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71 (); 16-22
doi:
10.1016/j.jor.2025.08.042

Pros and cons of the coronal plane alignment of the knee (CPAK) classification in total knee arthroplasty – a narrative review

, , ,
a University Department of Orthopaedic Surgery and Traumatology, Kantonsspital Baselland, CH-4101, Bruderholz, Switzerland
b Department of Clinical Research, Research Group Michael T. Hirschmann, Regenerative Medicine & Biomechanics, University of Basel, CH-4001, Basel, Switzerland

⁎Corresponding author: Michael T. Hirschmann. michael.hirschmann@unibas.ch

Received: , Accepted: ,
Professor P K Surendran Memorial Education Foundation
Disclaimer:
This article was originally published by Reed Elsevier India Pvt. Ltd. and was migrated to Scientific Scholar after the change of Publisher.

Abstract

Abstract

The increasing interest in modern alignment philosophies for total knee arthroplasty has highlighted the need for a more detailed coronal plane alignment classification system to assess preoperative phenotypes and investigate postoperative outcomes. Currently, the two most commonly used classification systems are the functional knee phenotypes (FKP) and the coronal plane alignment of the knee (CPAK) classification. Since its publication in 2021, the CPAK classification has been utilized globally in various knee-related investigations. This study examines the applications of the CPAK classification to date and summarizes its impact on the personalization of knee surgery. The study aims to identify the limitations of current classification systems and to stimulate future research in personalized knee surgery and knee phenotyping.

Keywords

CPAK
Coronal plane alignment of the knee
Knee phenotype
Coronal alignment
Total knee arthroplasty
1

1 Introduction

Along with a more profound understanding of the huge variation in individual knee alignment the long-standing gold standard of mechanical alignment in total knee arthroplasty (TKA) has been challenged over the last decade by a surge of interest in more individualized alignment strategies.1–3 (see Fig. 1)

CPAK phenotypes depicting the relationship between aHKA and JLO. Figure inspired from36.
Fig. 1 CPAK phenotypes depicting the relationship between aHKA and JLO. Figure inspired from36.

The traditional mechanical alignment approach primarily focused on achieving a horizontal joint line and a neutral leg axis optimizing joint mechanics for longevity and minimizing the risk of polyethylene wear and implant loosening. In contrast to systematic alignment philosophies such as mechanical alignment or anatomical alignment, more recent personalized alignment philosophies such as constitutional, adjusted mechanical, kinematic, restricted kinematic, and inverse kinematic alignment, emphasize personalizing alignment to the individual patient's alignment. More interestingly, anatomical alignment, a concept that arise with the implementation of custom-made implants4–6 is currently gaining popularity given its multiple advantages.7,4 Furthermore, it is noteworthy mentioning that due to the overall similar survivorship irrespective of the employed alignment technique the question of optimizing postoperative patient satisfaction is at the forefront of the current debate on alignment philosophies. For this reason, understanding patient-specific knee morphology as well as laxity phenotypes could potentially enrich the understanding of each alignment concept and aid surgeons in deciding the best approach for their patients.8–10 Nevertheless, when implementing specific alignment strategies, it is crucial to precisely characterize the patient's pre- and postoperative alignment to effectively assess the success of the balancing strategy.

Along with these still evolving alignment strategies, the need for a more specific alignment classification beyond the basic and commonly used varus, valgus and neutral description became evident. The two major classification systems available are the functional knee phenotypes (FKP) and the Coronal Plane Alignment of the Knee (CPAK) classification.11,12

