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2929 citation(s) found for "Wu, Ronald".

Volume Progression and Imaging Classification of Polycystic Liver in ADPKD
Bae, Kyongtae T., Tao, Cheng , Feldman, Robert , Chapman, Arlene B., Brosnahan, Godela , Steinman, Theodore I., Braun, William E. , Mrug, Michal , Landsittel, Douglas , Yu, Alan S.L. , Torres, Vicente E. , Perrone, Ronald D. , Bennett, William M. , Harris, Peter C. , Abebe, Kaleab Z

Journal of the American Society of Nephrology | May 17, 2024 | Volume: 31 | Issue: 10S | Pages: 500-500

10.1681/asn.20203110s1500c Get It

Overweight and Obesity Are Predictors of Pain in the HALT-PKD Studies
You, Zhiying , Brosnahan, Godela , Miskulin, Dana C. , Steinman, Theodore I., Braun, William E. , Chapman, Arlene B., Chonchol, Michel , Study, HALT-PKD, Wang, Wei Qiang , Gitomer, Berenice Y , Harris, Peter C. , Torres, Vicente E. , Abebe, Kaleab Z , Yu, Alan S.L. , Perrone, Ronald D. , Nowak, Kristen L. , Study, HALT-PKD

Journal of the American Society of Nephrology | May 17, 2024 | Volume: 31 | Issue: 10S | Pages: 500-500

10.1681/asn.20203110s1500a Get It

PKD1 Compared with PKD2 Genotype and Cardiac Hospitalizations in the HALT-PKD Studies
You, Zhiying , Brosnahan, Godela , Steinman, Theodore I., Braun, William E. , Chapman, Arlene B., Chonchol, Michel , Steele, Cortney , Gitomer, Berenice Y , Harris, Peter C. , Torres, Vicente E. , Abebe, Kaleab Z , Yu, Alan S.L. , Perrone, Ronald D. , Nowak, Kristen L.

Journal of the American Society of Nephrology | May 17, 2024 | Volume: 31 | Issue: 10S | Pages: 488-488

10.1681/asn.20203110s1488a Get It

Terlipressin Improves Renal Replacement Therapy-Free Survival in Hepatorenal Syndrome Type 1
Velez, Juan Carlos Q. , Befeler, Alex S. , Kurtz, Ira , Gallegos‐Orozco, Juan F. , Pappas, S. Chris , Jamil, Khurram , Vargas, Hugo E. , Vierling, John Moore

Journal of the American Society of Nephrology | May 17, 2024 | Volume: 31 | Issue: 10S | Pages: 15-15

10.1681/asn.20203110s115b Get It

TDP-43 Is Associated with Subiculum and Cornu Ammonis 1 Hippocampal Subfield Atrophy in Primary Age-Related Tauopathy
Youssef, Hossam , Gatto, Rodolfo G. , Pham, Nha Trang Thu, Petersen, Ronald C. , Reichard, R. Ross , Jack, Clifford R. , Whitwell, Jennifer L., Josephs, Keith A. , Jack, Clifford R , Whitwell, Jennifer L , Youseff, Hossam , Machulda, Mary M. , Dickson, Dennis W. , Whitwell, Jennifer

Journal of Alzheimer’s Disease | May 10, 2024 | Volume: 99 | Issue: 3 | Pages: 1023-1032

10.3233/jad-240136 | PMID 38728190 Get It

Background: TAR DNA binding protein 43 (TDP-43) has been shown to be associated with whole hippocampal atrophy in primary age-related tauopathy (PART). It is currently unknown which subregions of the hippocampus are contributing to TDP-43 associated whole hippocampal atrophy in PART. Objective: To identify which specific hippocampal subfield regions are contributing to TDP-43-associated whole hippocampal atrophy in PART. Methods: A total of 115 autopsied cases from the Mayo Clinic Alzheimer Disease Research Center, Neurodegenerative Research Group, and the Mayo Clinic Study of Aging were analyzed. All cases underwent antemortem brain volumetric MRI, neuropathological assessment of the distribution of Aβ (Thal phase), and neurofibrillary tangle (Braak stage) to diagnose PART, as well as assessment of TDP-43 presence/absence in the amygdala, hippocampus and beyond. Hippocampal subfield segmentation was performed using FreeSurfer version 7.4.1. Statistical analyses using logistic regression were performed to assess for associations between TDP-43 and hippocampal subfield volumes, accounting for potential confounders. Results: TDP-43 positive patients ( n = 37, 32%), of which 15/15 were type-α, had significantly smaller whole hippocampal volumes, and smaller volumes of the body and tail of the hippocampus compared to TDP-43 negative patients. Subfield analyses revealed an association between TDP-43 and the molecular layer of hippocampal body and the body of cornu ammonis 1 (CA1), subiculum, and presubiculum regions. There was no association between TDP-43 stage and subfield volumes. Conclusions: Whole hippocampal volume loss linked to TDP-43 in PART is mainly due to volume loss occurring in the molecular layer, CA1, subiculum and presubiculum of the hippocampal body.
Cell-Free DNA to Predict Severe Exacerbations in Chronic Obstructive Pulmonary Disease
Richert, Mary, Balasubramanian, S. , Brower, Ronald W., Bleecker, Eugene R., Meyers, Deborah A. , Ortega, Victor E. , Woodruff, Prescott G. , Curtis, J.L., Kong, Hyesik , Jang, Moon Kyoo , Andargie, Temesgen Ewunetu , Brower, R., Bowler, Russell P. , Christenson, Stephanie A. , O’Neal, Wanda K. , Martínez, Fernando J. , Curtis, J.L., Agbor-Enoh, Sean T.

A101. FULL METAL JACKET TARGETING COPD AND CHRONIC AIRWAYS DISEASE | April 30, 2024 | Volume: No volume available | Issue: No issue available | Pages: A2798-A2798

10.1164/ajrccm-conference.2024.209.1_meetingabstracts.a2798 Get It

Interim Results From the Phase 1B and Phase 2 TORREY Open-label Extension Study of Seralutinib in Pulmonary Arterial Hypertension (PAH)
Zolty, Ronald , Kingrey, J.F. , Penn, Benjamin G., Sobol, Irina , Sood, Namita , Benza, R.L., Channick, Richard N. , McLaughlin, Vallerie V. , Vachiéry, Jean‐Luc , Zamanian, R.T., Cravets, Matt , Roscigno, R.F., Mottola, David, Parsley, E., Aranda, R., Zisman, Lawrence S. , Investigators, on behalf of the TORREY Study, Sitbon, Olivier , Sahay, Sandeep , Subías, Pilar Escribano , Penn, B., Channick, Richard N. , Chin, Kelly M , Frantz, Robert P. , Hemnes, Anna R. , Howard, Luke , McLaughlin, Vallerie V. , Ghofrani, Hossein Ardeschir

A14. BUILDING LEGO(LAND): LESSONS LEARNED FROM LARGE SCALE CLINICAL TRIALS IN PAH | April 30, 2024 | Volume: No volume available | Issue: No issue available | Pages: A1011-A1011

10.1164/ajrccm-conference.2024.209.1_meetingabstracts.a1011 Get It

AI and machine learning in medical imaging: key points from development to translation
Samala, Ravi K. , Chan, Heang‐Ping , Petrick, Nicholas , Mahmood, Usman , Summers, Ronald M. , Yoshida, Hiroyuki , Huo, Zhimin, Vergara, Daniel , Mazurchuk, Richard, Grizzard, Kevin , Suzuki, Kenji , Armato, Samuel G. , Shukla-Dave, Amita , Chan, Heang-Ping , Mahmood, Usman , Summers, Ronald M , Deserno, Thomas M , Yoshida, Hiroyuki , Drukker, Karen , Huisman, Henkjan , Samala, Ravi K , Drukker, Karen , Shukla‐Dave, Amita , Sahiner, Berkman , Greenspan, Hayit , Tourassi, Georgia D. , Regge, Daniele , Näppi, Janne J. , Chen, Quan , Morra, Lia , Hadjiiski, Lubomir M.

BJR|Artificial Intelligence | April 29, 2024 | Volume: 1 | Issue: 1 | Pages: No page available

10.1093/bjrai/ubae006 | PMID 38828430 Get It

Abstract Innovation in medical imaging artificial intelligence (AI)/machine learning (ML) demands extensive data collection, algorithmic advancements, and rigorous performance assessments encompassing aspects such as generalizability, uncertainty, bias, fairness, trustworthiness, and interpretability. Achieving widespread integration of AI/ML algorithms into diverse clinical tasks will demand a steadfast commitment to overcoming issues in model design, development, and performance assessment. The complexities of AI/ML clinical translation present substantial challenges, requiring engagement with relevant stakeholders, assessment of cost-effectiveness for user and patient benefit, timely dissemination of information relevant to robust functioning throughout the AI/ML lifecycle, consideration of regulatory compliance, and feedback loops for real-world performance evidence. This commentary addresses several hurdles for the development and adoption of AI/ML technologies in medical imaging. Comprehensive attention to these underlying and often subtle factors is critical not only for tackling the challenges but also for exploring novel opportunities for the advancement of AI in radiology.
Phase Ib Study of Unesbulin (PTC596) Plus Dacarbazine for the Treatment of Locally Recurrent, Unresectable or Metastatic, Relapsed or Refractory Leiomyosarcoma
Tine, Brian A. Van , Ingham, Matthew , Attia, Steven , Meyer, Christian F. , Baird, John D. , Brooks-Asplund, Esther M. , D'Silva, Dhiren, Kong, Ronald , Mwatha, Anthony, O’Keefe, Kylie, Weetall, Marla , Spiegel, Robert J. , Van Tine, Brian A , Ingham, Matthew A , Brooks-Asplund, Esther , Schwartz, Gary K , Meyer, Christian , Schwartz, Gary K.

Journal of Clinical Oncology | April 29, 2024 | Volume: 42 | Issue: 20 | Pages: 2404-2414

10.1200/jco.23.01684 | PMID 38684039 Get It

PURPOSE This multicenter, single-arm, open-label, phase Ib study was designed to determine the recommended phase II dose (RP2D) and to evaluate the safety and preliminary efficacy of unesbulin plus dacarbazine (DTIC) in patients with advanced leiomyosarcoma (LMS). PATIENTS AND METHODS Adult subjects with locally advanced, unresectable or metastatic, relapsed or refractory LMS were treated with escalating doses of unesbulin orally twice per week in combination with DTIC 1,000 mg/m2 intravenously (IV) once every 21 days. The time-to-event continual reassessment method was used to determine the RP2D on the basis of dose-limiting toxicities (DLTs) assessed during the first two 21-day treatment cycles. All explored doses of unesbulin (200 mg up to 400 mg) were in combination with DTIC. An expansion cohort was enrolled to evaluate the safety and efficacy of unesbulin at the RP2D. RESULTS Unesbulin 300 mg administered orally twice per week in combination with DTIC 1,000 mg/m2 IV once every 21 days was identified as the RP2D. On the basis of data from 27 subjects who were deemed DLT-evaluable, toxicity was higher in the unesbulin 400 mg group, with three of four subjects (75%) experiencing DLTs versus one of four subjects (25%) in the 200 mg group and three of 19 subjects (15.8%) in the 300 mg group. The most commonly reported DLTs and treatment-related grade 3 and 4 adverse events were thrombocytopenia and neutropenia. At the RP2D, seven subjects who were efficacy evaluable achieved partial response for an objective response rate of 24.1%. CONCLUSION Unesbulin 300 mg twice per week plus DTIC 1,000 mg/m2 once every 21 days was identified as the RP2D, demonstrating a favorable benefit-risk profile in a heavily pretreated population of adults with advanced LMS.