Browsing by Author "Sperling, John W."

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    Artificial intelligence to automatically measure glenoid inclination, humeral alignment, and the lateralization and distalization shoulder angles on postoperative radiographs after reverse shoulder arthroplasty
    (Elsevier Inc., 2024) Linjun, Yang; De Marinis Acle, Rodrigo Ignacio; Yu, Kristin; Marigi, Erick; Oeding, Jacob F.; Sperling, John W.; Sánchez-Sotelo, Joaquín
    Background: Radiographic evaluation of the implant configuration after reverse shoulderarthroplasty (RSA) is time-consuming and subject to interobserver disagreement. The finalconfiguration is a combination of implant features and surgical execution. Artificial intel ligence (AI) algorithms have been shown to perform accurate and efficient analysis ofimages. The purpose of this study was to develop an AI algorithm to automatically measureglenosphere inclination, humeral component inclination, and the lateralization and dis talization shoulder angles (DSAs) on postoperative anteroposterior radiographs after RSA.Methods: The Digital Imaging and Communications in Medicine files corresponding topostoperative anteroposterior radiographs obtained after implantation of 143 RSAs wereretrieved and used in this study. Four angles were analyzed: (1) glenoid inclination angle(GIA, between the central fixation feature of the glenoid and the floor of the supraspinatusfossa), (2) humeral alignment angle (HAA, between the long axis of the humeral shaft and aperpendicular to the metallic bearing of the prosthesis), (3) DSA, and (4) lateralizationshoulder angle (LSA). A UNet segmentation model was trained to segment bony and implant elements using manually segmented training (n ¼ 89) and validation (n ¼ 22) images. Then, an image-processingebased pipeline was developed to measure all 4 angles using AI-segmented images. Measures performed by 3 physician observers and the AI algorithm were then completed in 32 additional images. The agreements among human observers and between observers and the AI algorithm were evaluated using intraclass correlation coefficients (ICCs) and absolute differences in degree. Results: The ICCs (95% confidence interval) for manual measurements of LSA, DSA, GIA, and HAA were 0.79 (0.55, 0.90), 0.90 (0.80, 0.95), 0.96 (0.93, 0.98), and 0.99 (0.97, 0.99), respectively. The AI algorithm measured the 32 images in the test set in less than 2 minutes. The agreement between observers and the AI algorithm was lowest when measuring the LSA for observer 2, with an ICC of 0.77 (0.52, 0.89), and an absolute difference in degrees (median [interquartile range]) of 5 (4). Better agreements were found between the AI measurements and the average manual measurements: absolute differences in degree for LSA, DSA, GIA, and HAA were 3 (5), 2 (3), 2 (2), and 2 (1), respectively; ICCs for LSA, DSA, GIA, and HAA were 0.89 (0.79, 0.95), 0.96 (0.93, 0.98), 0.85 (0.68, 0.93), and 0.98 (0.95, 0.99), respectively. Conclusion: The AI algorithm developed in this study can automatically measure the GIA, HAA, LSA, and DSA on postoperative anteroposterior radiographs obtained after implantation on RSA.
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    Cement-within-cement technique in revision reverse total shoulder arthroplasty: complications, reoperations, and revision rates at 5-year mean follow-up
    (Elsevier Inc., 2025) Marinis Acle, Rodrigo Ignacio de; Sperling, John W.; Marigi, Erick M.; Velasquez Garcia, Ausberto; Wagner, Eric R.; Sanchez-Sotelo, Joaquin
    Background: Revision reverse total shoulder arthroplasty (rTSA) of a previously cemented humeral component is challenging. In hip arthroplasty, the cement-within-cement (CwC) technique has been well described as an effective option. However, for shoulder arthroplasty there remains a paucity of data investigating this technique. The purpose of this study was to determine the mid-term outcomes of patients who underwent a revision rTSA utilizing the CwC for management of the humeral component. Methods: Between 2005 and 2021, 68 revision rTSA using the CwC technique with a minimum of 2 years clinical follow-up were identified from a single institution joint registry database. Revised implants consisted of 38 (55.9%) hemiarthroplasties, 22 (32.4%) anatomic total shoulder arthroplasties, and 8 (11.8%) rTSA. A total of 12 (17.6%) shoulders required an osteotomy (corticotomy or window) to assist with extraction of the cemented stem. The mean follow-up after revision was 5.4 years (range, 2-16 years). Surgical complications, reoperations, revisions, and implant survivorship were assessed. Results: Of the 12 shoulders that required an osteotomy for component removal, 11 (91.7%) were healed. At final follow-up, the overall complication rate was 26.9%. The most common complication was fracture or fragmentation of the greater tuberosity (20.6%, n = 13) with 10 (76.9%) cases showing signs of healing at final follow-up. The overall survivorship free of revision surgery was 88.2% at 2 and 80.9% at 5 years, respectively. The most frequent causes of re-revision surgery were aseptic glenoid component loosening (n = 4) and instability (n = 4), with only 2 (2.9%) patients developing humeral component loosening (at 2 and 5 years, respectively). Male sex was associated with an increased risk of revision surgery (hazard ratio [HR], 3.52 [95% confidence interval [CI] 1.22-10.18]; P = .02) and complications (HR, 3.56 [95% CI, 1.40-9.07]; P = .008). The grade of postoperative lucent lines at the humerus (HR, 1.35 [95% CI, 1.04-1.74]; P = .02) and glenoid (HR, 1.59 [95% CI, 1.22-2.10]; P = .001) also correlated with an increased risk of re-revision surgery. Conclusion: The CwC technique is a reliable option for revising previously cemented humeral components in revision rTSA. Although a low rate of humeral component loosening was observed, higher rates of complications and re-revision surgery were observed over time secondary to aseptic glenoid component loosening and instability, which are not directly related to CwC technique but to revision surgery in general.
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    Current Clinical Applications of Artificial Intelligence in Shoulder Surgery: What the Busy Shoulder Surgeon Needs to Know and What’s Coming Next
    (2023) De Marinis Acle Rodrigo Ignacio; Marigi, Erick M.; Atwan, Yousif; Yang, Linjun; Oeding, Jacob F.; Gupta, Puneet; Pareek, Ayoosh; Sanchez-Sotelo, Joaquin; Sperling, John W.
    Artificial intelligence (AI) is a continuously expanding field with the potential to transform a variety of industries -including healthcare- by providing automation, efficiency, precision, accuracy, and decision-making support for simple and complex tasks. Basic knowledge of the key features as well as limitations of AI is paramount to understand current developments in this field and to successfully apply them to shoulder surgery. The purpose of the present review is to provide an overview of artificial intelligence within orthopedics and shoulder surgery exploring current and forthcoming AI applications.
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    Early complications of operatively treated proximal humeral fractures
    (MOSBY-ELSEVIER, 2007) Smith, Adam M.; Mardones, Rodrigo M.; Sperling, John W.; Cofield, Robert H.
    Minimal information exists regarding early complications after operatively treated proximal humeral fractures. Of the 82 shoulders that hod osteosynthesis, 42 had a (nonmedical) complication, with 2 1 requiring further surgery. Of 42 shoulders with complications, 72 were related to incomplete reduction, 16 had loss of anatomic fracture fixation, 9 had delayed healing, 3 had an infection, 1 had rotator cuff failure, and 1 had loose bodies. Fixed-angle plates had lower rates of initial malpositioning and resultant malunion. Of the 22 shoulders requiring hemiarthroplasty, 14 had an early complication. Of these, 7 had complications relating to implant insertion or tuberosity malreduction at the index operation and 7 had problems with tuberosity healing. The rate of complications after operative treatment of proximal humeral fractures is high. All efforts at fracture fragment fixation with osteosynthesis and hemiarthroplasty should be directed at obtaining anatomic fracture fixation that resists displacement.
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    Reverse Shoulder Arthroplasty Megaprosthesis for Surgical Management of Severe Proximal Humeral Bone Loss
    (2024) Labrum, IV, Joseph T.; De Marinis Acle Rodrigo Ignacio; Atwan, Yousif; Marigi, Erick M.; Houdek, Matthew T.; Barlow, Jonathon D.; Morrey, Mark E.; Sanchez-Sotelo, Joaquin; Sperling, John W.
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    Venous Thromboembolism Following Surgical Management of Proximal Humerus Fractures: A Systematic Review
    (2023) Marigi, Erick M.; Sperling, John W.; Marinis Acle, Rodrigo Ignacio de; Gupta, Puneet; Hassett, Leslie C.; Soza Rex Jose Francisco; Sánchez-Sotelo, Joaquín
    Currently, there is limited information on the incidence of venous thromboembolism (VTE), including deep vein thrombosis (DVT) and pulmonary embolism (PE) after surgical treatment of proximal humerus fractures (PHFs). Therefore, the purpose of this systematic review is to evaluate the incidence of VTE, DVT, and PE following surgery for PHFs.