In 2021, Samuel MacDessi and his research team introduced the Coronal Plane Alignment of the Knee (CPAK) classification. The new classification aimed to simplify the previous and the more comprehensive functional knee phenotype classification proposed by Hirschmann et al., by focusing on patient's arithmetic hip knee ankle angle (aHKA) and joint line obliquity (JLO). The CPAK classification was designed not only to rationalize knee phenotype categorisation, but also to assist in identifying candidates for kinematic alignment TKA, thereby facilitating a joint line preserving approach to knee arthroplasty with the aim of improving postoperative kinematics. At the same time, while simplifying the phenotype classification may make it easier for surgeons to apply, such simplifications ultimately undermine the generalizability of the phenotype concept, thereby falsely diminishing interest in the topic. Even more importantly, recent evidence suggests that surgeons should be aware of over simplifications due to the fact that within each CPAK group multiple knee morphologies can be found which might alter surgical decision-making when thoroughly considered.13,14 Despite these drawbacks the CPAK classification has provided surgeons with an easily accessible glimpse of the importance of knee morphology and indirectly of knee laxity.

The CPAK classification categorises into a matrix consisting of nine knee types based on two alignment variables: Types I, IV and VII are varus, types II, V and VIII are neutral, and types II, VI and IX are valgus. Types I-III have a distal apex JLO, types IV-VI have a neutral JLO, and type VII-IX have a proximal apex JLO. However, knees with a proximal apex JLO (types VII-IX) are very rare and generally not encountered in common surgical practice, with types I-VI being the main focus in clinical practice. Compared to the more detailed functional knee phenotype classification system by Hirschmann et al.,11 which involves mechanical hip knee ankle angle (mHKA), mechanical lateral distal femoral angle (LDFA) and mechanical medial proximal tibia angle (MPTA) and joint line congruence angle (JLCA), the CPAK classification reduces the clinically relevant knee phenotypes from 43 to 6.12 This reduction enhances the simplicity and practicality of CPAK, making it an easily approachable and valuable tool to describe patient populations and to compare groups in knee-related clinical research.15–20

This review aims to explore the impact that the CPAK classification has had on personalization of knee surgery, summarize its areas of application in clinical research to date, propose future investigations involving CPAK classification and contribute to the ongoing development of a knee alignment classification system that accommodates the wide variability of knee phenotypes.

2

2 CPAK methodology

The CPAK classification relies on a long leg radiograph (LLR) to measure medial proximal tibia angle (MPTA) and lateral distal femoral angle (LDFA). These measurements have an excellent inter- and intra-observer reliability.21 The arithmetic Hip Knee Ankle angle (aHKA) is calculated as the difference between MPTA and LDFA, while joint line obliquity (JLO) is calculated with their sum. Knees are then allocated to specific CPAK types based on a matrix, with the boundaries for a neutral aHKA defined as 0° ±2° and for a neutral JLO as 180° ±3°.

Reliability is one of the most relevant aspects.22 Although excellent intra- and inter-observer reliability have been demonstrated for MPTA and LDFA measurement on LLR,21 caution is advised to avoid sources of error. Compared to CT-based assessments, LLR may underestimate proximal tibial varus due to inaccuracies in identifying tibial weightbearing points on LLR, potentially leading to an underrepresentation of CPAK type I and II knees when LLRs are used.23 Additional sources of error include limb torsion and rotation, beam height, fixed knee flexion and hyperextension. Most studies agree that external rotation overestimates varus, while internal rotation overestimates valgus deformity.24 However, in the presence of a knee flexion contracture, which is common in osteoarthritic patients, these errors may be even more significant. Furthermore, recent studies on knee alignment utilizing deep learning algorithms indicate that several factors, which are typically not considered, such as femoral shaft bowing, condylar mismatch, torsion, and complex wear patterns, play a significant role in the broader concept of what is currently referred to as "knee alignment".11To mitigate such errors, a standardized protocol is recommended when obtaining images and measuring angles.25,26 Investigators should detect knee extension deficits and estimate leg rotation using patellar position and fibular overlap before measuring.24

3

3 Epidemiology of CPAK types

Geographic variability in the distribution of CPAK types has been widely documented.27–30 The original study by MacDessi et al. applied CPAK classification to a Belgian non-arthritic and an Australian osteoarthritic population, identifying CPAK types I (distal apex JLO, varus aHKA), II (distal apex JLO, neutral aHKA) and V (neutral JLO, neutral aHKA) as the most common phenotypes. Subsequently, validation studies have confirmed its applicability across different populations.

