Introduction

Osteoarthritis (OA) of the knee is a degenerative joint disease characterized by a

low-grade joint infection leading to altered chondrocyte metabolism. In a healthy microenvironment, chondrocytes regulate the composition of the extracellular matrix (ECM) such as collagen II and non-collagen proteins (e.g., aggrecan) via a complex signaling

network of catabolic and anabolic factors. In OA a metabolic shift of the chondrocytes causes a homeostatic imbalance with increased catabolism and apoptosis and reduced anabolism and autophagy leading to disease progression. Intra-articular injections of local anesthetics (LA) are widely used for treating patients suffering from painful OA of the knee. LA are prevalently administered to OA patients for instantaneous pain relief. The problem is that this effect only lasts a couple of days, depending on pharmacokinetics of the respective substance, and only recurrent injections of LA subside persistent pain relief. However, the cytotoxic effects of LA on chondrocytes are well known. Intra-articular injection of LA is contra-productive and intensifies the progression of osteoarthritis. The detrimental impact varies depending on the substance being injected. Some studies have shown that ropivacaine induces less apoptosis of chondrocytes in vitro than other anesthetics like lidocaine or bupivacaine.

Content

LA only treat the symptom, namely pain, and accelerates the degenerative process. In contrast, intra-articular administered glucocorticoids (GC) or hyaluronic acid (HA) target to offset the progression of OA. GC have a potent anti-inflammatory effect which plays a significant role in constraining the progression of OA. However, pro-apoptotic effects of GC on chondrocytes have been reported. This raises the question of whether GC should be administered intra-articular together with local anesthetics because adverse effects on chondrocytes are known for both substances. Interestingly, despite that, their coadministration is frequently performed in clinical practice. HA also has anti-inflammatory effects, albeit to a lesser extent than GC. Advantages of HA include increased cell viability and its role as a viscosupplement for increased lubrication. Furthermore, administered HA induces endogenous HA production. Recently, the co-administration of HA with GC was introduced to combine the beneficial effects of both substances. Primary clinical studies show promising results with decreased pain levels in the co-administration compared to a single injection. Administering different substances offers the potential of achieving synergistic effects and might mitigate detrimental effects of one substance (e.g., cytotoxicity of LA, the apoptotic potential on chondrocytes of GC) by another one (e.g., HA).

The current study aimed to investigate the cytotoxicity of co-administrating local anesthetics (LA) with glucocorticoids (GC) and hyaluronic acid (HA) in vitro. Human articular cartilage

was obtained from five patients undergoing total knee arthroplasty. Chondrocytes were isolated, expanded, and seeded in 24-well plates for experimental testing. LA (lidocaine, bupivacaine, ropivacaine) were administered separately and co-administered with the following substances: GC, HA, and GC/HA. Viability was confirmed by microscopic images, flow cytometry, metabolic activity, and live/dead assay. The addition of HA and GC/HA resulted in enhanced attachment and branched appearance of the chondrocytes compared to LA and LA/GC. Metabolic activity was better in all LA co-administered with HA and GC/HA than with GC and only LA. Flow cytometry revealed the lowest cell viability in lidocaine and the highest cell viability in ropivacaine. This finding was also confirmed by live/dead assay. The study showed that co-administering LA with HA and HA/GC reduces its chondrotoxicity.

Administering GC is desirable due to its potent anti-inflammatory effect, albeit its apoptotic potential is problematic. In the present study, HA supports the effects of GC and reduces the cytotoxic effects of LA. Differences between LA were observed; (i) lidocaine showed high apoptotic rates; (ii) ropivacaine showed the best cell viability. The findings of the present study are of high clinical relevance. Although the chondrotoxic effect of LA and GC is well known, the substances are widely used in a clinical setting. The data of this study suggest that co-administrating HA with LA and GC might mitigate their detrimental effects on chondrocytes while still maintaining the beneficial effects of anti-inflammation.

