Mucoid degeneration of the anterior cruciate ligament: A step toward standardized classification

INTRODUCTION

Mucoid degeneration of the anterior cruciate ligament (mACL) is a non-traumatic condition characterized by the accumulation of mucoid material within the anterior cruciate ligament (ACL) fibers, leading to an expanded and thickened ligament. This condition was first described by Kumar et al. in 1999 in a middle-aged man who presented with pain in the knee, which on magnetic resonance imaging (MRI) showed a mass in the ACL and on biopsy showed mucoid degeneration.^[1] This process results from myxoid changes, where collagen fibers are replaced by mucoid substances, impairing the ligament’s structure but typically without any history of acute trauma.^[2] mACL is uncommon and often under-recognized due to its subtle clinical presentation. Incidence in MRI-based studies ranges from 0.5% to 5% of patients undergoing knee MRI for suspected internal derangements. It most commonly affects middle-aged individuals, typically between 30 and 50 years, with a slight male predominance. It is often associated with degenerative changes in the knee, such as osteoarthritis or meniscal tears.^[2-4]

The presentation of mucoid degeneration is often atypical and insidious, making diagnosis challenging. Key symptoms include deep-seated, poorly localized knee pain without a clear history of injury. Pain often worsens with activities involving knee flexion and extension, such as squatting or climbing stairs. Limited maximum extension can be seen, referred to as a “cyclops-like syndrome,” where the thickened ligament impinges on surrounding structures. Occasionally, patients report a sensation of knee instability or locking.^[5] Unlike ACL tears, patients with mucoid degeneration typically do not experience significant instability, as the ligament remains continuous despite degeneration. Swelling or effusion may be present in some cases, but it is not a dominant feature.

MRI Findings are critical for diagnosis. The ACL appears thickened, swollen, and hyperintense on T2-weighted images, reflecting water content from the mucoid material. Linear or striated areas of low-signal intensity (representing preserved ACL fibers) within a hyperintense background give a “celery stalk” sign. ACL continuity is maintained, distinguishing it from partial or complete tears. Arthroscopic findings include a bulky, yellowish, and gelatinous ACL, often described as “celery stalk-like” or “noodle-like.”^[6] Conservative treatment options such as physical therapy, non-steroidal anti-inflammatory drugs, and activity modification are first-line treatments. Arthroscopic debridement or notchplasty may be indicated in cases with significant symptoms (e.g., pain, extension loss) unresponsive to conservative measures.^[7]

There is currently no universally accepted classification or grading system specifically for mACL. Unlike other ACL conditions, such as partial or complete tears, mucoid degeneration has not been formally stratified into grades in most of the available literature. While no standardized classification or grading system exists for mACL, clinicians rely on descriptive MRI and arthroscopic findings to assess its extent.

In this study, we aim to develop and validate a standardized classification system for the mACL. The primary objective is to establish and validate a standardized classification system that enhances consistency and clarity in communication between radiologists and orthopedic surgeons. By introducing a formal classification system, we seek to facilitate accurate diagnosis, improve reporting uniformity, and guide clinical decision-making. This classification will serve as a common language, bridging the gap between imaging findings and surgical observations, ultimately contributing to better patient management and treatment outcomes.

MATERIALS AND METHODS

This retrospective observational study aimed to develop and validate a classification system for mACL based on MRI findings. The study was conducted following approval from the local ethical committee as service evaluation Imaging/SE/2024-25/07. Given the retrospective design of the study, the requirement to obtain informed consent from the participants was waived. To ensure confidentiality, all identifying information of the subjects was anonymized, and data were handled in compliance with institutional and ethical guidelines for patient privacy and data protection.

A retrospective analysis was conducted using 100 knee MRI scans that included a mix of normal ACLs and cases with varying degrees of mucoid degeneration. The MRIs were selected by the senior author, ensuring representation across the spectrum of mACL and normal cases. MRIs showing normal ACLs or findings suggestive of mucoid degeneration were included. Patients with acute ACL tears, previous ACL reconstruction, or other significant knee injuries were excluded. The MRI scans are routinely performed using standard knee imaging sequences, which include proton density sequences in three orthogonal planes, a T2-weighted sequence in the sagittal plane, and a T1-weighted sequence in the coronal plane.

Two independent, blinded readers (musculoskeletal radiologists with 20 and 10 years of experience) evaluated the MRIs to classify each ACL based on the proposed classification system [Figures 1 and 2]. In our proposed classification system of SHRINK, there are 5 categories of ACL: Category 1 includes normal ACL without thickening or signal changes; Category 2 includes mACL with involvement of femoral half (a. <50% thickness increase and b. more than 50% thickness increase); Category 3 includes mACL with involvement of tibial half (a. <50% thickness increase and b. more than 50% thickness increase); Category 4 includes mACL with the presence of intra-ligamentous and/or peri-ligamentous ganglion cyst; and, Category 5 includes mACL with associated bony abnormalities, such as subchondral oedema or cystic changes. A hierarchical rule of application was defined to ensure unambiguous classification. If a case exhibited features of multiple categories, it was assigned to the single highest applicable category based on the following order of precedence: Category 5 (bony abnormalities) > Category 4 (ganglion cyst) > Categories 3 or 2 (ligamentous thickening, with “b” subgrades taking precedence over “a”) > Category 1 (normal).

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Figure 1:

Algorithm of classification.

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Figure 2:

The proposed classification system of SHRINK for categorizing Mucoid degeneration of the anterior cruciate ligament (mACL). The Category 1 includes normal anterior cruciate ligament without thickening or signal changes; Category 2 includes mACL with involvement of femoral half (a. <50% thickness increase and b. more than 50% thickness increase); Category 3 includes mACL with involvement of tibial half (a. <50% thickness increase and b. more than 50% thickness increase); Category 4 includes mACL with the presence of intra-ligamentous and/or peri-ligamentous ganglion cyst; and Category 5 includes mACL with associated bony abnormalities, such as subchondral oedema or cystic changes.

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The readers were blinded to the clinical history, patient demographics, and each other’s assessments. To assess the reliability of the proposed classification system, inter-observer agreement was calculated using the intraclass correlation coefficient (ICC 2,1). The frequency distribution of each category within the classification system was determined. Inter-observer reliability was analyzed to evaluate consistency between the two readers.

RESULTS

A total of 100 knee MRI scans were evaluated by two independent, blinded readers using the proposed classification system for mACL. The frequency distribution of observations for each category of the classification system of SHRINK is presented in Table 1. Inter-observer agreement was assessed using the intra-class correlation coefficient (ICC 2,1). The calculated ICC was 0.679 (95% confidence interval: 0.558–0.772). According to the Landis and Koch criteria^[8] for interpreting reliability coefficients, this represents “good” inter-observer agreement. This level of agreement demonstrates that the proposed classification system can be consistently applied across different evaluators [Figure 3].

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Figure 3:

Bland-Altman plot representation of disagreement between the two observers per average rating. The x axis represents the mean rating, and the y axis represents the difference in grades between the two observers. The size of the circle represents the number of observations falling within the group.

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The most frequently assigned category was Category 4, representing cases with intra-ligamentous and/or periligamentous ganglion cysts. Observer 1 identified 35 cases in this category, while Observer 2 identified 29 cases. This category’s prevalence highlights the significance of cystic changes in mACL cases. In contrast, Categories 3a and 3b, which denote mACL with involvement of the tibial half, showed the lowest frequency, reflecting their relative rarity in the evaluated dataset. Minimal discrepancies were noted for these categories between the two observers. Figure 4 shows the representative MRI images of different categories.

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Figure 4:

The representative magnetic resonance images of different categories of SHRINK. (a) Normal anterior cruciate ligament with schematic shown in b; (c) Category 2a with schematic shown in d; (e) Category 2b with schematic shown in f; (g) Category 5 with schematic shown in h; (i-k) Category 4 with schematic shown in l.

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Overall, the results indicate that the proposed classification system of SHRINK aids in distinguishing between varying degrees of mACL involvement. The good inter-observer agreement supports its reliability and potential utility in clinical practice for facilitating consistent communication and decision-making between radiologists and orthopedic surgeons.

DISCUSSION

This study introduces a novel classification system for mucoid degeneration of the mACL based on MRI findings. The classification system aims to standardize reporting and improve diagnostic consistency. Our results demonstrate that the system is reliable, as evidenced by good inter-observer agreement (ICC 0.679), aligning with similar studies that have reported on the reproducibility of imaging-based classification systems for musculoskeletal conditions.^[9,10]

The high prevalence of Category 4 observations (intraligamentous or peri-ligamentous ganglion cysts) aligns with findings from prior research highlighting the association between mACL and cystic changes.^[11-13] Such changes are thought to arise from chronic degeneration and myxoid transformation within the ligament. In addition, the relative rarity of Categories 3a and 3b (tibial half involvement) corresponds to earlier studies, which have noted that degeneration typically begins in the femoral portion of the ligament before progressing.^[14] The proposed classification system’s stratification into specific categories, including the differentiation between femoral and tibial involvement (2a, 2b, 3a, 3b), provides a detailed framework for evaluating the extent of degeneration.

Clinically, the differentiation of mACL into distinct categories has important implications. For instance, identifying cases with associated bony changes (Category 5) may prompt more aggressive management strategies, as such changes can indicate advanced degeneration and potential compromise of joint mechanics.

This study represents an initial step in the validation pathway for a novel mACL classification. While we have demonstrated good inter-observer reliability, the established framework for validating medical classifications also includes establishing content and face validity through formal expert consensus methods (e.g., Delphi technique, consensus workshops). Our work provides a concrete, reliable framework on which such expert review can now be conducted. Future research must prioritize this next phase to assess the clinical relevance and appropriateness of each category, followed by multi-center studies to evaluate criterion validity against patient symptoms, arthroscopic findings, and treatment outcomes.

This study focused solely on imaging characteristics and did not correlate the proposed categories with specific clinical symptoms or patient-reported outcomes. Future prospective studies are needed to establish the clinical relevance and prognostic value of each category, which is a logical and necessary next step in the validation process. Future research should focus on integrating this classification system into clinical workflows to assess its impact on diagnostic accuracy, treatment decision-making, and patient outcomes. Prospective studies correlating MRI findings with arthroscopic and histopathological results would further enhance the validity of the proposed categories. Finally, exploring the natural history of mACL within the framework of this classification may provide insights into its progression and long-term impact on knee function.

Several limitations of this study should be acknowledged. The retrospective, single-center design and the lack of correlation with clinical symptoms or surgical findings mean that the clinical relevance and prognostic value of the proposed categories and hierarchy are not yet defined. While the hierarchical rule provides essential logical consistency, its basis in clinical severity is presumptive and requires validation.

For this classification system to remain relevant and evidence-based, a structured process for maintenance and updates is required. We propose that long-term stewardship is best undertaken by relevant professional societies in musculoskeletal radiology and orthopedic surgery. An ideal pathway would involve the formation of a society-endorsed committee to oversee periodic reviews, integrate new evidence, manage user feedback, and issue versioned updates. Establishing such a governance structure will be a key focus of our efforts to promote this system beyond its initial publication.

CONCLUSION

The proposed classification system of SHRINK for mACL offers a structured and reliable approach for evaluating this under-recognized condition. By facilitating standardized communication and enhancing diagnostic precision, it has the potential to improve patient management and guide future research.