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Ramkumar, Prem N.

0000-0002-1704-9156

Mayo Clinic

Hospital for Special Surgery

Citations 2

Evaluating the Need for Preoperative MRI Before Primary Hip Arthroscopy in Patients 40 Years and Younger With Femoroacetabular Impingement Syndrome: A Multicenter Comparative Analysis
Berrier, Ava S., Helm, J. Matthew , Koolmees, Dylan S. , Pareek, Ayoosh , Nwachukwu, Benedict U. , Ramkumar, Prem N. , Krych, Aaron J. , Makhni, Eric Chugh , Harris, Joshua D.

Orthopaedic Journal of Sports Medicine | January 12, 2023 | Volume: 11 | Issue: 1 | Pages: No page available

10.1177/23259671221144776 Get It

Background: Routine hip magnetic resonance imaging (MRI) before arthroscopy for patients with femoroacetabular impingement syndrome (FAIS) offers questionable clinical benefit, delays surgery, and wastes resources. Purpose: To assess the clinical utility of preoperative hip MRI for patients aged ≤40 years who were undergoing primary hip arthroscopy and who had a history, physical examination findings, and radiographs concordant with FAIS. Study Design: Cohort study; Level of evidence, 3. Methods: Included were 1391 patients (mean age, 25.8 years; 63% female; mean body mass index, 25.6) who underwent hip arthroscopy between August 2015 and December 2021 by 1 of 4 fellowship-trained hip surgeons from 4 referral centers. Inclusion criteria were FAIS, primary surgery, and age ≤40 years. Exclusion criteria were MRI contraindication, reattempt of nonoperative management, and concomitant periacetabular osteotomy. Patients were stratified into those who were evaluated with preoperative MRI versus those without MRI. Those without MRI received an MRI before surgery without deviation from the established surgical plan. All preoperative MRI scans were compared with the office evaluation and intraoperative findings to assess agreement. Time from office to arthroscopy and/or MRI was recorded. MRI costs were calculated. Results: Of the study patients, 322 were not evaluated with MRI and 1069 were. MRI did not alter surgical or interoperative plans. Both groups had MRI findings demonstrating anterosuperior labral tears treated intraoperatively (99.8% repair, 0.2% debridement, and 0% reconstruction). Compared with patients who were evaluated with MRI and waited 63.0 ± 34.6 days, patients who were not evaluated with MRI underwent surgery 6.5 ± 18.7 days after preoperative MRI. MRI delayed surgery by 24.0 ± 5.3 days and cost a mean $2262 per patient. Conclusion: Preoperative MRI did not alter indications for primary hip arthroscopy in patients aged ≤40 years with a history, physical examination findings, and radiographs concordant with FAIS. Rather, MRI delayed surgery and wasted resources. Routine hip MRI acquisition for the younger population with primary FAIS with a typical presentation should be challenged.
Concerns surrounding application of artificial intelligence in hip and knee arthroplasty
Jain, Samagra, Pang, Michael , Karnuta, Jaret M. , Nawabi, Danyal H. , Polisetty, Teja S. , Vigdorchik, Jonathan M. , Wyles, Cody C. , Ramkumar, Prem N.

The Bone & Joint Journal | December 1, 2022 | Volume: 104-B | Issue: 12 | Pages: 1292-1303

10.1302/0301-620x.104b12.bjj-2022-0922.r1 Get It

Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered. Cite this article: Bone Joint J 2022;104-B(12):1292–1303.