References

1. Moser LB, Bauer C, Jeyakumar V, Niculescu-Morzsa E-P, Nehrer S. Hyaluronic Acid as a Carrier Supports the Effects of Glucocorticoids and Diminishes the Cytotoxic Effects of Local Anesthetics in Human Articular Chondrocytes In Vitro. Int J Mol Sci. 2021 Oct 25;22(21):11503.

2. Szwedowski D, Szczepanek J, Paczesny Ł, Pękała P, Zabrzyński J, Kruczyński J. Genetics in Cartilage Lesions: Basic Science and Therapy Approaches. International Journal of Molecular Sciences. 2020 Jan;21(15):5430.

3. Sophia Fox AJ, Bedi A, Rodeo SA. The Basic Science of Articular Cartilage. Sports Health. 2009 Nov;1(6):461–8.

4. Zheng L, Zhang Z, Sheng P, Mobasheri A. The role of metabolism in chondrocyte dysfunction and the progression of osteoarthritis. Ageing Res Rev. 2021 Mar;66:101249.

5. Kreuz PC, Steinwachs M, Angele P. Single-dose local anesthetics exhibit a type-, dose-, and time-dependent chondrotoxic effect on chondrocytes and cartilage: a systematic review of the current literature. Knee Surg Sports Traumatol Arthrosc. 2018 Mar;26(3):819–30.

6. Breu A, Rosenmeier K, Kujat R, Angele P, Zink W. The cytotoxicity of bupivacaine, ropivacaine, and mepivacaine on human chondrocytes and cartilage. Anesth Analg. 2013 Aug;117(2):514–22.

7. Akmal M, Singh A, Anand A, Kesani A, Aslam N, Goodship A, et al. The effects of hyaluronic acid on articular chondrocytes. J Bone Joint Surg Br. 2005 Aug;87(8):1143–9.

Acknowledgments

The research was supported by unrestricted funding:

Anika Therapeutics Inc., 32 Wiggins Avenue, MA 01730 Bedord, Massachusetts, USA

Introduction

Introduction Radiographic classification of osteoarthritis (OA) in the knee has typically been performed using semi-quantitative grading schemes ¹, the most widely used of which being the Kellgren-Lawrence (KL) scale ² which was recognized by the World Health Organization in 1961 as the standard for clinical studies of OA. The KL grading scheme requires the assessment of presence and severity degree of several individual radiographic features (IRFs), including osteophytes, sclerosis, and joint space narrowing. These assessments are them summarized into a 5 point scale, reflecting the severity of OA. However, the KL grading scheme has come under criticism for assuming a unique progression mode of OA ³ and for depending on subjective assessments ^4,5, exacerbated by the vague verbal definitions of individual radiographic features at each stage ⁶. In order to deal with these issues, the Osteoarthritis Research Society International (OARSI) proposed a classification system for each of the IRFs supported by a reference atlas, in which canonical examples of the classification of each of the IRFs are depicted ⁷.

In a first study (Part A) Joint Space Width has been the gold standard to assess loss of cartilage in knee OA. Here we describe a novel quantitative measure of joint space width: standardized JSW (stdJSW). We assess the performance of this quantitative metric for joint space width (JSW) at tracking Joint Space Narrowing OARSI grade (JSN) changes and provide reference values for different joint space narrowing OARSI grades and their annual change.

One of the main purposes of a systematic OA grading scheme, such as the KL and the OARSI systems, is to standardize diagnostic and assessments of OA. However, several studies report that the KL grading scheme, as well as the accessory assessments, suffer from subjectivity and low inter-observer reliability ^8,9. This leads to differences in assessments of the prevalence of the disease ⁴ and variability of diagnoses of the same patient. This is especially problematic for the early stages of the disease: severe forms of OA are easily recognized in radiographs but its early stages are less consensual ¹⁰. In part this stems from the high degree of subjectivity of the assessments¹¹, even with the guidance of the OARSI atlas. This problem has consequences at several levels: In the clinical practice, it can lead to misdiagnosis, leading to unnecessary examination procedures or omitted treatment, and psychological stress to the patient¹². In the context of clinical trials, the variability of assessments can decrease the power to detect statistical effects of the efficacy of treatments¹³ and complicate the estimation of prevalence and incidence rates ¹⁴.

