
| 1464.
 | 62 | Automatically Quantitative Intratumoral Susceptibility Signal In Evaluating The FlOG Staging Of Ovarian Cancer Patients Li Hao1, Ailian Liu2, Ye Li2, Qingling Song2, Yuting Shi3, Qingwei Song2, Hongkai Wang4, and Mingrui Zhuang4
1Department of Radiology, Dalian Municipal Central Hospital, Dalian, China, 2The First Affiliated Hospital of Dalian Medical University, Dalian, China, 3Dalian Medical University, Dalian, China, 4Dalian University of Technology, Dalian, China Keywords: fMRI Analysis, Quantitative Imaging, ovarian tumor Motivation: Accurate diagnosis and staging of ovarian cancer play a key role in the selection of treatment plan, surgical method and determination of the circumference Goal(s): Tumor intratumoral susceptibility signal (ITSS) can reflect the new growth inside the tumor
Vascular and bleeding conditions, ITSS have been widely used in many departments
Although few studies have applied this technique to ovarian cancer Approach: Automatically quantitative ITSS prediction of clinical FIGO staging of ovarian cancer was performed by using AS (AnatomySketch 1.0) software (Dalian University of Technology) Results: The automatic quantitative ITSS rate was significantly higher in advanced ovarian cancer than in early ovarian cancer Impact: Automatic quantitative ITSS is expected to be applied to the study of ovarian tumors and more sites in the future. ITSS can effectively predict FIGO type of ovarian cancer and provide valuable information for making treatment plan and judging prognosis |
| 1465.
 | 63 | Quantitative MRI parameters of amide proton transfer and diffusion kurtosis imaging in the evaluation of breast cancer Haiyan Shan1, Chengde Liao1, Tengfei Ke2, Shasha Bao1, Yifan Liu2, Yongzhou Xu3, and Jun Yang2
1Yan 'an Hospital, kunming, China, 2Yunnan Cancer Hospital, kunming, China, 3Philips Healthcare, kunming, China Keywords: fMRI Analysis, Breast Motivation: Limited clinical studies have explored the potential of Amide Proton Transfer Weighted Imaging (APTWI) in discriminating between benign and malignant breast lesions and molecular subtypes of breast cancer. Goal(s): This study aims to assess the clinical utility of APTWI and DKI in the evaluation of benign and malignant breast diseases and the determination of molecular subtypes of breast cancer. Approach: We quantitatively analyzed lesions in breast MRI scans of patients prior to surgery and evaluated the diagnostic value of each quantitative parameter. Results: APTWI did not exhibit superior diagnostic efficacy compared to DKI and ADC in characterizing the molecular subtypes of breast cancer. Impact: Our study underscores that APT imaging, as a novel quantitative magnetic resonance technique, does not confer a diagnostic advantage over DKI and ADC in the context of breast disease assessment. |