Back to Authors

Chen, Tingyu

https://orcid.org/0009-0000-0092-0868

Mayo Clinic

Sichuan University

Citations 2

Magnetic Resonance Elastography Combined With PI‐RADS v2.1 for the Identification of Clinically Significant Prostate Cancer
Chen, Jie , Chen, Yuntian , Deng, Liping , Tang, Hehan , Zhang, Zhen , Chen, Tingyu , Zeng, Hao , Yuan, Enyu , Yao, Jin , Song, Bin , Yao, Jin , Chen, Guoyong , Yuan, Yuan , Yin, Meng , Chen, Jun

Journal of Magnetic Resonance Imaging | November 8, 2024 | Volume: 61 | Issue: 5 | Pages: 2248-2257

10.1002/jmri.29653 Get It

BackgroundMultiparametric MRI may cause overdiagnosis of clinically significant prostate cancer (csPCa) with the Prostate Imaging Reporting and Data System version 2.1 (PI‐RADS v2.1).ObjectivesTo investigate the diagnostic performance of stiffness as a standalone and complementary marker to PI‐RADS v2.1 for diagnosing csPCa.Study TypeProspective.SubjectsOne hundred forty‐seven participants with pathologically confirmed prostate lesions (≥1 cm), including 71 with csPCa.Field Strength/SequenceT1‐weighted fast spin‐echo, T2‐weighted fast spin‐echo, single‐shot echo‐planar diffusion‐weighted imaging, fast 3D gradient‐echo T1‐weighted dynamic contrast‐enhanced imaging, and 3D single‐shot spin‐echo based echo‐planar MR elastography at 3.0 T.AssessmentThe PI‐RADS v2.1 score was assessed by three radiologists independently. Lesion shear stiffness (SS) values at 60 Hz and 90 Hz were measured. A modified PI‐RADS integrating stiffness with PI‐RADS v2.1 was developed. Diagnostic performance for csPCa was compared between stiffness, PI‐RADS v2.1 and the modified PI‐RADS.Statistical TestSpearman's correlation, Fleiss κ and intraclass correlation, Pearson correlation, one‐way analysis of variance, area under the receiver operating characteristic curve (AUC), and the Delong test. Significance level was P < 0.05.ResultsIn the peripheral zone, csPCa (N = 35) had significantly higher SS than non‐csPCa at 60 Hz (3.22 ± 0.66 kPa vs. 2.56 ± 0.56 kPa) and at 90 Hz (5.64 ± 1.30 kPa vs. 4.48 ± 0.84 kPa). PI‐RADS v2.1 showed 100% sensitivity, 58% specificity, and 0.79 AUC for detecting csPCa. SS achieved 97% sensitivity, 52% specificity, and 0.80 AUC at 60 Hz, while SS had 63% sensitivity, 87% specificity, and 0.78 AUC at 90 Hz. The modified PI‐RADS, combing SS at 60 Hz with PI‐RADS v2.1, resulted in a significantly increased AUC (0.86) compared to that of PI‐RADS v2.1, with a sensitivity of 97% and specificity of 75%.Data ConclusionStiffness can help identifying csPCa in the peripheral zone. Combining stiffness with the PI‐RADS v2.1 improved the diagnostic accuracy and specificity for csPCa.Evidence Level1Technical EfficacyStage 2
Longitudinal graphics of physical function and other patient-reported outcomes in patients treated for hematologic malignancies 
Thanarajasingam, Gita , Chen, Tingyu , Hoffman, Ron, Mascarenhas, John , Murugappan, Meena N. , Ross, Joseph F., Warsame, Rahma , Dueck, Amylou C. , Dueck, A. C. , Bhatnagar, Vishal , Noble, Brie N. , Fiero, Mallorie H. , Jeffery, Molly Moore , Mazza, Gina L , Mascarenhas, John , Mesa, Ruben A. , Ross, Joseph, Sidana, Surbhi , Kluetz, Paul Gustav

No container title available | October 11, 2024 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.21203/rs.3.rs-4888383/v1 Get It

Abstract Background The US Food and Drug Administration (FDA) released a draft guidance document detailing core patient-reported outcomes in cancer clinical trials, including physical function (PF). This study aimed to develop analytic methods and visualizations of patient-reported PF in patients with cancer. Methods We applied an estimand framework to a patient-reported tolerability endpoint to develop data summaries cross-sectionally and over time, along with visualizations. We accomplished this through iterative feedback with clinicians, statisticians, and FDA stakeholders using three clinical trial datasets in hematologic malignancies. Graphical approaches were applied to three datasets in hematologic malignancies: (1) patients with myeloproliferative neoplasms enrolled in MPN-RC 111/112 trials completed EORTC QLQ-C30 over 12 months; (2) patients with hematologic malignancies undergoing CAR-T cell therapy or autologous transplant who completed FACT questionnaires over 6 months; and (3) patients with multiple myeloma or amyloidosis who completed the PROMIS-29 questionnaire over 6 months. Zoom polls were administered to two stakeholder groups (clinicians/clinical investigators and patient advocates) to elicit feedback. Results Visualizations included stacked bar charts, line plots of arithmetic mean changes from baseline, pie charts, waffle plots, and waterfall plots of PF data. Graphics considered scaled scores and individual items and included delineation of PRO completion rate at each time point. Confidence intervals and reference lines were included as applicable, and colorblind accessible colors were implemented to ensure inclusivity of all visualizations. Data summaries over time reporting “worst” change were difficult to interpret. In terms of stakeholders’ preference, patients preferred stacked bar charts while clinicians equally favored stacked bar charts and line plots; both patients and clinicians preferred waterfall plots to pie charts. Patient feedback highlighted the need for various graphics to convey group level trends and granular individual-patient level information. Conclusion Patient-reported PF informs the evaluation of treatment tolerability in cancer trials. Data summaries and visualizations of physical function developed through an iterative process were reviewed favorably by patients, clinicians and FDA stakeholders in this study. Future work to systematically assess accuracy of interpretation of the various analytic and visualization methods is a necessary next step across clinical, regulatory, payer and patient stakeholders. Trial registration NCT01259817, NCT01259856