Fully automated assessment of the knee alignment on long leg radiographs following corrective knee osteotomies in patients with valgus or varus deformities.

INTRODUCTION: The assessment of the knee alignment on long leg radiographs (LLR) postoperative to corrective knee osteotomies (CKOs) is highly dependent on the reader's expertise. Artificial Intelligence (AI) algorithms may help automate and standardise this process. The study aimed to analyse the reliability of an AI-algorithm for the evaluation of LLRs following CKOs. MATERIALS AND METHODS: In this study, we analysed a validation cohort of 110 postoperative LLRs from 102 patients. All patients underwent CKO, including distal femoral (DFO), high tibial (HTO) and bilevel osteotomies. The agreement between manual measurements and the AI-algorithm was assessed for the mechanical axis deviation (MAD), hip knee ankle angle (HKA), anatomical-mechanical-axis-angle (AMA), joint line convergence angle (JLCA), mechanical lateral proximal femur angle (mLPFA), mechanical lateral distal femoral angle (mLDFA), mechanical medial proximal tibia angle (mMPTA) and mechanical lateral distal tibia angle (mLDTA), using the intra-class-correlation (ICC) coefficient between the readers, each reader and the AI and the mean of the manual reads and the AI-algorithm and Bland-Altman Plots between the manual reads and the AI software for the MAD, HKA, mLDFA and mMPTA. RESULTS: In the validation cohort, the AI software showed excellent agreement with the manual reads (ICC: 0.81-0.99). The agreement between the readers (Inter-rater) showed excellent correlations (ICC: 0.95-0. The mean difference in the DFO group for the MAD, HKA, mLDFA and mMPTA were 0.50 mm, - 0.12°, 0.55° and 0.15°. In the HTO group the mean difference for the MAD, HKA, mLDFA and mMPTA were 0.36 mm, - 0.17°, 0.57° and 0.08°, respectively. Reliable outputs were generated in 95.4% of the validation cohort. CONCLUSION:  he application of AI-algorithms for the assessment of lower limb alignment on LLRs following CKOs shows reliable and accurate results. LEVEL OF EVIDENCE: Diagnostic Level III.

Gender-specific distribution of knee morphology according to CPAK and functional phenotype classification: analysis of 8739 osteoarthritic knees prior to total knee arthroplasty using artificial intelligence.

PURPOSE: Osteoarthritis of the knee is commonly associated with malalignment of the lower limb. Recent classifications, as the Coronal Plane Alignment of the Knee (CPAK) and Functional Phenotype classification, describe the bony knee morphology in addition to the overall limb alignment. Data on distribution of these classifications is not sufficient in large populations. The aim of this study was to analyse the preoperative knee morphology with regard to the aforementioned classifications in long leg radiographs prior to total knee arthroplasty surgery using Artificial Intelligence. METHODS: The cohort comprised 8739 preoperative long leg radiographs of 7456 patients of all total knee arthroplasty surgeries between 2009 and 2021 from our institutional database. The automated measurements were performed with the validated Artificial Intelligence software LAMA (ImageBiopsy Lab, Vienna) and included standardized axes and angles [hip-knee-ankle angle (HKA), mechanical lateral distal femur angle (mLDFA), mechanical medial proximal tibia angle (mMPTA), mechanical axis deviation (MAD), anatomic mechanic axis deviation (AMA) and joint line convergence angle (JLCA)]. CPAK and functional phenotype classifications were performed and all measurements were analysed for gender, age, and body mass index (BMI) within these subgroups. RESULTS: Varus alignment was more common in men (m: 2008, 68.5%; f: 2953, 50.8%) while neutral (m: 578, 19.7%; f: 1357, 23.4%) and valgus (m: 345, 11.8%; f: 1498, 25.8%) alignment was more common in women. The most common morphotypes according to CPAK classification were CPAK Type I (2454; 28.1%), Type II (2383; 27.3%), and Type III (1830; 20.9%). An apex proximal joint line (CPAK Type VII, VIII and IX) was only found in 1.3% of all cases (n = 121). In men, CPAK Type I (1136; 38.8%) and CPAK Type II (799; 27.3%) were the most common types and women were spread more equally between CPAK Type I (1318; 22.7%), Type II (1584; 27.3%) and Type III (1494; 25.7%) (p < 0.001). The most common combination of femur and tibia types was NEUmLDFA0°,NEUmMPTA0° (m: 514, 17.5%; f: 1004, 17.3%), but men showed femoral varus more often. Patients with a higher BMI showed a significantly lower age at surgery (R2 = 0.09, p < 0.001). There were significant differences between men and women for all radiographic parameters (p < 0.001). CONCLUSION: Distribution in knee morphology with gender-specific differences highlights the wide range in osteoarthritic knees, characterized by CPAK and phenotype classification and may influence future surgical planning. LEVEL OF EVIDENCE: Level III.

