Dynamic CT–Based Quantification of Patellofemoral Contact Area Following Cartilage Removal: An Ex Vivo Study

Dynamic CT–Based Quantification of Patellofemoral Contact Area Following Cartilage Removal: An Ex Vivo Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Dynamic CT–Based Quantification of Patellofemoral Contact Area Following Cartilage Removal: An Ex Vivo Study Manou Acke, Benyameen Keelson, Thierry Scheerlinck, Nicolas Van Vlasselaer, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7121995/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Knee osteoarthritis (OA) is a musculoskeletal disorder characterised by abnormal joint motion, joint space narrowing, and cartilage degeneration. Early diagnosis is important to slow disease progression. Dynamic CT imaging adds three-dimensional functional information to an otherwise static diagnosis. This study investigates the diagnostic potential of inter-articular contact area during knee motion across three stages of cartilage degeneration. Methods Cartilage was progressively removed from the patellofemoral joint of a cadaveric knee to simulate stages of cartilage degeneration: first laterally, then at the crista, and finally medially. After each intervention, dynamic CT was performed during induced cyclic flexion-extension motion of the cadaveric knee. We quantified contact area dynamically by measuring distances between intact cartilage layers of the patella and femur. Contact areas across stages (baseline, lateral, crista, medial) were compared using the Wilcoxon Signed Rank test at six knee flexion angles (0°, 5°, 10°, 15°, 20°, 25°). Reproducibility was assessed by repeating the dynamic CT acquisition post-cartilage removal three times. Results Contact area increased significantly at each stage of cartilage degeneration compared to the previous stage (p < 0.05), progressing from 0 mm² to 84.2 mm², 176.0 mm², and 308.7 mm². For reproducibility, the standard error of the mean across three repetitions showed an average deviation of 6%. Differences varied across knee angles, with the least distinction observed in full extension. Spatially, the contact areas corresponded anatomically to the regions of cartilage removal. Conclusion Progressive cartilage removal in a cadaveric knee results in a significant increase in contact area. Health sciences/Anatomy Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Health sciences/Rheumatology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 INTRODUCTION Knee osteoarthritis (OA) is a common musculoskeletal disorder, affecting 16% of the global population [ 1 ]. The prevalence of these disorders is expected to rise further due to the aging global population, underscoring the need for effective prevention, diagnosis, and treatment strategies. Early diagnosis can slow disease progression and enhance patients' quality of life [ 11 ]. Knee osteoarthritis is caused by uneven pressure distribution and abnormal joint movement. Over time, these factors lead to cartilage thinning, joint space narrowing, and increased bone-on-bone friction [ 1 , 16 ]. Quantifying the extent of these structural and kinematic changes can provide an early diagnosis for osteoarthritis. A range of assessment methods have been introduced for the diagnosis and quantification of knee OA, broadly categorized into image-based and non-image-based approaches. Non-image-based methods include electromyography (EMG) for assessing muscle activity and motion capture systems for evaluating joint kinematics [ 4 , 19 ]. However, these approaches are often limited by inaccuracy or impracticality [ 14 , 22 ]. Invasive marker-based techniques are more accurate but unsuitable for clinical application [ 14 , 22 ]. Image-based techniques, such as radiography, ultrasound, MRI, fluoroscopy, and CT, are routinely employed to diagnose musculoskeletal disorders (MSDs) by investigating structural changes in the bones, muscles, and surrounding soft tissues [ 11 ]. These methods can also quantify metrics, including cartilage thickness and surface-to-surface distance, which measures the gap between opposing cartilage or bone surfaces during motion. 3D imaging can identify contact areas, surface areas where cartilage layers are in contact. Increased contact area indicates potential cartilage degeneration. CT imaging offers superior spatial resolution for bone and fast acquisition times. However, unlike MRI, CT imaging cannot reliably differentiate cartilage from joint space fluid. To address this, studies either use iodine contrast to visualise cartilage [ 15 ] or assume a constant cartilage thickness [ 8 , 13 ]. Heatmaps can be used to visualize spatial variations in cartilage thickness and inter-bone distances, aiding interpretation of these degenerative changes [ 2 , 19 ]. Most clinical imaging relies on either static 3D CT or MRI imaging, or dynamic 2D fluoroscopy imaging. While the former lacks kinematic information, the latter is limited by anatomical superposition and the lack of depth information. Currently, no clinical imaging modality can simultaneously assess joint morphology and function in three dimensions over time. Dynamic CT or time-resolved CT imaging was initially developed for cardiopulmonary applications, but gained recognition in musculoskeletal research for its ability to capture real-time joint motion with high spatial and temporal resolution [ 3 , 4 , 9 , 23 ]. It enables non-invasive, high-speed imaging to quantify joint kinematics and morphological changes during motion [ 16 , 23 ]. Dynamic