Overall, CPAK type I appears more prevalent across both arthritic and non-arthritic populations in Asia, likely due to the higher frequency and greater degree of tibial varus in these populations. Interestingly, in a Chinese osteoarthritic population, the functional knee phenotype classification was found to be more appropriate than CPAK, potentially due to this greater variance in varus deformities that is better represented in the functional knee phenotype classification.31 However, a modification of CPAK classification has been proposed for Asian populations to better represent these differences.32 In a Japanese population, a longitudinal study observed no significant shift in CPAK type distribution with advancing osteoarthritis, although varus deformity in the MPTA, aHKA and HKA did progress significantly.33 This could be attributed to CPAK classification's lack of subcategorization in different degrees of deformity severity.

In contrast, a South African population showed a higher prevalance of valgus-aligned CPAK type III and VI knees,34 however, there is limited literature on CPAK distribution in populations from Africa, as well as Central and South America.

Of course, sex-based differences have also been reported, with CPAK types I and II being more prevalent in males, while a more equal distribution pattern of CPAK types was found in females in an Austrian TKA population.35 However, it is important to note that very recent findings highlight that fine morphological differences exist between males and females12 and that every CPAK group can misclassify specific functional knee phenotypes. For this reason, investigations into sex-based differences across various populations still offer potential for further research.

4

4 Application of CPAK in total knee arthroplasty

The original publication by MacDessi et al. found enhanced ligament balance and less need for re-cuts with a kinematic alignment (KA) approach compared to mechanical alignment (MA), particularly in CPAK type I, II, IV, and V knees.12 Since then, CPAK classification has been used in numerous investigations examining the relationship between preoperative phenotype, alignment strategy and postoperative CPAK type in TKA patients.13,14,37–44 Most of these studies are of retrospective design and investigate how different arthroplasty techniques change or maintain CPAK types from pre-to postoperatively.

Several studies have investigated clinical outcome scores in relation to preoperative CPAK type and postoperative change in phenotype. For instance, Agarwal et al. found no significant difference in patient satisfaction when CPAK types were changed postoperatively45 and despite the common postoperative shift in CPAK type with a MA, this change overall may not impact clinical outcomes significantly.46,47 Conversely, restoring the preoperative CPAK phenotype with a TKA has been associated with improved functional outcomes in another similar study.48 Furthermore, when results of MA TKAs were further analysed for different preoperative phenotypes, knees with a preoperative varus aHKA yielded inferior clinical outcome scores compared to knees with a neutral or valgus aHKA.49

Various studies take the relation between CPAK types and alignment strategies into account. Comparing restricted kinematic alignment (rKA) and MA, Ettinger et al. suggested enhanced clinical outcomes in varus CPAK types with rKA, whereas they did not observe significant differences between rKA and MA in CPAK types with a neutral aHKA.50 Contrarily, in valgus phenotypes, postoperative changes in CPAK type, particularly in preoperative type III knees, may lead to improved activity scores with MA TKA compared to those left in valgus alignment.51 Moreover, preoperative varus phenotypes have been predictive of the need for ligament release in MA TKA.52 These findings align with up-to-date literature, which emphasizes the importance of considering patient-specific alignment, as grouping patients into predefined categories possesses a high risk of misclassification, especially in valgus knees that exhibit considerable variability in morphology and ligamentous laxity.13,30,53

CPAK classification has highlighted the importance of preoperative alignment phenotypes and JLO in clinical outcomes, yet concerns remain about the potential negative effect of an oblique joint line on TKA longevity, especially when the native knee alignment is forcefully changed to fit a mechanically aligned target. Inferior implant survival has been observed in cases where TKA resulted in a varus alignment with an oblique joint line (CPAK I).54 However, this raises the question of whether CPAK classification is differentiating enough to assess varying degrees of joint line obliquity and leg alignment, or if a more refined system would be necessary to determine acceptable levels of JLO and aHKA. A key concept related to intra-compartmental pressure during the gait cycle is the physiological loading of the knee.55 While existing literature consistently reports that the medial compartment is primarily loaded during the flexion-extension cycle, maintaining ligamentous balance is essential when physiological load transfers are desired.56,57 Notably, the growing body of research on the importance of the adductor lever arm indicates that an oblique joint line reduces the lever arm, thereby decreasing the force transferred to the tibial baseplate during gait.58 However, surgeons must be cautious of inter-compartmental laxity differences,53,59 as intra-articular lever arms can easily form on the lateral side in varus knees and on the medial side in valgus knees.60 These lever arms may lead to abnormal load transfer and subclinical instability throughout the gait cycle, resulting in persistent discomfort and reduced patient satisfaction.61

Considering these varied findings, future research should prioritize prospective, randomized studies with focus on limited bias,62 investigating the clinical outcomes63 of different alignment philosophies in TKA, in particular when applied to specific preoperative CPAK phenotypes.

5

5 Unicompartmental knee arthroplasty and CPAK

Preoperative CPAK phenotypes in unicompartmental knee arthroplasties (UKA) are less reported, less widely distributed and most studies focus on medial UKA. In medial UKA cohorts, CPAK types I and II are most prevalent, with type I being more common in males and type V in females.64 Notably, a large proportion of patients (45 %) seem to maintain their CPAK phenotype following UKA, particularly those patients with a preoperative CPAK type II or III knee. Investigating PROMs between CPAK types following UKA, clinical outcomes appear to be superior when CPAK type is preserved postoperatively.65 However, another study reported that while Kujala scores were superior postoperatively, no significant differences were found in Knee Injury and Osteoarthritis Outcome Scores (KOOS) and patient satisfaction among patients who maintained their preoperative CPAK type compared to those who transitioned into another class.66 Accordingly, in lateral UKA, altering the CPAK type postoperatively does not seem to affect outcomes significantly.67 For this reason, current literature needs to be viewed through the lens of surgical relevance. Due to the fact that UKA is designed as a resurfacing procedure within a normal ligamentous envelope, it is therefore expected that the CPAK classification will not have significant contributions to postoperative outcomes given that the JLO concept, although interesting, is overly tolerant under the 177° threshold where the majority of OA patients can be found.

Future prospective studies could focus on comparing alignment correction between severe and minor deformities and assess the impact of JLO changes following UKA.

6

6 Osteotomy and CPAK

The application of CPAK classification extends beyond arthroplasty research, finding applicability in osteotomy planning and research.68–70 In a medial opening wedge high tibia osteotomy (MOWHTO) population of Van Genechten et al. CPAK type I was most prevalent preoperatively and nearly 50 % resulted in a CPAK type VI knee postoperatively.71 Postoperative clinical outcome scores did not differ significantly between preoperative CPAK phenotypes in this cohort. Another study, analysing pre- and postoperative CPAK types following MOWHTO, showed a tendency for valgus progression in patients who transitioned to CPAK type VIII or IX (apex proximal JLO) and a tendency for varus progression when JLO was only corrected to neutral.72 CPAK classification, with its emphasis on JLO, could play an important role in future investigations into osteotomies around the knee, as they most often change JLO and change of leg alignment is the main goal of the procedures. Depending on whether a single-level or two-level osteotomy is performed, the procedure can change both JLO and leg alignment or only leg alignment. In this context, CPAK could be very valuable for assessing pre- and postoperative alignment types, setting alignment goals, and compare clinical outcomes of different osteotomies. As such, CPAK could enhance the precision of osteotomy planning and execution, since the transition of phenotype is a key consideration in these procedures.

7

7 Discussion

The introduction of CPAK classification in 2021 aimed to simplify more detailed classification systems, in particular the functional knee phenotypes (FKP) classification, which relies on four coronal alignment variables: mechanical HKA (mHKA), femoral mechanical angle (LDFA), tibial mechanical angle (MPTA) and Joint Line Congruence Angle (JLCA). However, a comparison of CPAK and functional knee phenotype classification with 520 cases revealed poor correlation between the two systems, likely due to differences in aHKA and mHKA calculation and measurement.73 Unlike the functional knee phenotype classification, which considers three variables, CPAK simplifies the classification on just two: aHKA and JLO. Another difference between the classifications lies in how each variable is subdivided based on its measured value. CPAK divides both aHKA and JLO in one subdivision on each side of the neutral, resulting in a matrix of nine CPAK types, with only 6 being clinically relevant. In contrast, the coronal alignment part of the functional knee phenotype classification offers greater detail, dividing LDFA and MPTA into 5 subdivisions each and mHKA into seven, creating a matrix of 125 possible combinations, of which 43 were represented in a non-arthritic population. While the functional knee phenotype classification may be less easy to apply, it provides a more detailed assessment by accurately accounting for varying degrees of varus and valgus alignment in the tibia and femur. The CPAK classification looses a pertinent part of information due to simplification. Simplification is warranted if no relevant information is lost and the system still remains differentiating enough from a scientific and clinical perspective.

In CPAK classification, the aHKA is the calculated difference of MPTA and LDFA and estimates a patient's constitutional (pre-arthritic) alignment based on bony anatomy from LLR, neglecting joint line convergence that results from asymmetric osteoarthritic cartilage loss. While aHKA correlates strongly with the mHKA of the contralateral healthy leg in unilateral osteoarthritis patients,74 the discrepancy between constitutional (pre-arthritic) alignment and aHKA may be bigger due to bony erosions and flexion contractures in the osteoarthritic knee.12 Additionally, a combination of flexion and rotation can further complicate and distort coronal plane measurements on LLR75 and caution is advised in the presence of an extra-articular knee deformity, where CPAK classification has limited applicability.76

MacDessi et al. highlighted the role of JLO in restoring constitutional phenotypes, to achieve ligament balance and establishing boundaries in individual TKA alignment strategies.77 Several methods of measuring JLO have been described,78 and the approach used in CPAK is one of them. However, this method has been questioned due to its limited correlation when compared to measuring JLO relative to the horizontal.79 The obliquity of the joint line significantly influences load distribution across the knee, especially during gait, when an apex distal joint line may become horizontal due to a shift in center of mass and leg adduction during the stance phase.80 A useful tool to assess JLO during movements may be a closed-leg LLR as it has the potential to mimic JLO during gait.81 However, there is still a lack of comprehensive research on optimal JLO during dynamic activities. In future, pre- and postoperative gait analyses may offer potential for improving our understanding of JLO during movement. Depending on alignment strategy and preoperative phenotype, the JLO can change to different extents with a TKA, potentially affecting ligament balance and joint mechanics.82 Despite the recent emphasis on phenotype restoration in TKA to enhance clinical outcomes and achieve ligament balance, definitive consensus about the “safe zone” of HKA, and JLO has not been found and long-term implications of a highly oblique joint line on TKA biomechanics remain uncertain 83.

Another potential limitation of CPAK is its inability to adequately differentiate between severe and minor deformities. Both aHKA and JLO are divided into only one category on each side of the neutral, which restricts the classification's capacity to capture the full range of coronal alignment phenotypes. For instance, a knee with a −3° aHKA and distal 3° JLO would be classified in the same group with a more severe deformity of −9° varus aHKA and a 10° distal JLO. Although these two cases would likely require different surgical planning and present distinct challenges in achieving balanced gaps, they would both fall under CPAK I classification. However, for neutrally aligned knees, the CPAK and functional phenotype classification may yield similar results. This was also observed in a simulation model that compared optimal alignment strategies for neutrally aligned knees.84

While the CPAK classification does not quantify the degree of deformity, it offers a nine-class matrix, of which only six are clinically represented. CPAK types VII to IX are exceptional among native knees and may only be relevant for knees that altered post-operatively into one of these classes. This raises questions about the validity of the CPAK classification, as it includes types not represented in the general population and overlooks the significant variability of knee alignments within its classes. In the original publication, the authors emphasized the importance to include these rare types to enhance understanding and facilitate postoperative investigations.

