Novel Technologies in the Assessment of Patellofemoral Pain: Comparison
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Patellofemoral pain (PFP) is a common clinical condition especially in the young active population. It refers to pain during activities behind or around the patella and has a gradual onset with increased frequency or duration. The literature for PFP reports concerns for the high incidence, prevalence numbers, disability levels, and poor prognosis. 

  • patellofemoral pain
  • technology-based assessment
  • biomechanics
  • medical imaging
  • gait analysis
  • electromyography
  • clinical evaluation

1. Introduction

Patellofemoral pain (PFP) is a common clinical condition especially in the young active population. It refers to pain during activities behind or around the patella and has a gradual onset with increased frequency or duration [1]. The literature for PFP reports concerns for the high incidence, prevalence numbers, disability levels, and poor prognosis [2,3][2][3]. Diagnosis of PFP relies mainly on clinical examination and imaging. Differential diagnosis is key to separate it from other possible causes of pain such as osteoarthritis and chondromalacia patellae. However, since it is a syndrome with unclear pathogenesis and still-debated biomechanics, understanding the causative reasons and clinical characteristics is a challenge for health professionals [4,5][4][5].
Associated with the large general developments of the technology, studies using state-of-the-art instruments and techniques, also during execution of daily living motor tasks, are growing rapidly by examining PFP patients through kinematic and kinetic analyses, imaging technologies, electromyography (EMG), isokinetics, etc. Unfortunately, results gathered from imaging and assessment measures can hardly be merged or compared, because of different factors, such as the reliability of instruments, real-life adaptability of the measure (i.e., somehow predictability of real-life conditions), and the large spectrum of variables [6,7][6][7]. Due to these conflicts, manufacturers focused on developing new technologies to solve the inconsistency in the results and also tried to consider the issues such as cost-effectiveness, fewer side-effects, and practical use. Despite the heterogeneity of the technologies used, a number of studies have recently examined possible innovative technologies, also evaluating their cost-effectiveness, and pros and cons [8,9,10][8][9][10]. These studies have highlighted the relevance of technological innovations in musculoskeletal rehabilitation and their potential to improve the sustainability of healthcare systems for the assessment and management of general patients.
Although measures from medical imaging in static conditions definitely provide valuable information, functional assessments during motor tasks can also provide observations from daily living and in real-time, thus giving access to the dynamic interactions of hard and soft tissues [5,7][5][7]. This has been reported in a number of studies using gait analysis and biomechanical modeling [11,12][11][12]. Now, medical imaging in dynamic and weight-bearing conditions also in 3D are accessible [13,14,15][13][14][15] for these assessments. However, technical experience must become more mature, and costs, radiation, access to these instruments, data post-processing, etc., are known concerns that limit current relevant exploitations [7]. Bi-dimensional analyses are still frequently used, such as those for the frontal plane projection angle [16] and the Q-angle, but modern instrumented gait analysis provides thorough 3D dynamic measurements of joint kinematics and kinetics [17[17][18],18], in real-time and also synchronized with surface EMG.

2. Biomechanical Analyses

There has been an increasing number of biomechanical studies in recent decades. This may be accounted for by the development of kinematic and kinetic analyses, the first game-changing technologies that later became the gold standard. Biomechanical studies based on state-of-the-art gait analysis are substantial to interpret motion patterns at the knee joints. A number of studies show that excessive load at the patellofemoral joint leads to increased patellofemoral contact force, which can result in altered tibial and femoral kinematics, both in the frontal and transverse planes [30,31][19][20]. Indeed, there is still a debate on these mechanisms, for which biomechanics can provide relevant evidence. To set standardized approaches to the kinematics and kinetics of the major joints of the lower limbs, a number of protocols have been developed and compared [17,18][17][18]. Known limitations include adequate data collection, skin motion artifacts, anatomical landmark identification, and tracking [17]. Appropriate marker positioning is essential to determine the joint kinematics and kinetics, and thus to work out relevant patterns within the gait cycle. The large majority of gait analysis protocols calculate motion of the tibiofemoral joint in the frontal and sagittal planes, and only a few on the transverse plane. Since skin markers should track motion of the underlying bones [5], this assumption is particularly critical for the patella, because of its small motion, small dimension, and the large gliding of the skin. Metal probes have been implanted into the patella to obtain a rigid connection with the markers and thus a reliable joint motion, but this was possible only in in vitro studies [5,32,33,34,35,36,37][5][21][22][23][24][25][26]. Thus, adapting the results of these studies to real patellofemoral joint function and PFP is difficult. Nevertheless, there are studies reporting the placement of skin markers on the patella [38,39,40,41,42,43,44,45][27][28][29][30][31][32][33][34]; however, careful full-text readings revealed that patella movements apparently were not tracked in these articles. The present observation also points out the importance of consistent reports in the literature.

3. Imaging Studies

Radiographic, CT, and MRI evaluations are commonly preferred for differential diagnosis of PFP [46][35]. Initially, anteroposterior and lateral radiographic imaging is involved for the evaluation since it is a simple and quick option to see the patellar position (patella alta, patella baja, mediolateral subluxation) for the first clinical diagnosis [7]. However, CT and MRI imaging have advantages over radiographic assessments since they provide static and dynamic cross-sectional scanning including soft tissues and information about other possible abnormalities [6,7][6][7]. However, all of the imaging techniques offer dynamic evaluations, and all of them have advantages and disadvantages in terms of radiation exposure, acquisition quality, and time limitations [5,47,48,49][5][36][37][38]. Imaging is often performed in the supine position in which the patella is simply not exposed to any muscle forces. However, PFP patients experience symptoms while the patella is exposed to muscle forces such as running and stair ascent and descent. Especially with the advancement in biomechanical analysis and improved understanding of patellar kinematics [30][19], acquisition techniques have become more specific and tailored by applying devices to create weight-bearing conditions. Thus, dynamic assessments have gained importance to provide a real-time interplay of soft tissue and bone structures. In the current review, there were 34 articles using imaging evaluations in weight-bearing and dynamic conditions. Thirty of these used standard MRI, CT, and other radiographic devices with custom-built loading platforms to apply forces at the patello-femoral joint. These platforms were mainly fixed under the feet and allowed the subject to push and release force in their muscles. So far, the technology was well known but the technique was different from static acquisition. However, two studies used CBCT, which is quite a breakthrough version of CT [23,24][39][40]. CBCT is an emerging medical imaging technique forming a cone shape as opposed to the spiral slicing of conventional CT [13]. CBCT uses a rotating platform with a radiation emitter and flat panel detector to gather multiple quick exposures and produce a 3D volumetric image. By projecting a collimated beam with a large rotation around the stationary patient, a complete volumetric three-dimensional data-set is collected. This differs from traditional CT scans, which use a helical 2D fan shape, resulting in slower scanning times and higher radiation dosages. Exposure to less than half the radiation dosage compared to traditional CT has been noted for these foot and ankle scans [50][41]. CBCT also has less image distortion and fewer artifacts associated with patient movement [51][42]. This technique provides convenience by collecting the data very quickly, enables data collection in an up-right posture, and implies less radiation exposure. While up-right evaluation is particularly important for foot and ankle studies, these devices enable visualization and measures of the position of bones and muscles under physiological load, which is much better when compared to CT scans under simulated loading conditions. However, the cone-shaped beam causes scatter interference when radio-opaque materials, like metal, are in the anatomical area of interest. This interference significantly reduces the image quality [51][42]. Regarding the cost-effectiveness, it has been reported that the yearly mean profit can even be over EUR 53,000 in a typical hospital [52][43]. Also, it has been shown that using CBCT shortens the scanning time 77% per patient in the same study.

4. EMG Studies

The number of EMG studies demonstrates the importance of assessing muscle forces in PFP. These studies reported on a wide range of motor tasks and of muscle groups, also including those around the hip and the ankle joints, and both flexors and extensors. However, standard data collection methods and systems were used. Only two studies [27[44][45],28], though the same research team reported the utilization of original high-density surface EMG (HDsEMG) electrodes; this technology enables the placement of several tens of electrodes for each single muscle. HDsEMG is a linear electrode grid array with 16 silver bar electrodes, with a 10 mm interelectrode distance (OT Bioelettronica, Torino, Italy). Each grid comprised 64 electrodes arranged in 5 columns and 13 rows with a single electrode missing in one of the corners. This electrode is claimed to provide information about innervation zones and anatomical factors for the best estimation of neuromuscular activation and regions. Using these electrodes, data from the vastus medialis and vastus lateralis were collected, since these can be placed between the edges of each muscle [27,28][44][45]. Acknowledged advantages of HDsEMGs with respect to traditional bipolar electrodes are a topographical representation of the EMG amplitude, more selective recordings, and reliable motor unit behavior [56,57][46][47]. Another study from the same team aimed to investigate whether Principal Component Analysis (PCA) and non-Negative Matrix Factorization (NMF) can provide similar results when used to identify regional muscle activation from HDsEMG signals and showed that a single factor from either the NMF or PCA explained on average 70% of the variance across channels [58][48]. They found that up to 30% of the variance was explained by regional variations in muscle activity rather than common fluctuations across the muscle, suggesting that a single bipolar electrode would not fully capture the EMG across the whole muscle. HDsEMGs differ from conventional sEMGs in terms of their scopes. Conventional sEMGs are mainly used in movement studies by yielding concurrent information on activity in different muscles. With HDsEMGs, it is possible to subtract information at a single motor unit, and also muscle-fiber conduction velocity can be gathered as in the needle EMG [59][49]. Surface electromyographic amplitude is influenced by factors such as adipose tissue thickness, normalization, cross-talk, and motor unit action potential cancellations [27][44]. As signals are collected from different locations of the muscles, HDsEMG helps to overcome the limitations such as describing activation of the regions within a muscle and taking into account the effect of location of the innervation zone [28][45]. For example, in the selected study, Gallina et al. showed that females with PFP have simpler VM and VL activation strategies, observed as a lower co-activation of regions between VM and VL and a lower redistribution of activation from VL to VM when the concentric and eccentric phases of the knee extension are compared by using this novel electrode [28][45]. HDsEMG is an electrode that needs uniformity from different perspectives since it is still in a very early stage in terms of clinical applications and the existence of different names for HDsEMGs (high-resolution EMG, multi-array EGM, matrix electrodes). Despite the obvious experimental issues, these novel electrodes may provide relevant information regarding femur muscle characteristics in different motor tasks.

5. Recommendations for Future Studies

5.1. Finite Element Analysis/Calculations/Networks/Artificial Intelligence

These assessment approaches seem to be receiving a lot of attention in the literature and there has been a rise in their number [60,61,62][50][51][52]. These methods either enable large amounts of data to be processed efficiently and yield results [63,64][53][54] or provide very detailed results from a very small number of subjects with detailed assessments [11,61,65,66,67,68,69,70,71,72][11][51][55][56][57][58][59][60][61][62]. They seem to have important potential for future studies, as they are approaches for processing data independent of the technology used. However, the obtained information should be manageable and convertible into useful information at the clinical level. It seems that the development of common approaches to understand the PFP characteristic may be useful for further studies.

5.2. Combined fMRI-, TMS-, and EEG-Based Analysis

By understanding the importance of central nervous system processes that modulate the interaction between pain and sensorimotor control for the people with movement dysfunctions, investigating brain activity has gained popularity in chronic pain patients [73,74][63][64]. This has led researchers toward technological evaluation methods that can be used to investigate the relationship between brain-activity-related signals and PFP. In the current review, there were studies using functional MRI (fMRI), electroencephalography (EEG), and transcranial magnetic resonance (TMS) imaging techniques to evaluate patient differences or the effectiveness of taping or exercise [73,74,75,76,77,78,79,80][63][64][65][66][67][68][69][70].

5.3. Ultrasonographic Imaging

Ultrasonographic evaluations are frequently used in the clinic because of their easy access and use. Although this is not in itself a novel technology, some its novel features can be taken into consideration in the future to understand the soft tissue properties in PFP through elastographic, architectural, and echo-intensity feature assessments of muscles [82,83,84][71][72][73]. In addition, with the introduction of portable systems and transducer fixation devices, dynamic skeletal muscle evaluation has become possible during different motor tasks [85][74].

5.4. Acoustic Emission

Acoustic emission is a technique used to detect the waveform features, which has been shown to provide potential biomarkers collected from the knee joint. Shark et al. conducted a study on osteoarthritis patients to demonstrate the differences in the knee from degeneration and age in the flexion–extension-related tasks [86][75]. The results showed that there was higher movement variation and increased asymmetry in the patient group compared to healthy individuals. Acoustic emission is shown as a measurement reflecting a composite of structural changes and joint loading factors and is highlighted as a potential candidate for relevant future studies [87][76]. However, even collecting data has some challenges such as application difficulties, optimal placement, accessibility, and being a novel method that still needs improvement. It can also be considered as a promising technology with the advantages of being non-invasive and non-radioactive and providing information about internal joint contact forces [88,89][77][78].

5.5. Myotonometry/Reaction Time

In the present search, three new technologies for PFP assessments were found. However, these were not exactly related to the patellofemoral joint but somehow to relevant muscular conditions. One is tensiomyography, which evaluates the muscular mechanical and contractile properties by means of an external electrical stimulus of controlled intensity. It provides information on fatigue, muscle activation, and tone [90][79]. Another one, used in the same study, is a myotonometry device that measures the stiffness of the muscle at rest [90][79]. Both of these assess biomechanical muscular properties in an objective way and have been shown to be of value. Muscle stiffness and fatigue are mentioned in fact to be among possible risk factors for knee-joint-related injuries [91][80]; thus, these new methods may provide original information in addition to EMG. The third method can evaluate the muscle reaction time, i.e., the time from the appearance of unpredictable stimuli to the start of the selected motor response. It includes central processing and motor time that is necessary for motor response. The reaction time was found higher in PFP patients compared to healthy populations, with this being a valuable representation of the central process and motor reaction delay [92,93][81][82]. This assessment can be used as a non-invasive and easy alternative for central deficit assessments.

5.6. Accelerometers

With the increased use of microsensor technology, relevant devices have become available to quantify kinetic and kinematic outcomes. Tibial accelerometers have been used in the past also in vivo, being mounted directly on the bone using transcortical pins to infer tibial axial acceleration from ground reaction forces [94][83]. More recently, skin-mounted accelerometers have been utilized to determine physical activity loading, running kinematics, and even ground reaction forces [95][84]. Being less expensive, user-friendly, and accessible than force plates, skin-mounted tibial accelerometers could be another novel option in research or clinical settings in PFP patients. However, it should be kept in mind that they do not measure vertical ground reaction forces as standard force plates; they are considered accurate and reliable tools to measure lower extremity load in constant-velocity running [95][84].

References

  1. Crossley, K.M.; Callaghan, M.J.; van Linschoten, R. Patellofemoral pain. BMJ 2015, 351, h3939.
  2. Smith, B.E.; Selfe, J.; Thacker, D.; Hendrick, P.; Bateman, M.; Moffatt, F.; Rathleff, M.S.; Smith, T.O.; Logan, P. Incidence and prevalence of patellofemoral pain: A systematic review and meta-analysis. PLoS ONE 2018, 13, e0190892.
  3. Barton, C.J.; Silva, D.D.O.; Morton, S.; Collins, N.J.; Rathleff, M.S.; Vicenzino, B.; Van Middelkoop, M.; Crossley, K.M.; Callaghan, M.J.; Selfe, J. REPORT-PFP: A consensus from the International Patellofemoral Research Network to improve REPORTing of quantitative PatelloFemoral Pain studies. Br. J. Sports Med. 2021, 55, 1135–1143.
  4. Hong, E.; Kraft, M.C. Evaluating anterior knee pain. Med. Clin. 2014, 98, 697–717.
  5. Yu, Z.; Yao, J.; Wang, X.; Xin, X.; Zhang, K.; Cai, H.; Fan, Y.; Yang, B. Research methods and progress of patellofemoral joint kinematics: A review. J. Healthc. Eng. 2019, 2019, 9159267.
  6. Drew, B.T.; Redmond, A.; Smith, T.; Penny, F.; Conaghan, P. Which patellofemoral joint imaging features are associated with patellofemoral pain? Systematic review and meta-analysis. Osteoarthr. Cartil. 2016, 24, 224–236.
  7. Gulati, A.; McElrath, C.; Wadhwa, V.; Shah, J.P.; Chhabra, A. Current clinical, radiological and treatment perspectives of patellofemoral pain syndrome. Br. J. Radiol. 2018, 91, 20170456.
  8. Lippi, L.; Turco, A.; Folli, A.; D’Abrosca, F.; Curci, C.; Mezian, K.; de Sire, A.; Invernizzi, M. Technological advances and digital solutions to improve quality of life in older adults with chronic obstructive pulmonary disease: A systematic review. Aging Clin. Exp. Res. 2023, 35, 953–968.
  9. Rojo, A.; Santos-Paz, J.Á.; Sánchez-Picot, Á.; Raya, R.; García-Carmona, R. FarmDay: A Gamified Virtual Reality Neurorehabilitation Application for Upper Limb Based on Activities of Daily Living. Appl. Sci. 2022, 12, 7068.
  10. Lippi, L.; Turco, A.; Moalli, S.; Nascimben, M.; Curci, C.; de Sire, A.; Rimondini, L.; Invernizzi, M. Quantitative Assessment of Upper-Limb Volume: Implications for Lymphedema Rehabilitation? Appl. