| Computer # |
| 3833.
 | 129 | The effects of different expression states of δ-catenin on resting brain functional in patients with breast cancer before treatment Mingtuan Xue1, Jiajun Cao1, Wei Du1, and Yanwei Miao1
1Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, China Keywords: Tumors (Pre-Treatment), Cancer Motivation: δ-catenin is the only member of the p120ctn family that can be expressed in neurons. It has been confirmed that δ-catenin highly expressed in breast cancer patients and is significantly associated with the poor prognosis.
Goal(s): Explore the changes of brain network function in BRCA patients with different expressions of δ-catenin before treatment. Approach: Categorize untreated BRCA patients into two groups based on the different expressions of δ-catenin,and subjected to neuropsychological testing, brain structural and functional MRI, along with a healthy control group. Results: The breast cancer patients with different δ-catenin expression have different effects on the indexes of brain functional network. Impact: The
research results suggest that the brain-network changes caused by δ-catenin
precede cognitive impairment changes. Early brain damage caused by
δ-catenin protein may involve areas related to executive functions and
emotional regulation. |
| 3834.
 | 130 | Comparing non-invasive blood-brain barrier mapping with dynamic susceptibility contrast MRI in patients with high-grade glioma and metastasis Gabriel Hoffmann1,2, Christine Preibisch1,2,3, Matthias Günther4,5,6, Amnah Mahroo4, Matthias JP van Osch7,8, Lena Václavů7, Marie-Christin Metz1, Kirsten Jung1, Claus Zimmer1,2, Benedikt Wiestler1, and Stephan Kaczmarz1,2,9
1School of Medicine and Health, Department of Neuroradiology, Technical University of Munich, Munich, Germany, 2School of Medicine and Health, TUM-Neuroimaging Center, Technical University of Munich, Munich, Germany, 3School of Medicine and Health, Clinic of Neurology, Technical University of Munich, Munich, Germany, 4MR Physics, Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany, 5MR-Imaging and Spectroscopy, University of Bremen, Bremen, Germany, 6mediri GmbH, Heidelberg, Germany, 7C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, Netherlands, 8Leiden Institute of Brain and Cognition, Leiden University, Leiden, Netherlands, 9Philips GmbH Market DACH, Hamburg, Germany Keywords: Tumors (Post-Treatment), Permeability, Blood Brain Barrier Motivation: Glioma-induced blood-brain barrier (BBB) disruptions can be characterized by dynamic susceptibility contrast MRI via the leakage parameter K2. However, it may lack sensitivity to subtle impairments. Recently, non-invasive ASL-based water-exchange measurements (Tex) were proposed to measure even subtle BBB-impairments. Goal(s): We hypothesized correlations of Tex with K2 in contrast-enhancing tissue (CET). Approach: K2 & Tex were compared in 22 patients with brain tumors and 19 healthy controls. Results: Tex agreed well with K2 in CET and was sensitive to pathophysiologically impaired BBB. Moreover, results indicate superior sensitivity to subtle impairments, which may improve therapy planning and progress monitoring. Impact: ASL-based Tex allows non-invasive detection of the pathophysiologically impaired blood-brain barrier in tumors. Whereas its sensitivity to subtle impairments may improve treatment planning in tumors, it could also impact diagnosis of neurodegenerative diseases such as Alzheimer's or Parkinson’s. |
| 3835.