One potential, albeit not practical, solution for the problem of variability of diagnosis would be to have the same radiograph reviewed by several physicians and to have a procedure to determine consensus, as it is done when establishing the gold-standard readings in many clinical studies. This is clearly not a practical solution for clinical practice. However, one way to approach such a problem could be make use of a computer assisted detection system to standardize the readings of the relevant features. Artificial intelligence, and especially deep learning, has proven remarkably efficient at recognizing complex visual patterns. When applied to medical imaging, these systems can provide guidance and recommendations for radiographic assessments to the reader in a robust fashion. These artificial intelligence systems can be trained on the assessments of several clinicians (or the consensus readings after several physicians have reviewed the case) and so incorporate the experience of several clinicians and could potentially simulate a consensus procedure. Here we take this latter approach.

In Part B we make use of a computer assisted detection system (KOALA, IB Lab GmbH) that was trained in a large dataset of radiographs graded for KL and JSN, Sclerosis and Osteophyte OARSI grades through a consensus procedure. KOALA makes use of deep learning networks to provide fully automated KL and OARSI grades in the form of a report. Here, we assess how the use of this computer assisted detection system affects physicians’ performance in terms of inter-observer variability at assessing KL grade and IRFs, as well as their accuracy performance at detecting several clinically relevant conditions.

Content

Methods Part A: We collected 18.934 individual knee images from the OAI study, from the follow-up visits up to month 48 (baseline plus 4 follow-up exams). Absolute JSW and JSN readings were collected from the OAI study. Standardized JSW was calculated for each knee as well as 12-month JSN grade changes. For each JSN grade and 12-month grade change, the distribution of JSW loss was calculated for stdJSW and absolute JSW measurements retrieved from the OAI study. Area under the curve of the ROC curves was calculated for the performance of both absolute and stdJSW at discriminating between different JSN grades. Standardized response mean (SRM) was used to compare the responsiveness of the two measures to change in JSN grade.

Part B: A set of 124 unilateral knee radiographs from the OAI study were analyzed by a computerized method with regard to Kellgren-Lawrence grade, as well as Joint Space Narrowing, Osteophytes and Sclerosis OARSI grades. Physicians scored all images, with respect to osteophytes, sclerosis, joint space narrowing OARSI grades and KL grade, in two modalities: through a plain radiograph (unaided) and a radiograph presented together with the report from the computer assisted detection system (aided). Intra-Class Correlation between the physicians was calculated for both modalities. Furthermore, physicians’ performance was compared to the grading of the OAIstudy , and accuracy, sensitivity and specificity were calculated in both modalities for each of the scored features.

Results Part A: The areas under the ROC curve for stdJSW at discriminating between successive JSN grades were AUC_stdJSW= 0.87, 0.95, and 0.96, for JSN>0, JSN>1 and JSN>2, respectively, whereas these were AUC_fJSW= 0.79, 0.90, 0.98 for absolute JSW. We find that standardized JSW is significantly more responsive than absolute JSW, as measured by the SRM.

Part B: Agreement rates for KL grade, sclerosis, and osteophyte OARSI grades, were statistically increased in the aided vs the unaided modality. Readings for Joint Space Narrowing OARSI grade did not show a statistically difference between the two modalities. Readers’ accuracy and specificity for KL grade > 0, KL>1, sclerosis OARSI grade > 0, and osteophyte OARSI grade > 0 was significantly increased in the aided modality. Reader sensitivity was high in both modalities.

Conclusions Our results (Part A) show that stdJSW outperforms absolute JSW at discriminating and tracking changes in JSN. Furthermore, our results show that this effect is in part because stdJSW cancels the variation in JSWs that comes from variation in height. In conclusion, our study suggests that the use of a computer assisted detection system, such as KOALA, improves both agreement rate and accuracy when assessing radiographic features relevant for the diagnosis of knee osteoarthritis. These improvements in physician performance and reliability come without trade-offs in terms of accuracy. These results argue for the use of this type of software as a way to improve the standard of care when diagnosing knee osteoarthritis.