CT allows simultaneous assessment of morphology and motion in 4D [ 16 , 23 ]. This study assessed induced cartilage removal in a cadaveric knee phantom by surgically removing cartilage in three progressive steps. Changes in contact area were evaluated using dynamic CT during joint flexion and extension. To estimate contact areas, a CT-based, model-driven approach was introduced, simulating healthy cartilage on both patella and femur and computing the inter-surface distance. MATERIALS AND METHODS Experimental set-up A Thiel-embalmed cadaveric left leg was used for this study to enable the preservation of both bone and soft tissue structures. The preservation of the soft tissue envelope allows to represent biomechanics and cartilage degeneration of the human knee. The study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Ethical approval for the study was granted by the ethics committee of VUB–UZ Brussels University Hospital (B.U.N. 1432023000100). Cartilage was sequentially removed by an expert orthopaedic surgeon using a milling cutter and evaluated across four conditions: a baseline with no intervention, followed by progressive damage at the lateral facet, crista, and medial facet. Final removal at the medial facet resulted in total cartilage loss within the patellofemoral joint. Dynamic CT imaging captured each condition of the knee during a cyclic flexion-extension motion to generate proximity maps showing changes in intra-articular contact areas during motion. Reproducibility was evaluated by repeating the CT acquisitions three times. The baseline and crista scenarios are illustrated on Fig. 1 . A wooden frame was foreseen to manipulate the leg in a cyclic flexion-extension while remaining in the CT scanner’s field of view (Fig. 2 ). Dynamic CT images were obtained while the leg underwent cyclic flexion-extension motion after each intervention stage. The scans were acquired using a 256-slice wide-beam CT (GE Revolution Healthcare) with 16 cm z-coverage, a 50 cm field of view, tube voltage of 80 kV, tube current of 452 mA, slice thickness of 0.625 mm, and pixel size of 0.98 mm. Reproducibility was assessed by repeating the dynamic CT acquisition three times after medial cartilage removal and calculating the standard error of the mean. Contact area is defined as the distance between two opposing healthy cartilage layer models. Prior to the cartilage removal, these models were derived from a contrast-enhanced CT scan after injecting 10 ml of contrast agent (Iodixanol 320, Visipaque) into the healthy cadaveric knee, allowing visualization of intact cartilage (Fig. 3 ). Image processing The femur and patella were segmented and registered using a multi-atlas approach with SimpleITK-Elastix, following a previously published in-house image processing pipeline for joint motion evaluation [ 12 ]. Surface proximity maps of the joint were generated to visualize the intra-articular joint space using the Pyvista package in Python. Proximity maps visualize contact area by calculating the distance between intact patellar and femoral cartilage layers. A cartilage-to-cartilage distance of zero indicates initial cartilage contact; a positive distance reflects a normal joint space without contact, and a negative value suggests active cartilage loss. A one-tailed Wilcoxon signed-rank test was used to assess whether contact area increased between the different steps of cartilage degeneration. The Wilcoxon Signed Rank test was used to compare contact areas at six knee angles (0°, 5°, 10°, 15°, 20°, 25°) to assess whether dynamic CT-derived proximity maps increase significantly between healthy and increasing levels of degenerated cartilage (baseline, lateral, crista, medial). RESULTS The cartilage thicknesses of intact patellar and femoral cartilage layers of the cadaveric knee are visualised on Fig. 4 . The mean (± standard deviation) cartilage thickness was 1.82 ± 0.53 mm for the femur and 1.98 ± 0.68 mm for the patella, adding up to a combined cartilage thickness of 3.8 ± 0.86 mm in the patellofemoral joint. The resulting proximity maps of contact areas with healthy cartilage layer models are visualised in Fig. 5 , where intra-articular contact areas are displayed as a heatmap on the patellar cartilage layer, which is shown in white, while bone structures are rendered in grey. These visualisations offer spatial context to the intra-articular contact areas shown as bar plots in Fig. 6 a. For the baseline, condition, no intra-articular contact area is observed. Following cartilage removal at the lateral facet, contact areas emerge at each flexion angle, localised to the lateral side of the patella, with a mean of 84.2 mm 2 (p = 0.016). The crista intervention further increases the contact area to a mean of 176.0 mm 2 (109.0% increase, p = 0.031), which also spatially extends into the central region. After complete cartilage removal, including the medial side, the contact area becomes more widespread with an average area of 308.7 mm 2 (75.4% increase, p = 0.016), with the medial aspect most affected at 25 degrees of flexion. The repeated measurements for the medial condition exhibit consistent results, as illustrated in Fig. 6 b. The confidence interval shown in Fig. 6 a, based on the standard error of the mean from three trials, shows an average deviation of 6%. At 0° flexion, all four conditions show minimal and indistinguishable contact area variation. DISCUSSION This study assessed cartilage contact area in a cadaveric knee across three stages of cartilage removal by intervention. After each intervention, dynamic CT captured knee motion, and proximity maps visualized contact area during 25° dynamic flexion-extension motion. This angle range was constrained to 25° by the physical limitations of the CT gantry. Contact area was computed from contrast-enhanced CT by extracting healthy cartilage layers and computing the area of contact between these two layers. The resulting area showed a clear trend across all experimental conditions: contact area increased with progressive cartilage removal. In the baseline (healthy) condition, no contact was observed at any flexion angle, consistent with the known absence of cartilage contact in a healthy knee. At full extension (0° angle), contact areas were similar across conditions. This suggests that static scans at this angle may not capture relevant differences between pathological states, reinforcing the value of dynamic CT for detecting kinematic changes. Our method also showed spatial correspondence. Contact appeared at the lateral facet following lateral cartilage removal, expanded to the central region with crista removal, and extended medially after medial removal. This indicates that contact area maps could potentially provide spatial information about the location of cartilage thinning. In literature, contact areas can also be defined by calculating bone-to-bone distances and assuming a constant cartilage thickness [ 6 , 21 ]. In this study, we found a combined thickness (patella and femur) of 3.80 ± 0.86 mm, indicating some thickness variation across the articulating surfaces. Reported average combined patellofemoral cartilage thickness varies from an average of 5.5 mm for adults [ 5 ] to 9.0 mm for adolescents [ 18 ]. Robinson et. al. [ 17 ] found that cartilage stiffness decreases with OA severity, potentially explaining increased contact area. This underscores dynamic CT’s value in assessing cartilage contact during motion. Further research is needed to compare fixed threshold methods with calculations that account for anatomically realistic variations in cartilage thickness. The increase in cartilage contact area with progressive degeneration aligns with other findings in literature. Eckstein et al. [ 7 ] reported increasing total subchondral bone areas (tAB) using static MRI imaging, but only for later stages of OA. Turmezei et al. [ 20 ] found a significant reduction in joint space width on static CT imaging, even for early stages of OA. In the wrist, D’Agostino et al. [ 6 ] observed a similar trend, where later stage arthritic patients exhibited greater contact areas and joint space narrowing compared to controls. In the first MTP joint, similar patterns were noted by Jones et al. [ 10 ], where hallux rigidus (HR) led to increased joint coverage on static CT imaging. This study has following limitations. It was an ex-vivo study based on a single specimen, which may affect the broader applicability of the results. Cartilage removal was done using a milling cutter, which might not fully replicate the characteristics of natural cartilage degeneration. Additionally, the analysis was limited to flexion angles up to 25 degrees due to constraints of the CT gantry. CONCLUSION This study demonstrated that progressive cartilage degeneration in a cadaveric knee specimen leads to a significant increase in contact area. Contact area varies during motion and is least distinguishable in full extension, highlighting the value for dynamic imaging. These findings underscore the potential of dynamic CT-based contact area analysis for assessing cartilage health. Future research should further investigate the diagnostic value of contact area for early osteoarthritis detection and its capacity to provide spatial context to cartilage degeneration. Declarations Funding information not applicable Author Contribution M.A. did project development, data collection, data analysis and manuscript writingB.K. supervised data analysis T.S. did project development, performed the surgical interventionN.V.V. provided technical support for the device in Figure 2G.V.G. did project development, data management, manuscript editingE.C. did project development and assisted surgical interventionN.B. did project development, manuscript editingAll authors reviewed the final manuscript. Data Availability Due to ethical regulations related to the use of human cadaveric material, the data supporting this study are not openly available. However, they can be obtained from the corresponding author upon reasonable request. References Adachi, T. et al. Accuracy Verification of Four-Dimensional CT Analysis of Knee Joint Movements: A Pilot Study Using a Knee Joint Model and Motion-Capture System. 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In vivo biomechanical behavior of the trapeziometacarpal joint in healthy and osteoarthritic subjects. Clin. Biomech. 49 , 119–127. https://doi.org/10.1016/j.clinbiomech.2017.09.006 (Nov. 2017). Eckstein, F. et al. (eds). Magnitude and regional distribution of cartilage loss associated with grades of joint space narrowing in radiographic osteoarthritis – data from the Osteoarthritis Initiative (OAI). Osteoarthritis Cartilage. 18(6). pp. 760–768. Jun. (2010). https://doi.org/10.1016/j.joca.2009.12.009 Foumani, M. et al. In-vivo dynamic and static three-dimensional joint space distance maps for assessment of cartilage thickness in the radiocarpal joint. Clin. Biomech. 28 (2), 151–156. https://doi.org/10.1016/j.clinbiomech.2012.11.005 (Feb. 2013). Gondim Teixeira, P. A. et al. Evidence-based recommendations for musculoskeletal kinematic 4D-CT studies using wide area-detector scanners: a phantom study with cadaveric correlation. Eur. 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Sidharthan, S., Apr. & et al Patterns of Articular Cartilage Thickness in Pediatric and Adolescent Knees: A Magnetic Resonance Imaging–Based Study. Arthrosc. Sports Med. Rehabil . 3 (2), e381–e390. https://doi.org/10.1016/j.asmr.2020.09.029 (2021). Siegler, S. et al. Jul.. Analysis of surface-to-surface distance mapping during three-dimensional motion at the ankle and subtalar joints. J Biomech. 76. pp. 204–211. (2018). https://doi.org/10.1016/j.jbiomech.2018.05.026 Turmezei, T. D. et al. Quantitative Three-dimensional Assessment of Knee Joint Space Width from Weight-bearing CT. Radiology 299 (3), 649–659. https://doi.org/10.1148/radiol.2021203928 (Jun. 2021). Van Royen, K. et al. Automated analysis of trapeziometacarpal joint kinematics using four-dimensional computed tomography. J. Hand Surg. Eur. 49 (9), 1095–1103. https://doi.org/10.1177/17531934241229948 (Oct. 2024). Wade, L. et al. Applications and limitations of current markerless motion capture methods for clinical gait biomechanics. PeerJ e12995. https://doi.org/10.7717/peerj.12995 (Feb. 2022). 10. Wong, M. T. et al. Four-dimensional computed tomography: musculoskeletal applications. Can. J. Surg. 65 (3), E388–E393. https://doi.org/10.1503/cjs.023420 (Jun. 2022). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7121995","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":496685562,"identity":"e68b9f6d-639a-44b2-90a2-351dc1227072","order_by":0,"name":"Manou Acke","email":"data:image/png;base64,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","orcid":"","institution":"Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel)","correspondingAuthor":true,"prefix":"","firstName":"Manou","middleName":"","lastName":"Acke","suffix":""},{"id":496685563,"identity":"fdea2cd9-925a-499a-85e3-2352e001d605","order_by":1,"name":"Benyameen Keelson","email":"","orcid":"","institution":"Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel)","correspondingAuthor":false,"prefix":"","firstName":"Benyameen","middleName":"","lastName":"Keelson","suffix":""},{"id":496685564,"identity":"79f05ae1-d7ad-4405-a0ba-7b2d13293fc6","order_by":2,"name":"Thierry Scheerlinck","email":"","orcid":"","institution":"Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel)","correspondingAuthor":false,"prefix":"","firstName":"Thierry","middleName":"","lastName":"Scheerlinck","suffix":""},{"id":496685565,"identity":"586b9ebf-7b4a-486f-a1fe-ed9f39512a89","order_by":3,"name":"Nicolas Van Vlasselaer","email":"","orcid":"","institution":"Vrije Universiteit Brussel (VUB)","correspondingAuthor":false,"prefix":"","firstName":"Nicolas","middleName":"Van","lastName":"Vlasselaer","suffix":""},{"id":496685566,"identity":"dd8c7100-1133-484d-be36-f43b7a2bd9ad","order_by":4,"name":"Gert Van Gompel","email":"","orcid":"","institution":"Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel)","correspondingAuthor":false,"prefix":"","firstName":"Gert","middleName":"Van","lastName":"Gompel","suffix":""},{"id":496685567,"identity":"6dd9a717-b450-447f-b075-0e3086d4d5f0","order_by":5,"name":"Erik Cattrysse","email":"","orcid":"","institution":"Vrije Universiteit Brussel (VUB)","correspondingAuthor":false,"prefix":"","firstName":"Erik","middleName":"","lastName":"Cattrysse","suffix":""},{"id":496685568,"identity":"35c44c85-7d7d-4775-b251-1815deb622f2","order_by":6,"name":"Nico Buls","email":"","orcid":"","institution":"Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel)","correspondingAuthor":false,"prefix":"","firstName":"Nico","middleName":"","lastName":"Buls","suffix":""}],"badges":[],"createdAt":"2025-07-14 14:08:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7121995/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7121995/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88643027,"identity":"67347dfa-e738-437f-adfb-c3c5557b6e14","added_by":"auto","created_at":"2025-08-08 16:13:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2766412,"visible":true,"origin":"","legend":"\u003cp\u003e(a) The anatomy that will be imaged for the baseline CT acquisition with cartilage still fully intact. (b) The anatomy with cartilage removed at the lateral facet and crista.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7121995/v1/924cfd96da872fa73187fb45.png"},{"id":88643026,"identity":"2c6b5a50-6079-4bc0-bc2e-7ff2e0d50fab","added_by":"auto","created_at":"2025-08-08 16:13:05","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":550580,"visible":true,"origin":"","legend":"\u003cp\u003eThe knee is manipulated in a linear vertical motion while the ankle and hip can freely move along a linear railing system. This allows the knee to remain in the CT scanner’s field of view (red).\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7121995/v1/f8e62dfcd5a0de72a0b290e0.jpeg"},{"id":88643024,"identity":"7d412125-b41c-4e45-833f-9276ecdfb4f9","added_by":"auto","created_at":"2025-08-08 16:13:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":70260,"visible":true,"origin":"","legend":"\u003cp\u003eThe cartilage layer was segmented on both the Patella (red) and Femur (green). This segmentation will be used to calculate the distance between the two cartilage layers and to visualize the areas where the cartilage layers are in contact.