Despite advances in robotic assistance and the growing focus on functional alignment and gap balancing, neither the functional knee phenotype classification, nor the CPAK classification account for ligamentous laxity. However, studies comparing stress radiographs and LLR have found a good correlation between aHKA and stress HKA,85,86 suggesting that the CPAK classification may account for ligamentous laxity to some extent. This correlation indicates that aHKA could serve as a useful tool for predicting preoperative ligament laxity and restoring constitutional leg alignment, particularly in varus knees.85,86

Some studies made the effort to analyse CPAK phenotype-specific mediolateral ligament laxity using datasets from robotic platforms, with the aim to individualise alignment strategies according to CPAK phenotype.87 However, there appears to be great variability in mediolateral ligament balance within CPAK phenotypes.88 While JLO and aHKA may help to predict ligament imbalance in certain cases, the correlation is not consistent and applicable across all CPAK classes.88 Additionally, prediction of ligament laxity may be complicated by the fact that CPAK classification does not quantify the severity of a deformity, nor does it separately consider MPTA and LDFA. The simplification is particularly relevant in cases of severe deformities, where a very small MPTA may indicate a lower potential for correction of coronal alignment.89 The absence of these details in CPAK classification raises the question whether a clas-sification system that is limited to coronal bony alignment and lacks quantification of a deformity is sufficient to capture the wide variability of knee phenotypes, including their three-dimensional and soft tissue characteristics.

Functional outcomes in TKA depend on multiple factors, with coronal limb alignment certainly being only one of them. As its name suggests, CPAK classification considers coronal plane knee phenotyping only, yet there is significant variability in knee phenotypes within the transverse and sagittal plane, as well as in the soft tissues. Several studies have emphasized the importance of three-dimensional implant positioning.90 For instance, Ziegenhorn et al. reported a correlation between femoral torsion and CPAK categories, suggesting that the CPAK classification could be extended beyond the coronal plane.91 Conversely, in 2024, a study by MacDessi's research group, which conducted a CT-based analysis of rotational and sagittal alignment correlations between CPAK types, did not find significant differences in femoral rotation across CPAK types. They concluded that their findings do not support extending CPAK classification beyond the coronal plane.92 Minimal Clinical Important Difference and Implementation strategies will be of interest in future studies.93,94

As artificial intelligence continues to evolve in medicine, it offers great potential for further personalizing total knee arthroplasty in future. Artificial intelligence has already enabled LLR assessments,95 and deep learning has automated phenotype assessment.96 Future advances may enable analyses of large datasets encompassing three-dimensional knee alignment and ligament laxity derived from robotic surgery. A comprehensive bony phenotype classification system alongside a detailed laxity phenotype classification, would be crucial for the effective implementation of artificial intelligence in patient-specific robotic-assisted surgery. These classifications would allow for more precise modeling and tailored treatment strategies. In the future, artificial intelligence could potentially propose automated alignment strategies on an individual basis and thereby providing the opportunity to assess long-term outcomes on specific patient populations.

8

8 Conclusion

In summary, the CPAK classification provides a useful system for understanding coronal plane knee phenotypes. While CPAK has shown good usability in guiding surgical strategies and assessing postoperative outcomes, its limitations in addressing the severity of deformities, ligamentous laxity and three-dimensional alignment emphasize the need for further research and improvement. Incorporating artificial intelligence and more comprehensive classifications, possibly by combining multiple systems that extend beyond the coronal plane, could lead to significant advancements in optimizing patient-specific TKA approaches.

Author contributions according to CRediT taxonomy

E.A. writing-original draft, formal analysis; N.M. writing-review and editing, formal analysis; G.M.A. writing-review and editing, visualization; M.T.H. supervision, funding acquisition, writing-review and editing.

Institutional review board statement

Not applicable.

Data availability statement

All data is present in the manuscript. There is no other data repository.

Funding

This research received no external funding.

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