References

1. Braun HJ, Gold GE. Diagnosis of osteoarthritis: imaging. Bone. 2012;51(2):278-288. doi:10.1016/j.bone.2011.11.019

2. Kellgren JH, Lawrence JS. Radiological assessment of osteo-arthrosis. Ann Rheum Dis. 1957;16(4):494-502. http://www.ncbi.nlm.nih.gov/pubmed/13498604.

3. Kohn MD, Sassoon AA, Fernando ND. Classifications in Brief: Kellgren-Lawrence Classification of Osteoarthritis. Clin Orthop Relat Res. 2016;474(8):1886-1893. doi:10.1007/s11999-016-4732-4

4. Culvenor AG, Engen CN, Øiestad BE, Engebretsen L, Risberg MA. Defining the presence of radiographic knee osteoarthritis: a comparison between the Kellgren and Lawrence system and OARSI atlas criteria. Knee Surgery, Sport Traumatol Arthrosc. 2015;23(12):3532-3539. doi:10.1007/s00167-014-3205-0

5. Wright RW, MARS Group TM, Wright RW, et al. Osteoarthritis Classification Scales: Interobserver Reliability and Arthroscopic Correlation. J Bone Joint Surg Am. 2014;96(14):1145-1151. doi:10.2106/JBJS.M.00929

6. Schiphof D, Boers M, Bierma-Zeinstra SMA. Differences in descriptions of Kellgren and Lawrence grades of knee osteoarthritis. Ann Rheum Dis. 2008;67(7):1034-1036. doi:10.1136/ard.2007.079020

7. Altman RD, Gold GE. Atlas of individual radiographic features in osteoarthritis, revised. Osteoarthr Cartil. 2007;15 Suppl A:A1-56. doi:10.1016/j.joca.2006.11.009

8. Gunther KP, Sun Y. Reliability of radiographic assessment in hip and knee osteoarthritis. Osteoarthr Cartil. 1999;7(2):239-246. doi:10.1053/joca.1998.0152 [doi]

9. Damen J, Schiphof D, Wolde S Ten, Cats HA, Bierma-Zeinstra SMA, Oei EHG. Inter-observer reliability for radiographic assessment of early osteoarthritis features: the CHECK (cohort hip and cohort knee) study. Osteoarthr Cartil. 2014;22(7):969-974. doi:10.1016/j.joca.2014.05.007

10. Hart DJ, Spector TD. Kellgren & Lawrence grade 1 osteophytes in the knee--doubtful or definite? Osteoarthr Cartil. 2003;11(2):149-150. doi:10.1053/JOCA.2002.0853

11. Gossec L, Jordan JM, Mazzuca SA, et al. Comparative evaluation of three semi-quantitative radiographic grading techniques for knee osteoarthritis in terms of validity and reproducibility in 1759 X-rays: report of the OARSI-OMERACT task force. Osteoarthr Cartil. 2008;16(7):742-748. doi:10.1016/j.joca.2008.02.021

12. Balint G, Szebenyi B, Bálint G, et al. Diagnosis of osteoarthritis - Guidelines and current pitfalls. Drugs. 1996;52(SUPPL. 3):1-13.

13. Sadler ME, Yamamoto RT, Khurana L, Dallabrida SM. The impact of rater training on clinical outcomes assessment data: a literature review. Int J Clin Trials. 2017;4(3):101. doi:10.18203/2349-3259.ijct20173133

14. Marshall DA, Vanderby S, Barnabe C, et al. Estimating the Burden of Osteoarthritis to Plan for the Future. Arthritis Care Res. 2015;67(10):1379-1386. doi:10.1002/acr.22612

Purpose

LNA043 is a modified human angiopoietin-like-3 (ANGPTL3) protein with chondro-anabolic properties. A first-in-human trial showed a favorable safety profile and modulation of pathways involved in osteoarthritis. The primary objective of this trial (NCT 03334812) was to assess the efficacy of a single intra-articular (i.a.) injection of LNA043 in regenerating hyaline cartilage at the donor site in patients undergoing autologous chondrocyte implantation (ACI).

Methods and Materials

This randomized, placebo-controlled, double-blind, proof-of-mechanism study included 14 subjects who received an i.a. LNA043 injection (randomization 2:1) at the end of the cartilage-harvesting procedure. Cartilage regeneration in the full-thickness defect at the ACI donor and index lesion was assessed via lesion-volume changes and glycosaminoglycan content (GAG) at Day 3 (baseline), Weeks 4 (primary endpoint), 12 and 28, using 7T magnetic resonance imaging (MRI), and histology of biopsies (second surgery, Week 4).

Results

LNA043 treatment resulted in a 65±8% refilling (vs placebo: 38±11%, p=0.04) of the donor site after 4 weeks (Figure 1), and increased to 86±11% at Week 28 (vs placebo: 63±14%, p=0.12). The index lesion showed partial repair at Week 4 (change from baseline-volume of the defect-encompassing sub-region: LNA043: +128±97mm³ vs placebo: +16±30mm³, p=0.03). Sodium-MRI demonstrated increased GAG-content of the regenerated donor site (sodium signal-increase of 26±5%, 16±6% and 38±7% for LNA043 vs. -2±12% (p=0.12), 13±10% (p=0.51) and 8±21% (p=0.15) for placebo at Weeks 4, 12 and 28) (Figure 2). Histology and immunohistochemistry confirmed the presence of hyaline cartilage. LNA043 was rapidly distributed into the circulation, no drug-related adverse events (AEs) or serious AEs were reported. No binding anti-LNA043 antibodies were detected.

Conclusion

A single i.a. injection of LNA043 at 20 mg promoted refilling of the donor site in patients undergoing ACI. The newly formed tissue showed hyaline-like quality, LNA043 displayed a favorable safety profile without significant drug related safety signals or immunogenicity.

Introduction

Early Osteoarthritis (OA) and its prevention has become an important topic in many meetings on cartilage repair and induced probably one of the most important shifts of paradigm in the treatment algorithm of cartilage defects. Early OA includes on one hand a still circumscribed lesions of the joint surface, but it also covers early signs of the ongoing process of degeneration and inflammation leading to OA. This combination seems to be the most prominent pathophysiology in patients leading to medical treatment. Isolated Cartilage defects which are only circumscribed lesions are rare and not representative for the clinical problems orthopedic surgeons are seeing in their daily practice. Therefor clinical studies do not reflect the actual patients population, where surface defects are often associated with synovitis, general changes in the biological environment in the synovial fluid and also morphological changes of the menisci and ligaments as well as background factors like joint alignment and bodyweight. So, the cartilage repair technologies have arrived in the real world. Cartilage registries clearly see early OA as the dominant indication for cartilage surgery.

Content

Early OA is characterized by the progredient loss of cartilage integrity and cellularity which eventually leads to the functional impairment of the joint. A hallmark of the osteoarthritic degenerative process is the exuberant production of proinflammatory cytokines (e.g., IL-1β, TNF-α), matrix metalloproteinases (e.g., MMP-1, -3, -13), and reactive oxygen and nitrogen species (ROS, RNS) by chondrocytes and synoviocytes. Thereby these cells become integral players in the vicious circle driving disease progression. So overall, OA is a complex process of biomechanically induced degeneration, reactive inflammation, and a general aging process with changing cellular activity.

Conservative therapies of OA include nutrients, drugs and injectables like corticosteroids, hyaluronic acid, and platelet-rich plasma as well as mesenchymal stem cells. However, the progress of the disease and persistence of symptoms might indicate early surgery and not to await the development of a full OA.

Working groups of ICRS have taken on the problem and developed a systematic approach to early OA and recently published a book with that focus. The definition or early OA is related to joint symptoms like tenderness on the joint space or crepitation, radiological Kellgren Lawrence grades between around one and two. MRI changes generally reflecting ICRS grades 1-2 with one area more than that. Furthermore, unnormal joint alignment, partial meniscus defects and functional or structural instability of the joint might be associated with the condition described above. The later mentioned conditions are obviously the hallmark of indicating surgery in early OA, since the biomechanical situation of the joint with regards to alignment, meniscus deficiency and instability is probably the most important factor in progressing OA conditions. The indication is even more critical if a cartilage defect or zonal degeneration is associated with the biomechanical malcondition. In the knee a femoro-tibial malalignment of more than 5 degrees is considered substantial and should be addressed at the same time as the cartilage defect on the overloaded joint-compartment. Same applies for instable situations after ACL ruptures, because a cartilage repair procedure will just be successful in a stable joint. Acute meniscus ruptures should be addressed immediately anyway, even more so if a suture is possible. Degenerative lesions are depending on symptoms of locking or painful movement, whereas asymptomatic degeneration of the meniscus should be observed to what degree the lesion might contribute the clinical situation. There is still discussion in the priority of the surgical procedures which can be concomitant or sequential, however the plan has to be discussed with the patient and his needs and compliance.

The most critical decision for surgery is the defect of the local osteoarthritic process or defect on the joint surface itself. A symptomatic defect bigger than 2 square centimeters is obviously an indication for surgery, although the question is how much degenerative changes in the knee beside the defect do we accept? Age is obviously a fact, but individual age (genetic background) has to be considered. Most of treatment-studies with regenerative surgery like microfracture with biomaterial (AMIC) or chondrocyte transplantation show better results below the age of 40. Defects with ICRS grades 1 or 2 might not be an indication for direct surgery since the prognosis is uncertain and there is no evidence for such lesions. In cases of persistent pain, the presence of bone edema has to be assessed by MRI, because other options like subchondroplasty, drilling or osteoporotic drugs might be more be more favorable, sometimes unloading of the joint can overcome the symptoms. Other surgical options like allografts have widened the indication of local OA since they immediately provide a stable situation of the replaced joint surface and provide a sustainable solution. Due to the lack of fresh allografts in Europe partial joint replacement and synthetic resorbable implants have become popular, however they are often just an in-between solution on the way to total joint replacement.

As a conclusion surgery is clearly indicated regarding the background-factors like alignment and instability and acute meniscus lesions in early OA because the benefit of osteotomies, ACL reconstruction and meniscus surgery including allograft is evident with regards to OA progression prevention.

The preventive effect of cartilage surgery on the defect itself is more critical to be discussed depending on age, expectation, compliance and goals of the patient. So it is more important to treat the patient, than just to concentrate too much on the surgery in this complex process of early OA.

References

1. Lattermann C, Madry H, Nakamura N, Kon E. Early Osteoarthritis: State-of-the-Art Approaches to Diagnosis, Treatment and Controversies. Springer Nature; 2021.

2. Gomoll AH, Filardo G, de Girolamo L, Espregueira-Mendes J, Esprequeira-Mendes J, Marcacci M, et al. Surgical treatment for early osteoarthritis. Part I: cartilage repair procedures. Knee Surg Sports Traumatol Arthrosc. 2012 Mar;20(3):450–66.

3. Gomoll AH, Filardo G, Almqvist FK, Bugbee WD, Jelic M, Monllau JC, et al. Surgical treatment for early osteoarthritis. Part II: allografts and concurrent procedures. Knee Surg Sports Traumatol Arthrosc. 2012 Mar;20(3):468–86.

4. Moser LB, Bauer C, Jeyakumar V, Niculescu-Morzsa E-P, Nehrer S. Hyaluronic Acid as a Carrier Supports the Effects of Glucocorticoids and Diminishes the Cytotoxic Effects of Local Anesthetics in Human Articular Chondrocytes In Vitro. Int J Mol Sci. 2021 Oct 25;22(21):11503.

5. Kon E, Engebretsen L, Verdonk P, Nehrer S, Filardo G. Clinical Outcomes of Knee Osteoarthritis Treated With an Autologous Protein Solution Injection: A 1-Year Pilot Double-Blinded Randomized Controlled Trial. Am J Sports Med. 2018 Jan;46(1):171–80.

Acknowledgments

None