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7121995/v1/52588eb302782ebce06798fb.png"},{"id":88644755,"identity":"3edd1b48-cdcb-4921-b042-92b1d1686342","added_by":"auto","created_at":"2025-08-08 16:21:05","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":376632,"visible":true,"origin":"","legend":"\u003cp\u003eCartilage thickness distribution of the femoral and patellar cartilage layers.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7121995/v1/3465aa13a20bd34e7f12251d.jpeg"},{"id":88644756,"identity":"e8032c17-205e-4d36-a399-5d21b3532c43","added_by":"auto","created_at":"2025-08-08 16:21:05","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":383075,"visible":true,"origin":"","legend":"\u003cp\u003eProximity maps illustrate contact area in function of flexion angle across increasing levels of cartilage degeneration (baseline, lateral, crista, medial). The inter-cartilage distances within this contact area are represented as a heatmap.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7121995/v1/15ee3baa36cd90eed5628756.jpeg"},{"id":88645744,"identity":"3c269caf-4851-4041-ad72-c81adb822b67","added_by":"auto","created_at":"2025-08-08 16:29:05","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":400778,"visible":true,"origin":"","legend":"\u003cp\u003eContact area was calculated in function of flexion angle across increasing levels of cartilage degeneration (baseline, lateral, crista, medial). To assess reproducibility, dynamic CT acquisition was repeated three times after medial cartilage removal; the resulting variability is shown as error bars.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7121995/v1/b60f210ac3a371206d048919.png"},{"id":91148287,"identity":"eeb9032e-15b1-4d4a-9be6-c1460f4e03df","added_by":"auto","created_at":"2025-09-12 06:43:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5568164,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7121995/v1/9dd555ee-1bf0-49c3-bf9f-bc81eec421ed.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Dynamic CT–Based Quantification of Patellofemoral Contact Area Following Cartilage Removal: An Ex Vivo Study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eKnee osteoarthritis (OA) is a common musculoskeletal disorder, affecting 16% of the global population [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The prevalence of these disorders is expected to rise further due to the aging global population, underscoring the need for effective prevention, diagnosis, and treatment strategies. Early diagnosis can slow disease progression and enhance patients' quality of life [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Knee osteoarthritis is caused by uneven pressure distribution and abnormal joint movement. Over time, these factors lead to cartilage thinning, joint space narrowing, and increased bone-on-bone friction [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Quantifying the extent of these structural and kinematic changes can provide an early diagnosis for osteoarthritis.\u003c/p\u003e\u003cp\u003eA range of assessment methods have been introduced for the diagnosis and quantification of knee OA, broadly categorized into image-based and non-image-based approaches.\u003c/p\u003e\u003cp\u003eNon-image-based methods include electromyography (EMG) for assessing muscle activity and motion capture systems for evaluating joint kinematics [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, these approaches are often limited by inaccuracy or impracticality [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Invasive marker-based techniques are more accurate but unsuitable for clinical application [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eImage-based techniques, such as radiography, ultrasound, MRI, fluoroscopy, and CT, are routinely employed to diagnose musculoskeletal disorders (MSDs) by investigating structural changes in the bones, muscles, and surrounding soft tissues [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThese methods can also quantify metrics, including cartilage thickness and surface-to-surface distance, which measures the gap between opposing cartilage or bone surfaces during motion. 3D imaging can identify contact areas, surface areas where cartilage layers are in contact. Increased contact area indicates potential cartilage degeneration. CT imaging offers superior spatial resolution for bone and fast acquisition times. However, unlike MRI, CT imaging cannot reliably differentiate cartilage from joint space fluid. To address this, studies either use iodine contrast to visualise cartilage [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] or assume a constant cartilage thickness [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Heatmaps can be used to visualize spatial variations in cartilage thickness and inter-bone distances, aiding interpretation of these degenerative changes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMost clinical imaging relies on either static 3D CT or MRI imaging, or dynamic 2D fluoroscopy imaging. While the former lacks kinematic information, the latter is limited by anatomical superposition and the lack of depth information. Currently, no clinical imaging modality can simultaneously assess joint morphology and function in three dimensions over time.\u003c/p\u003e\u003cp\u003eDynamic CT or time-resolved CT imaging was initially developed for cardiopulmonary applications, but gained recognition in musculoskeletal research for its ability to capture real-time joint motion with high spatial and temporal resolution [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. It enables non-invasive, high-speed imaging to quantify joint kinematics and morphological changes during motion [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Dynamic CT allows simultaneous assessment of morphology and motion in 4D [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study assessed induced cartilage removal in a cadaveric knee phantom by surgically removing cartilage in three progressive steps. Changes in contact area were evaluated using dynamic CT during joint flexion and extension. To estimate contact areas, a CT-based, model-driven approach was introduced, simulating healthy cartilage on both patella and femur and computing the inter-surface distance.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003e\u003cspan type=\"BoldItalicSmallCaps\" class=\"BoldItalicSmallCaps\" name=\"Emphasis\"\u003eExperimental set-up\u003c/span\u003e\u003c/p\u003e\u003cp\u003eA Thiel-embalmed cadaveric left leg was used for this study to enable the preservation of both bone and soft tissue structures. The preservation of the soft tissue envelope allows to represent biomechanics and cartilage degeneration of the human knee.\u003c/p\u003e\u003cp\u003eThe study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Ethical approval for the study was granted by the ethics committee of VUB\u0026ndash;UZ Brussels University Hospital (B.U.N. 1432023000100).\u003c/p\u003e\u003cp\u003eCartilage was sequentially removed by an expert orthopaedic surgeon using a milling cutter and evaluated across four conditions: a baseline with no intervention, followed by progressive damage at the lateral facet, crista, and medial facet. Final removal at the medial facet resulted in total cartilage loss within the patellofemoral joint.\u003c/p\u003e\u003cp\u003eDynamic CT imaging captured each condition of the knee during a cyclic flexion-extension motion to generate proximity maps showing changes in intra-articular contact areas during motion. Reproducibility was evaluated by repeating the CT acquisitions three times. The baseline and crista scenarios are illustrated on Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eA wooden frame was foreseen to manipulate the leg in a cyclic flexion-extension while remaining in the CT scanner\u0026rsquo;s field of view (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eDynamic CT images were obtained while the leg underwent cyclic flexion-extension motion after each intervention stage. The scans were acquired using a 256-slice wide-beam CT (GE Revolution Healthcare) with 16 cm z-coverage, a 50 cm field of view, tube voltage of 80 kV, tube current of 452 mA, slice thickness of 0.625 mm, and pixel size of 0.98 mm.\u003c/p\u003e\u003cp\u003eReproducibility was assessed by repeating the dynamic CT acquisition three times after medial cartilage removal and calculating the standard error of the mean.\u003c/p\u003e\u003cp\u003eContact area is defined as the distance between two opposing healthy cartilage layer models. Prior to the cartilage removal, these models were derived from a contrast-enhanced CT scan after injecting 10 ml of contrast agent (Iodixanol 320, Visipaque) into the healthy cadaveric knee, allowing visualization of intact cartilage (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldItalicSmallCaps\" class=\"BoldItalicSmallCaps\" name=\"Emphasis\"\u003eImage processing\u003c/span\u003e\u003c/p\u003e\u003cp\u003eThe femur and patella were segmented and registered using a multi-atlas approach with SimpleITK-Elastix, following a previously published in-house image processing pipeline for joint motion evaluation [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Surface proximity maps of the joint were generated to visualize the intra-articular joint space using the Pyvista package in Python.\u003c/p\u003e\u003cp\u003eProximity maps visualize contact area by calculating the distance between intact patellar and femoral cartilage layers. A cartilage-to-cartilage distance of zero indicates initial cartilage contact; a positive distance reflects a normal joint space without contact, and a negative value suggests active cartilage loss.\u003c/p\u003e\u003cp\u003eA one-tailed Wilcoxon signed-rank test was used to assess whether contact area increased between the different steps of cartilage degeneration.\u003c/p\u003e\u003cp\u003eThe Wilcoxon Signed Rank test was used to compare contact areas at six knee angles (0\u0026deg;, 5\u0026deg;, 10\u0026deg;, 15\u0026deg;, 20\u0026deg;, 25\u0026deg;) to assess whether dynamic CT-derived proximity maps increase significantly between healthy and increasing levels of degenerated cartilage (baseline, lateral, crista, medial).\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe cartilage thicknesses of intact patellar and femoral cartilage layers of the cadaveric knee are visualised on Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe mean (\u0026plusmn;\u0026thinsp;standard deviation) cartilage thickness was 1.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53 mm for the femur and 1.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68 mm for the patella, adding up to a combined cartilage thickness of 3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86 mm in the patellofemoral joint.\u003c/p\u003e\u003cp\u003eThe resulting proximity maps of contact areas with healthy cartilage layer models are visualised in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, where intra-articular contact areas are displayed as a heatmap on the patellar cartilage layer, which is shown in white, while bone structures are rendered in grey. These visualisations offer spatial context to the intra-articular contact areas shown as bar plots in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea.\u003c/p\u003e\u003cp\u003eFor the baseline, condition, no intra-articular contact area is observed. Following cartilage removal at the lateral facet, contact areas emerge at each flexion angle, localised to the lateral side of the patella, with a mean of 84.2 mm\u003csup\u003e2\u003c/sup\u003e (p\u0026thinsp;=\u0026thinsp;0.016). The crista intervention further increases the contact area to a mean of 176.0 mm\u003csup\u003e2\u003c/sup\u003e (109.0% increase, p\u0026thinsp;=\u0026thinsp;0.031), which also spatially extends into the central region. After complete cartilage removal, including the medial side, the contact area becomes more widespread with an average area of 308.7 mm\u003csup\u003e2\u003c/sup\u003e (75.4% increase, p\u0026thinsp;=\u0026thinsp;0.016), with the medial aspect most affected at 25 degrees of flexion.\u003c/p\u003e\u003cp\u003eThe repeated measurements for the medial condition exhibit consistent results, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb. The confidence interval shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea, based on the standard error of the mean from three trials, shows an average deviation of 6%.\u003c/p\u003e\u003cp\u003eAt 0\u0026deg; flexion, all four conditions show minimal and indistinguishable contact area variation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study assessed cartilage contact area in a cadaveric knee across three stages of cartilage removal by intervention. After each intervention, dynamic CT captured knee motion, and proximity maps visualized contact area during 25\u0026deg; dynamic flexion-extension motion. This angle range was constrained to 25\u0026deg; by the physical limitations of the CT gantry. Contact area was computed from contrast-enhanced CT by extracting healthy cartilage layers and computing the area of contact between these two layers.\u003c/p\u003e\u003cp\u003eThe resulting area showed a clear trend across all experimental conditions: contact area increased with progressive cartilage removal. In the baseline (healthy) condition, no contact was observed at any flexion angle, consistent with the known absence of cartilage contact in a healthy knee. At full extension (0\u0026deg; angle), contact areas were similar across conditions. This suggests that static scans at this angle may not capture relevant differences between pathological states, reinforcing the value of dynamic CT for detecting kinematic changes.\u003c/p\u003e\u003cp\u003eOur method also showed spatial correspondence. Contact appeared at the lateral facet following lateral cartilage removal, expanded to the central region with crista removal, and extended medially after medial removal. This indicates that contact area maps could potentially provide spatial information about the location of cartilage thinning.\u003c/p\u003e\u003cp\u003eIn literature, contact areas can also be defined by calculating bone-to-bone distances and assuming a constant cartilage thickness [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In this study, we found a combined thickness (patella and femur) of 3.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86 mm, indicating some thickness variation across the articulating surfaces. Reported average combined patellofemoral cartilage thickness varies from an average of 5.5 mm for adults [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] to 9.0 mm for adolescents [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Robinson et. al. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] found that cartilage stiffness decreases with OA severity, potentially explaining increased contact area. This underscores dynamic CT\u0026rsquo;s value in assessing cartilage contact during motion. Further research is needed to compare fixed threshold methods with calculations that account for anatomically realistic variations in cartilage thickness.\u003c/p\u003e\u003cp\u003eThe increase in cartilage contact area with progressive degeneration aligns with other findings in literature. Eckstein et al. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] reported increasing total subchondral bone areas (tAB) using static MRI imaging, but only for later stages of OA. Turmezei et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] found a significant reduction in joint space width on static CT imaging, even for early stages of OA. In the wrist, D\u0026rsquo;Agostino et al. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] observed a similar trend, where later stage arthritic patients exhibited greater contact areas and joint space narrowing compared to controls. In the first MTP joint, similar patterns were noted by Jones et al. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], where hallux rigidus (HR) led to increased joint coverage on static CT imaging.\u003c/p\u003e\u003cp\u003eThis study has following limitations. It was an ex-vivo study based on a single specimen, which may affect the broader applicability of the results. Cartilage removal was done using a milling cutter, which might not fully replicate the characteristics of natural cartilage degeneration. Additionally, the analysis was limited to flexion angles up to 25 degrees due to constraints of the CT gantry.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study demonstrated that progressive cartilage degeneration in a cadaveric knee specimen leads to a significant increase in contact area. Contact area varies during motion and is least distinguishable in full extension, highlighting the value for dynamic imaging. These findings underscore the potential of dynamic CT-based contact area analysis for assessing cartilage health. Future research should further investigate the diagnostic value of contact area for early osteoarthritis detection and its capacity to provide spatial context to cartilage degeneration.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding information \u003c/h2\u003e\u003cp\u003enot applicable\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eM.A. did project development, data collection, data analysis and manuscript writingB.K. supervised data analysis T.S. did project development, performed the surgical interventionN.V.V. provided technical support for the device in Figure 2G.V.G. did project development, data management, manuscript editingE.C. did project development and assisted surgical interventionN.B. did project development, manuscript editingAll authors reviewed the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eDue to ethical regulations related to the use of human cadaveric material, the data supporting this study are not openly available. However, they can be obtained from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdachi, T. et al. Accuracy Verification of Four-Dimensional CT Analysis of Knee Joint Movements: A Pilot Study Using a Knee Joint Model and Motion-Capture System. \u003cem\u003eCureus\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e(2). p. e35616. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7759/cureus.35616\u003c/span\u003e\u003cspan address=\"10.7759/cureus.35616\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAteshian, G. A. et al. Quantitation of articular surface topography and cartilage thickness in knee joints using stereophotogrammetry. \u003cem\u003eJ. 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Four-dimensional computed tomography: musculoskeletal applications. \u003cem\u003eCan. J. Surg.\u003c/em\u003e \u003cb\u003e65\u003c/b\u003e (3), E388\u0026ndash;E393. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1503/cjs.023420\u003c/span\u003e\u003cspan address=\"10.1503/cjs.023420\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (Jun. 2022).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7121995/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7121995/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKnee osteoarthritis (OA) is a musculoskeletal disorder characterised by abnormal joint motion, joint space narrowing, and cartilage degeneration. Early diagnosis is important to slow disease progression. Dynamic CT imaging adds three-dimensional functional information to an otherwise static diagnosis. This study investigates\u003c/em\u003e the diagnostic potential of\u003cem\u003einter-articular contact area during knee motion across three stages of cartilage degeneration.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCartilage was progressively removed from the patellofemoral joint of a cadaveric knee to simulate stages of cartilage degeneration: first laterally, then at the crista, and finally medially. After each intervention, dynamic CT was performed during induced cyclic flexion-extension motion of the cadaveric knee. We quantified contact area dynamically by measuring distances between intact cartilage layers of the patella and femur. Contact areas across stages (baseline, lateral, crista, medial) were compared using the Wilcoxon Signed Rank test at six knee flexion angles (0°, 5°, 10°, 15°, 20°, 25°). Reproducibility was assessed by repeating the dynamic CT acquisition post-cartilage removal three times.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eContact area increased significantly at each stage of cartilage degeneration compared to the previous stage (p \u0026lt; 0.05), progressing from 0 mm² to 84.2 mm², 176.0 mm², and 308.7 mm². For reproducibility, the standard error of the mean across three repetitions showed an average deviation of 6%.\u003c/p\u003e\n\u003cp\u003eDifferences varied across knee angles, with the least distinction observed in full extension. Spatially, the contact areas corresponded anatomically to the regions of cartilage removal.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProgressive cartilage removal in a cadaveric knee results in a significant increase in contact area.\u003c/p\u003e","manuscriptTitle":"Dynamic CT–Based Quantification of Patellofemoral Contact Area Following Cartilage Removal: An Ex Vivo Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-08 16:13:00","doi":"10.21203/rs.3.rs-7121995/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3d54c993-fab1-48e7-aafd-fc278d38c99a","owner":[],"postedDate":"August 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":52759921,"name":"Health sciences/Anatomy"},{"id":52759922,"name":"Health sciences/Diseases"},{"id":52759923,"name":"Health sciences/Health care"},{"id":52759924,"name":"Health sciences/Medical research"},{"id":52759925,"name":"Health sciences/Rheumatology"}],"tags":[],"updatedAt":"2025-09-08T05:39:09+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-08 16:13:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7121995","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7121995","identity":"rs-7121995","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}