 | 131 | Diffusion and contrast-enhancement MRI phenotypes predict immune cell infiltration in brain metastases Francesco Sanvito1,2, Sonoko Oshima1,2, Eileen Shiuan3, Lu Sun4, Nicholas S Cho1,2, Asher Kim5, Noriko Salamon2, Benjamin M Ellingson1,2, Robert Prins4, Won Kim4, and Jingwen Yao1,2
1Brain Tumor Imaging Laboratory (BTIL), Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States, 2Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States, 3Division of Hematology/Oncology, Department of Medicine, University of California Los Angeles, Los Angeles, CA, United States, 4Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States, 5Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, United States Keywords: Tumors (Post-Treatment), Treatment Motivation: Immune checkpoint inhibitors (ICIs) can promote immune cell infiltration and increase anti-tumoral immune response in brain metastases (BM). Imaging proxies of immune infiltration would facilitate ICI-response monitoring in BM. Goal(s): To test whether the combined assessment of diffusion and contrast-enhancement MRI phenotypes can provide insights into microscopic immune infiltration. Approach: We studied the associations of diffusion and contrast-enhancement MRI phenotypes with histological immune cell infiltration and with ICI-treatment status Results: Correlation analysis showed that high diffusivity and pronounced contrast-enhancement were positively associated with increased immune cell infiltration and were more likely observed in ICI-treated lesions. Impact: Immune checkpoint inhibitors (ICIs) can promote immune cell infiltration and increase anti-tumoral immune response in brain metastases (BM). Diffusion and contrast-enhancement MRI phenotypes provide potential imaging biomarkers to non-invasively monitor tissue changes related to anti-tumoral immune response following ICIs. |
| 3836.
 | 132 | Differentiation between high-grade gliomas and solitary brain metastases: a comparison of five diffusion weighted MRI models Libing He1, Meining Chen2, Yinqiao Yi3, Xu Yan4, Qin Zhang5, and Xiaoxue Xu1
1Department of radiology, Affiliated Hospital of North Sichuan Medical College, nanchong, SIchuan, China, 2MR Research Collaboration, Siemens Healthineers, Chengdu, China, 3Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China, 4MR Research Collaboration, Siemens Healthineers, Shanghai, China, 5MRI clinical application, Customer Service Department, Siemens Digital Medical Technology, Shanghai, China Keywords: Tumors (Pre-Treatment), Diffusion/other diffusion imaging techniques Motivation: Differentiating high-grade gliomas (HGGs) from solitary brain metastases (SBMs) using conventional MRI remains challenging due to similar imaging features. Goal(s): Evaluating the diagnostic performance of advanced diffusion models, like NODDI and MAP, against traditional techniques like DWI, DTI and DKI in distinguishing HGGs from SBMs. Approach: Using a 12-minute sequence, parameters of NODDI, MAP, DKI, DTI, and DWI were reconstructed using specialized postprocessing tools. Results: NODDI_Viso was the most effective parameter in distinguishing HGGs from SBMs, and combining parameters of DTI_AD, DTI_RD, MAP_MSD and NODDI_Viso further enhanced classification accuracy. Impact: Combined models from DTI, MAP and NODDI shows promise as sensitive imaging biomarkers for neuro-oncology and potentially improves treatment strategies for HGGs and SBMs. |
| 3837.
 | 133 | Differentiation of Brain Metastases from Different Pathological Types of Lung Cancers by Using Radiomic Features of the Edema and Tumor Region Hanting Zhu1, Rui fang Xiong1, Chengyi Li1, Pengxin Hu1, Yu Zou1, and Xiaoping Tang1
1Second Affiliated Hospital of Nanchang University, Nanchang, China Keywords: Tumors (Pre-Treatment), Cancer Motivation: Prediction of brain metastases from different pathological types of lung cancers. Goal(s): To develop a radiomic model based on the peritumoral edema and tumor region for tumor type prediction of brain metastases from different pathological types of lung cancers. Approach: Collect lung cancer patients, establish radiomics models, and test the model's differentiation of lesions. Results: The radiomic model could effectively differentiate two pathological types of brain metastasis from lung cancer. Impact: The radiomic model based on the edema and tumor region could effectively differentiate two pathological types of brain metastasis from lung cancer. It is expected to provide an imaging basis for clinicians to evaluate prognosis and formulate personalized treatment plans. |
| 3838.
 | 134 | Differentiating Brain Metastases Recurrence from Treatment-Induced Changes Using Velocity-Selective ASL: Initial Experience Dan Zhu1,2, Feng Xu1,2, Dapeng Liu1,2, Lisa Katulis3, Doris Lin2, Lawrence Kleinberg3, and Qin Qin1,2
1F.M. Kirby Research Center, Kennedy Krieger Institute, Baltimore, MD, United States, 2Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore, MD, United States, 3Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD, United States Keywords: Tumors (Post-Treatment), Arterial spin labelling, Brain Metastasis Motivation: Brain metastases (BM) have increased frequency of treatment-related changes difficult to distinguish from progressive disease. To date, there are no studies evaluating arterial spin labeling (ASL) for BM patients during post-therapy follow-up. Goal(s): To evaluate the feasibility of velocity-selective ASL (VSASL) derived cerebral blood flow (CBF) mapping in differentiating metastases recurrence from treatment-induced changes. Approach: VSASL was applied to 9 BM patients, and compared with pseudo-continuous ASL (PCASL), dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI), and pathologic confirmation for some patients. Results: VSASL is clinically feasible and more comparable with DSC-PWI than PCASL in patients with treated BM at suspicion of tumor progression. Impact: This study showed
that velocity-selective arterial spin labeling has the potential to offer a non-invasive alternative to dynamic
susceptibility contrast perfusion-weighted imaging in
differentiating tumor recurrence
from treatment-induced changes among patients with brain metastases. |
| 3839.
 | 135 | Application of Contrast-Enhanced MULTIPLEX T1 and aT1-weighted Imaging in the Diagnosis of Brain Metastases Xue Liang1, Yongjuan Lin2, Qinglei Zhang1, Kuan Wang1, Weitong Song1, Chuanshuai Tian1, Zhengyang Zhu1, Yunfei Zhang3, Zhenyu Yin2, Bing Zhang1, and Xin Zhang1
1Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing University, Nanjing, China, 2Department of Geriatrics，The Affiliated Drum Tower Hospital of Nanjing University Medical School, Department of Geriatrics，The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China, 3Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, China Keywords: Tumors (Pre-Treatment), Tumor, MULTI-parametric MR imaging with fLEXible design（MULTIPLEX）; contrast-enhanced(CE); gradient recalled-echo(GRE);brain tumor; intracranial metastasis Motivation: Early monitoring for intracranial metastatic lesions through non-invasive methods will directly impact patient prognosis and quality of life. Goal(s): The aim of this study was to evaluate the performance of MULTIPLEX in detecting brain metastases. Approach: Signal-to-noise ratios (SNRs) for gray matter (GM) and white matter (WM), contrast-to-noise ratios (CNRs) for lesion/GM, lesion/WM, and GM/WM were quantitatively compared. Results: MULTIPLEX aT1 imaging is preferred for depicting lesions containing hemorrhage or calcifications. Impact: The combination of MULTIPLEX T1 and aT1
sequences enhances the detection of brain metastatic lesions compared to T1-GRE imaging, which could be helpful for detecting of
small metastatic tumors. |
| 3840.
 | 136 | Comparing methods of biomarker quantification for contrast clearance analysis in patients with brain metastases Yifan Guo1, James de Boisanger2, Emma Harris1, Philip Benjamin3,4, Nicola Rosenfelder2, and Matthew David Blackledge1
1Department of Radiotherapy and Imaging, Institute of Cancer Research, London, United Kingdom, 2Neuro-oncology Unit, The Royal Marsden NHS Foundation Trust, London, United Kingdom, 3Department of Radiology, The Royal Marsden NHS Foundation Trust, London, United Kingdom, 4Department of Neuroradiology, St George’s University Hospital, London, United Kingdom Keywords: Tumors (Pre-Treatment), Cancer, brain metastases, contrast clearance analysis (CCA) Motivation: Differentiating tumour progression and treatment-induced changes in brain metastases is challenging, and quantitative measures of tumour burden and response are needed. Goal(s): To develop and compare quantitative contrast clearance analysis (CCA) mapping techniques with conventional qualitative approaches in 9 patients with brain metastases. Approach: We assessed the correlation of Relative Enhancement and Fractional Enhancement methods with conventional CCA in the brain and within detected tumour regions. Results: Fractional Enhancement mapping was superior to relative enhancement in terms of its statistical properties and correlation with conventional CCA. Impact: Quantitative enhancement fraction mapping of contrast clearance analysis (CCA) data is clinically feasible and demonstrates good correlation with conventional CCA. When used in combination with conventional radiological CCA, it may help quantify post-treatment changes in brain metastases following treatment.
|
| 3841.
 | 137 | The association between the intravoxel incoherent motion diffusion-weighted imaging(IVIM) with the DSC and 3DASL imaging in Glioma Recurrence Yanhong Liu1, Yuhan Liang1, Jiayi Sun1, and Yulin Wang1
1Department of Radiology, The First Medical Center, Chinese PLA General Hospital, Beijing, China Keywords: Tumors (Post-Treatment), Diffusion/other diffusion imaging techniques, Glioma;recurrence Motivation: Diffusion-weighted imaging and perfusion-weighted imaging have shown promising accuracy in differentiating glioma recurrence and treatment-related changes. Intravoxel incoherent motion (IVIM) MRI enables the simultaneous acquisition of diffusion and perfusion parameters, providing true diffusion and capillary perfusion in the tumor. Goal(s): To evaluate the diagnostic performance of IVIM-derived parameters in glioma recurrence patients with DSC and 3DASL perfusion-weighted imaging. Approach: The correlation between IVIM parameter and perfusion-MRI parameters was evaluated in regions of contrast enhancement with Pearson’s correlation analysis. Results: ADC-F within T1-enhanced lesions positively correlated with relative cerebral blood volume (rCBV),nrCBF, and nCBF. Additionally,ADC-F was statistically significantly associated with rCBV and nrCBF. Impact: IVIM has the same
diagnostic efficacy for recurrent glioma with the perfusion-MRI parameters and
can used as a reliable alternative diagnostic sequence for glioma
recurrence.
|
| 3842.
 | 138 | Detecting BCL-6 overexpression Status in Primary Central Nervous System Lymphoma Using Multiparametric MRI Based Machine Learning wang mingxiao1, Ma Lin1, Liu Guoli1, Zhang nan2, and Li Yanhua1
1Radiological Diagnosis Department of the First Medical Center of the General Hospital of the People's Liberation Army of China, Beijing, China, 2Radiological Diagnosis Department of the First Medical Center of the General Hospital of the People's Liberation Army of China, Bejing, China Keywords: Tumors (Pre-Treatment), Cancer Motivation: Based on BCL-6 status，the prognosis of PCNSL can be detected，then the treatment can be adjusted. Goal(s): Detecting BCL-6 Expression Status in Primary Central Nervous System Lymphoma Using Multiparametric MRI Based Machine Learning. Approach: Using Python code to retrieve Pyromics for radiomics feature screening from T2、T2 Flair、ADC.The AUC value was used to evaluate the detection performance of the image sequence joint classifier, Obtain the best classifier. Results: The multi parameter sequence combined with SVM machine learning has the highest AUC, with BCL-6 overexpression detected in the training and validation sets of 0.945 and 0.865,sensitivity of 98% and 92.7%, specificity of 83.9% and 87.5%. Impact: Based on BCL-6 status, the patients are divided into "good risk" and "poor risk".patients who have a “poor risk”phenotype may be candidates for aggressive initial therapy with chemotherapy and radiaion.It may be desirable to defer WBRTto avoid the radiation-induced neurotoxicity. |
| 3843.
 | 139 | Value of whole-lesion histogram analysis based on ADC and ASL in predicting the response to chemotherapy and prognosis of PCNSL Nan Zhang1, Guoli Liu1, Mingxiao Wang1, and Lin Ma1
1Radiology, The First Medical Center, Chinese People’s Liberation Army General Hospital, Beijing, China Keywords: Tumors (Pre-Treatment), Quantitative Imaging Motivation: Primary central nervous system lymphoma (PCNSL) is a rare malignant non-Hodgkin's lymphoma with a poor prognosis, the combination chemotherapy regimen based on methotrexate is the main therapeutic regimen. There are no reliable indicators to predict the treatment response and survival outcome of PCNSL patients. Goal(s): To predict the response to methotrexate (MTX) chemotherapy and prognosis in primary central nervous system lymphoma (PCNSL) patients by the histogram parameters based on apparent diffusion coefficient (ADC) and arterial spin labeling (ASL). Approach: Use the univariate and multivariate logistic regressions to identify the independent predictors for the response of MTX chemotherapy. The predictive performance was assessed by the receiver operating characteristic. The Kaplan-Meier analysis and Cox regression were used to analyze the OS. Results: Number of lesions (NL), the maximum of ADC values and the 95th percentile of CBF values were independent predictive factors of chemotherapy response. Impact: ADC and CBF values are promising predictive factors of chemotherapy response and outcome in PCNSL patients. |
| 3844.
 | 140 | Pixel-wise correlation among DCE/DSC metrics in brain tumor with Multitasking-based dynamic imaging for cerebrovascular evaluation (MT-DICE) Jiayu Xiao1, Yang Chen2, Jushen Wu2, Jason Ye2, Frances Chow2, Gabriel Zada2, Mark Shiroishi2, Steven Cen2, and Zhaoyang Fan2
1Radiology, University of Southern California, Los Angeles, CA, United States, 2University of Southern California, Los Angeles, CA, United States Keywords: Tumors (Post-Treatment), Tumor Motivation: DCE and DSC-derived Ktrans, ve, CBV, and kio are measures of microcirculatory function, perfusion, and water channel in brain tumors. They have shown clinical values in tumor grading, treatment response, and prognosis evaluation. However, their pixel-wise inter-correlation remains unclear, partially due to separate scans in conventional protocol or having one of them omitted. Goal(s): To investigate the pixel-wise correlation of Ktrans, ve, CBV, and kio in patients with brain tumors using MT-DICE. Approach: The multiparametric maps simultaneously quantified by MT-DICE were analyzed pixel-by-pixel within the slice showing the largest enhancing tumor. Results: Ktrans and ve correlate well with kio in the spatial distribution. Impact: MR multitasking-based dynamic imaging for cerebrovascular evaluation (MT-DICE) provides spatial quantitative maps of BBB permeability, tumor perfusion, and water channel. The information helps better understand intra-tumor heterogeneity and may assist in selecting biopsy sites and precisely monitoring treatment response. |
| 3845.
 | 141 | Comparing DSC-CBV, DSC-CBF and ASL for Detecting Residual and Recurrent Glioblastoma with Deep Learning and multishell Diffusion MRI Louis Gagnon1, Diviya Gupta2, George Mastorakos3, Nathan White3, Vanessa Goodwill2, Carrie McDonald2, Thomas Beaumont2, Tyler Siebert2, Jona Hattangadi-Gluth2, Santosh Kesari4, Jessica Schulte2, David Piccioni2, Divya S Bolar2, Nikdokht Farid2, Anders Dale2, and Jeffrey Rudie2
1Laval University, Quebec City, QC, Canada, 2UCSD, San Diego, CA, United States, 3Cortechs.ai, San Diego, CA, United States, 4Pacific Neuroscience Institute, Santa Monica, CA, United States Keywords: Tumors (Post-Treatment), Tumor Motivation: Differentiating recurrent tumor from post-treatment changes is challenging in post-operative glioblastoma MRI. Goal(s): To compare the performance of DSC-CBV, DSC-CBF, and ASL perfusion MRI to differentiate recurrent tumor from treatment-related changes using a Deep Learning segmentation model together with multishell Diffusion MRI. Approach: 138 post-operative scans were manually segmented for enhancing and non-enhancing cellular tumor volume. A Deep Learning segmentation was trained to segment cellular tumor and then tested to differentiate recurring disease from post-treatment changes from the segmentations. Results: DSC-CBV and DSC-CBF improved the detection of residual/recurrent cellular tumor with Deep Learning while ASL perfusion did not. Impact: Our work re-demonstrates the importance of including a DSC perfusion method in clinical brain tumor MRI protocols. |
| 3846.
 | 142 | Whole-brain Morphological Network Alterations in Patients with H3K27M-altered Diffuse Midline Glioma Di Chen1,2, Simin Zhang1,2, Qiyong Gong1,2, and Qiang Yue1,2
1Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, Chengdu, China, 2Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu, China, Chengdu, China Keywords: Tumors (Pre-Treatment), Brain Connectivity, H3K27M-altered diffuse midline glioma, structural covariance networks, graphy theory, topological properties Motivation: H3K27M-altered diffuse midline glioma (DMG) is a highly infiltrative and deadly form of brain cancer with a dismal prognosis. The mechanisms underlying its aggressiveness remain elusive. Goal(s): To elucidate alterations in whole-brain morphological networks in diffuse midline glioma patients and assess whether such alterations are associated with the H3K27M mutation. Approach: A whole-brain structural covariance network (SCN) was constructed based on cortical thickness. Results: The topological characteristics of structural covariance network (SCN) were severely disrupted in DMG. Additionally, H3K27M mutations may induce more aggressive whole-brain network damage. Impact: The research offers novel insights into the mechanisms of progression in H3K27M-altered DMG, which may help in developing new treatment protocols. |
| 3847.
 | 143 | The Value of CEST MRI of Peritumoral Regions in Post-Therapy Malignant Glioma Assessment Qianqi Huang1,2, Puyang Wang2, Jingpu Wu2,3, Mingchao Liu4, Yunfan Zou2,5, Jinyuan Zhou2, and Shanshan Jiang2
1Department of Computer Science, Johns Hopkins University, Baltimore, MD, United States, 2Department of Radiology, Johns Hopkins University, Baltimore, MD, United States, 3Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States, 4Department of Data Science, Johns Hopkins University, Baltimore, MD, United States, 5Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States Keywords: Tumors (Post-Treatment), CEST & MT Motivation: Monitoring post-chemoradiotherapy malignant gliomas is a persistent challenge in neuro-oncology. The peritumoral region, closely related to tumor recurrence, has been infrequently examined in the imaging pattens and the potential mechanism. Goal(s): Our objective was to explore whether CEST MRI could distinguish tumor recurrence from treatment effects and uncover potential mechanisms behind high-grade gliomas' invasive behavior. Approach: We investigated the CEST effects at 3.5ppm and 2.0ppm, as well as T1 and T2 values from the peritumoral regions of malignant gliomas with histogram analysis. Results: Significant higher CEST effects across chemical shift offsets were presented in peritumoral regions in recurrent tumor compared with treatment effects. Impact: The different progressive patterns in peritumoral regions between treatment effects and tumor recurrence are assessable by CEST MRI. It provides a potential imaging maker matrix to unveil the mechanism of invasive behavior of malignant gliomas. |
| 3848.
 | 144 | A continuous-time random-walk diffusion model for predicting tumor consistency and extent of resection in patients with pituitary adenomas Chun-Qiu Su1, Zeng-Ping Lin2, Ran Tang2, Ke Xue2, Hai-Bin Shi1, and Shan-Shan Lu1
1Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China, 2United Imaging Healthcare, Shanghai, China Keywords: Tumors (Pre-Treatment), Tumor, Diffusion; Pituitary adenoma Motivation: Preoperative evaluation of the consistency of pituitary adenomas (PAs) plays a significant role in the surgical strategy. However, previous studies concerning the assessment of tumor consistency of PAs were controversial1-4. Goal(s): To evaluate the ability of the continuous-time random-walk (CTRW) diffusion model to predict the consistency and extent of resection (EOR) of PAs. Approach: The CTRW diffusion model relaxes a priori distributions of waiting times and distance increments of water molecular diffusion, providing a realistic description of the complex structures of biological tissues5. Results: CTRW diffusion model could provide information about the tumor consistency and EOR of PAs. Impact: CTRW
diffusion model provides an imaging dimension for
characterizing tissue microstructure of PAs and may serve as a promising tool
to predict the tumor consistency and EOR in patients with PAs. |