Can an artificial intelligence powered software reliably assess pelvic radiographs?

PURPOSE: Despite advances of three-dimensional imaging pelvic radiographs remain the cornerstone in the evaluation of the hip joint. However, large inter- and intra-rater variabilities were reported due to subjective landmark setting. Artificial intelligence (AI)-powered software applications could improve the reproducibility of pelvic radiograph evaluation by providing standardized measurements. The aim of this study was to evaluate the reliability and agreement of a newly developed AI algorithm for the evaluation of pelvic radiographs. METHODS: Three-hundred pelvic radiographs from 280 patients with different degrees of acetabular coverage and osteoarthritis (Tönnis Grade 0 to 3) were evaluated. Reliability and agreement between manual measurements and the outputs of the AI software were assessed for the lateral-center-edge (LCE) angle, neck-shaft angle, sharp angle, acetabular index, as well as the femoral head extrusion index. RESULTS: The AI software provided reliable results in 94.3% (283/300). The ICC values ranged between 0.73 for the Acetabular Index to 0.80 for the LCE Angle. Agreement between readers and AI outputs, given by the standard error of measurement (SEM), was good for hips with normal coverage (LCE-SEM: 3.4°) and no osteoarthritis (LCE-SEM: 3.3°) and worse for hips with undercoverage (LCE-SEM: 5.2°) or severe osteoarthritis (LCE-SEM: 5.1°). CONCLUSION: AI-powered applications are a reliable alternative to manual evaluation of pelvic radiographs. While being accurate for patients with normal acetabular coverage and mild signs of osteoarthritis, it needs improvement in the evaluation of patients with hip dysplasia and severe osteoarthritis.

Clinical impact of microbiological results in two-stage revision arthroplasty with spacer exchange.

INTRODUCTION: Patients who require a spacer exchange as part of a two-stage procedure for the treatment of periprosthetic hip and knee joint infections (PJI) have high failure rates. Little is known about the clinical impact of microbiological results and changes in the microbiological spectrum and resistance pattern in these patients. MATERIAL AND METHODS: Between 01/2011 and 12/2019, 312 patients underwent a total of 327 two-stage revision arthroplasties at our institution. A spacer exchange was required in 52/312 (16.7%) patients (27 knee/25 hip). Microbiological results, antibiotic resistance patterns, patient's host factors as well as re-revision and re-infection rates at a median follow-up of 47.8 months (range 12.2-116.7 months) were analyzed. A propensity score (PS)-matched analysis of patients who underwent spacer exchange and patients treated with standard two-stage procedure was performed. RESULTS: We found a high number of microbiological spectrum changes in patients with multiple culture positive procedures between explantations and spacer exchanges (10/12 [83.3%]), spacer exchanges and reimplantations (3/4 [75%]) as well as between reimplantations and subsequent re-revision surgeries (5/6 [83.3%]). In 9/52 (17.3%) patients, same microorganisms were detected repeatedly in two different procedures. We observed changes in the antibiotic resistance patterns in 6/9 (66.7%) of these patients. High re-infection rates were found in patients with culture positive reimplantations (10/12 [83.3%]), and low re-infection rates were found in patients with culture negative reimplantations (2/40 [5%]; p < 0.001). Between patients with and without spacer exchange, no differences were found in the re-revision rates (13/52 [25%] with vs. 13/52 [25%] without; p = 1.00) as well as re-infection rates (12/52 [23.1%] with vs. 8/52 [15.4%] without; p = 0.32). CONCLUSIONS: Changes in microbiological spectrum and antibiotic resistance patterns between stages are common in patients who require a spacer exchange. If eradication of the microorganism at reimplantation can be accomplished, comparable re-revision rates to standard two-stage procedures can be achieved.

Chondrosarcoma of the spine-a case report.

CASE: A 73-year-old male patient presented with a 3-month history of back pain. In bone scintigraphy and the FDG PET-CT scan (fluorodeoxyglucose positron-emission computed tomography), highly suspect uptake levels were found in TH12-L1. Accordingly, an osteodestructive process was found on MRI (magnetic resonance imaging). Following a successfully performed biopsy of TH12, histologic analysis of the bone material revealed a chondrosarcoma (G1; T4N2M0). Complete resection of the tumor was successfully performed, since chondrosarcoma are resistant to radiation and chemotherapy. CONCLUSION: As chondrosarcoma is a rare bone neoplasm, it must be considered in the differential diagnosis of lower back pain to initiate adequate treatment.

Alpha-defensin as a diagnostic tool in revision total knee arthroplasties with unexpected positive intraoperative cultures and unexpected culture negative intraoperative cultures.

PURPOSE: Unexpected-positive-intraoperative-cultures (UPIC) are common in presumed aseptic revision-total-knee-arthroplasties (rTKA). However, the clinical significance is not entirely clear. In contrast, in some presumably septic rTKA, identification of an underlying pathogen was not possible, so-called unexpected-negative-intraoperative-cultures (UNIC). The purpose of this study was to evaluate the potential use of synovial alpha-defensin (AD) levels in these patients. METHODS: Synovial AD levels from 143 rTKAs were evaluated retrospectively from our prospectively maintained institutional periprostetic joint infection (PJI) biobank and database. The 2018-International Consensus Meeting (ICM) criteria was used to define the study groups. Samples from UPICs with a minimum of one positive intraoperative culture (ICM 2- ≥ 6) (n = 20) and UNIC's (ICM ≥ 6) (n = 14) were compared to 34 septic culture-positive samples (ICM ≥ 6) and 75 aseptic culture-negative (ICM 0-1). Moreover, AD-lateral-flow-assay (ADLF) and an enzyme-linked-immunosorbent-assay (ELISA) in detecting the presence of AD in native and centrifuged synovial fluid specimens was performed. Concentration of AD determined by ELISA and ADLF methods, as well as microbiological, and histopathological results, serum and synovial parameters along with demographic factors were analysed. RESULTS: AD was positive in 31/34 (91.2%) samples from the septic culture-positive group and in 14/14 (100%) samples in the UNIC group. All UPIC samples showed a negative AD result. Positive AD samples were highly associated with culture positive and histopathological results (p < 0.001). No high-virulent microorganisms (0/20) were present in the UPIC group, compared to infected-group (19/34; 55.9%). High virulent microorganisms showed a positive AD result in 89.5% (17/19) of the cases. Methicillin resistant Staphylococcus epidermis (MRSE) infections had significantly higher AD levels than with methicillin susceptible S. epidermdis (MSSE) (p = 0.003). ELISA and ADLF tests were positive with centrifuged (8/8) and native (8/8) synovial fluid. CONCLUSION: AD showed a solid diagnostic performance in infected and non-infected revisions, and it provided an additional value in the diagnosis of UPIC and UNIC associated to rTKAs. Pathogen virulence as well as antibiotic resistance pattern may have an effect on AD levels. Centrifugation of synovial fluid had no influence on ADLF results.

Changes in microbiological spectrum and antibiotic susceptibility in two-stage exchange for periprosthetic shoulder infections.

BACKGROUND: Periprosthetic joint infections (PJI) are a major concern in shoulder arthroplasty, which in some cases require two-stage exchange. While it was shown that low-virulence bacteria are the most isolated pathogens in shoulder PJI, little is known about changes in microbiological spectrum and resistance patterns during two-stage revision. METHODS: This retrospective study included all patients (n = 25) who received a two-stage revision from January 2011 to December 2020 for shoulder PJI in one institution. Microbiological spectrum, antimicrobial resistance patterns, and re-revision rates of culture positive first- and second-stage procedures were analyzed. The mean follow-up time was 29.7 months (range 8; 115 months). At final follow-up, subjective shoulder value (SSV) and visual analog scale (VAS) score for pain and satisfaction with the surgery were assessed. RESULTS: In 25 patients, a total of 54 2-stage exchange procedures were performed and positive cultures were obtained in 36 of these surgeries (66.7%). A total of 7 out of 25 patients (28.0%) showed a positive microbiological culture at first and second stages. In those patients, the mean time between first and second stages was 30.9 weeks (range 6; 70). Three out of those seven patients (42.9%) had a polymicrobial spectrum with one microorganism persistent at stage two, including Cutibacterium acnes (n = 1) and Staphylococcus epidermidis (MRSE) (n = 2). In all these cases, antimicrobial resistance patterns changed. All cultures with monomicrobial spectrum (n = 4) at first stage showed a changed spectrum. Patients with positive first- and second-stage revisions showed a mean SSV of 49.3% ± 23.5 versus 52.9% ± 29.5 in single positive patients (p = 0.76). Re-revision was performed in five cases, two of those in patients with positive first- and second-stage cultures. CONCLUSION: There is a high rate of changes in microbiological spectrum and resistance patterns between culture positive first- and second-stage procedures as well as subsequent re-revisions. Intraoperative samples during reimplantation should be taken and resistance reconsidered in case of re-revision.

Changes of the microbiological spectrum and antibiotic resistance pattern in postoperative spinal implant infections with multiple culture-positive revision surgeries.

BACKGROUND CONTEXT: In severe cases of postoperative spinal implant infections (PSII) multiple revision surgeries may be needed. Little is known if changes in the microbiological spectrum and antibiotic resistance pattern occur between revision surgeries. PURPOSE: Analysis of the microbiological spectrum and antibiotic resistance pattern in patients with multiple revision surgeries for the treatment of PSII STUDY DESIGN: Retrospective database analysis. PATIENT SAMPLE: Between 01/2011 and 12/2018, 103 patients underwent 248 revision surgeries for the treatment of PSII. Twenty patients (19.4%) who underwent multiple revision surgeries for PSII were included in this study. OUTCOME MEASURES: Microbiological spectrum, antibiotic resistance pattern. METHODS: A retrospective analysis of a prospectively maintained single center spine infection database was performed with a minimum follow-up of 3 years. Overall, 20 patients (six male/14 female) underwent 82 revisions for PSII (median 3; range 2-12). There were 55 of 82 (67.1%) procedures with a positive microbiological result. Microbiological analysis was performed on tissue and implant sonication fluid. Changes in microbial spectrum and antibiotic resistance pattern between surgeries were evaluated using Chi-Square and Fisher's exact test. RESULTS: In total, 74 microorganisms (83.3% gram-positive; 10.8% gram-negative) were identified. The most common microorganisms were Staphylococcus epidermidis (18.9%) and Cutibacterium acnes (18.9%). All S. epidermidis identified were methicillin-resistant (MRSE). Overall, there were 15 of 55 (27.3%) polymicrobial infections. The microbiological spectrum changed in 57.1% (20/35) between the revision stages over the entire PSII period. In 42.9% (15/35) the microorganism persisted between the revision surgeries stages. Overall, changes of the antibiotic resistance pattern were seen in 17.4% (8/46) of the detected microorganisms, comparing index revision and all subsequent re-revisions. Moreover, higher resistance rates were found for moxifloxacin and for ciprofloxacin at first re-revision surgery compared with index PSII revision. Resistances against vancomycin increased from 4.5% (1/23) at index PSII revision to 7.7% (2/26) at first re-revision surgery. CONCLUSIONS: Changes of the microbiological spectrum and the resistance pattern can occur in patients with severe PSII who require multiple revision surgeries. It is important to consider these findings in the antimicrobial treatment of PSII. The microbiological analysis of intraoperative tissue samples should be performed at every revision procedure for PSII.

Artificial intelligence enables reliable and standardized measurements of implant alignment in long leg radiographs with total knee arthroplasties.

PURPOSE: The purpose of this study was to evaluate the reliability of a newly developed AI-algorithm for the evaluation of long leg radiographs (LLR) after total knee arthroplasties (TKA). METHODS: In the validation cohort 200 calibrated LLRs of eight different common unconstrained and constrained knee systems were analysed. Accuracy and reproducibility of the AI-algorithm were compared to manual reads regarding the hip-knee-ankle (HKA) as well as femoral (FCA) and tibial component (TCA) angles. In the evaluation cohort all institutional LLRs with TKAs in 2018 (n = 1312) were evaluated to assess the algorithms' ability of handling large data sets. Intraclass correlation (ICC) coefficient and mean absolute deviation (sMAD) were calculated to assess conformity between the AI software and manual reads. RESULTS: Validation cohort: The AI-software was reproducible on 96% and reliable on 92.1% of LLRs with an output and showed excellent reliability in all measured angles (ICC > 0.97) compared to manual measurements. Excellent results were found for primary unconstrained TKAs. In constrained TKAs landmark setting on the femoral and tibial component failed in 12.5% of LLRs (n = 9). Evaluation cohort: Mean measurements for all postoperative TKAs (n = 1240) were 0.2° varus ± 2.5° (HKA), 89.3° ± 1.9° (FCA), and 89.1° ± 1.6° (TCA). Mean measurements on preoperative revision TKAs (n = 74) were 1.6 varus ± 6.4° (HKA), 90.5° ± 3.1° (FCA), and 88.9° ± 4.1° (TCA). CONCLUSIONS: AI-powered applications are reliable for automated analysis of lower limb alignment on LLRs with TKAs. They are capable of handling large data sets and could, therefore, lead to more standardized and efficient postoperative quality controls. LEVEL OF EVIDENCE: Diagnostic Level III.

Differential microbiological spectrum and resistance pattern in periprosthetic hip joint infections: a matched-cohort analysis comparing direct anterior versus lateral approach.

BACKGROUND: In recent years, total hip arthroplasty via the direct anterior approach (DAA) has become more common. Little is known on the influence of the surgical approach on the microbiological spectrum and resistance pattern in periprosthetic hip joint infections. The aim of the present study was to evaluate the microbiological spectrum and resistance pattern in periprosthetic hip joint infections comparing the direct anterior versus lateral approach in a matched-cohort analysis at a single institution. METHODS: Patients who underwent revision hip arthroplasty due to PJI following primary total hip arthroplasty with culture positive microbiology were analyzed. In all study patients, both the primary surgery and the revisions surgery were performed at the same institution. Only patients in whom primary surgery was performed via a direct anterior or lateral approach were included (n = 87). A matched cohort analysis was performed to compare the microbiological spectrum and resistance pattern in PJI following direct anterior (n = 36) versus lateral (n = 36) primary THA. RESULTS: We identified both a significantly different microbiological spectrum and resistance pattern in PJI comparing direct anterior versus lateral approach THA. Cutibacterium avidum was obtained more frequently in the anterior subgroup (22.2% vs. 2.8%, p = 0.028). In the subgroup of infections with Staphylococcus aureus (n = 12), methicillin resistance was detected in 3/5 cases in the direct anterior group versus 0/7 cases in the lateral group (p = 0.045). Overall, Staphylococcus epidermidis was the most common causative microorganism in both groups (direct anterior: 36.1%; lateral: 27.8%, p = 0.448). CONCLUSION: The present study indicates a potential influence of the localization of the skin incision in THA on the microbiological spectrum and resistance pattern in PJI. Cutibacterium avidum seemed to be a more common causative microorganism in PJI in patients who underwent direct anterior compared to lateral approach THA.

Analysis of Culture Positive First and Second Stage Procedures in Periprosthetic Knee and Hip Joint Infections.

BACKGROUND: A positive microbiological result at reimplantation may lead to a failed 2-stage revision arthroplasty in the treatment of periprosthetic joint infections. Little is known about changes in microbiological spectrum and resistance pattern between culture positive first and second stage procedures in revision knee and hip arthroplasty. METHODS: Between January 2011 and December 2019, we performed 327 two-stage revision arthroplasties on 312 patients. There were 37 of 312 (11.9%) patients (20 hips/17 knees) who had a positive microbiological culture during the first and second stage procedure. We analyzed the microbiological spectrum, antimicrobial resistance pattern, and clinical outcome of culture positive first and second stage procedures as well as subsequent re-revisions. RESULTS: Re-revision was necessary in 40.5% (15/37) of patients with culture positive first and second stage procedure at a median follow-up of 3.5 years. We found microbiological changes in 83.8% (31/37) of patients between the first and second stage and in 88.9% (8/9) between the second stage and subsequent culture positive re-revision. Polymicrobial infections were found in 21.6% (8/37) of first and in 16.2% (6/37) of second stage procedures. In 27% (10/37) of patients, microorganisms persisted between the first and second stage procedure. The antimicrobial resistance pattern changed in 60% of persistent microorganisms between the first and second stage procedure. CONCLUSION: Changes in microbiological spectrum and resistance pattern are common between culture positive first and second stage procedures as well as subsequent re-revisions. This has to be considered in the antimicrobial treatment of periprosthetic joint infections.

Beating cancer-related fatigue with the Untire mobile app: Results from a waiting-list randomized controlled trial.

OBJECTIVE: This waiting-list randomized controlled trial examined the effectiveness of a self-management mHealth app in improving fatigue and quality of life (QoL) in cancer patients and survivors. METHODS: Persons with cancer-related fatigue (CRF) were recruited across four English speaking countries, via social media, and randomized into intervention (n = 519) and control (n = 280) groups. Whereas the intervention group received immediate access to the Untire app, the control group received access only after 12-weeks. Primary outcomes fatigue severity and interference, and secondary outcome QoL were assessed at baseline, 4, 8, and 12-weeks. We ran generalized linear mixed models for all outcomes to determine the effects of app access (yes/no), over 12-weeks, following the intention-to-treat principle. RESULTS: Compared with the control group, the intervention group showed significantly larger improvements in fatigue severity (d = 0.40), fatigue interference (d = 0.35), and overall QoL on average (d = 0.32) (P's < .01), but not for overall QoL in the past week (P = .07). Sensitivity analyses indicated that participants with medium or high app use benefited most when compared with nonusers and control participants (P's ≤ .02). The intervention effect on fatigue interference was slightly stronger in younger participants (≤56 vs. >56). Effects did not depend on education and cancer status. Reliable change analyses indicated that significantly more people showed full recovery for fatigue in the intervention vs the control group (P's = .02). CONCLUSIONS: The Untire app can be an effective mHealth solution for cancer patients and survivors with moderate to severe CRF.

Influence of the induced membrane filled with syngeneic bone and regenerative cells on bone healing in a critical size defect model of the rat's femur.

INTRODUCTION: The induced membrane technique for the treatment of large bone defects consists of a 2-stage procedure. In the first stage, a polymethylmethacrylate (PMMA) cement spacer is inserted into the bony defect of a rat's femur and over a period of 2-4 weeks a membrane forms that encapsulates the defect/spacer. In a second operation the membrane is opened, the PMMA spacer is removed and the resulting cavity is filled with autologous bone. Since little effort has been made to replace the need for autologous bone this study was performed to elucidate the influence of different stem cells and the membrane itself on bone healing in a critical size femur defect model in rats. Especially the question should be addressed whether the use of stem cells seeded on a ß-TCP scaffold is equivalent to syngeneic bone as defect filling in combination with the induced membrane technique. MATERIALS AND METHODS: A total of 96 male Sprague-Dawley (SD) rats received a 10 mm critical size defect of the femur, which was stabilized by a plate osteosynthesis and filled with PMMA cement. In a second step the spacer was extracted and the defects were filled with syngeneic bone, ß-TCP with MSC + EPC or BM-MNC. In order to elucidate the influence of the induced membrane on bone defect healing the induced membrane was removed in half of the operated femurs. The defect area was analysed 8 weeks later for bone formation (osteocalcin staining), bone mineral density (BMD) and bone strength (3-point bending test). RESULTS: New bone formation, bone mineral density and bone stiffness increased significantly, if the membrane was kept. The transplantation of biologically active material (syngeneic bone, stem cells on b-TCP) into the bone defect mostly led to a further increase of bone healing. Syngeneic bone had the greatest impact on bone healing however defects treated with stem cells were oftentimes comparable. CONCLUSION: For the first time we demonstrated the effect of the induced membrane itself and different stem cells on critical size defect healing. This could be a promising approach to reduce the need for autologous bone transplantation with its' limited availability and donor site morbidity.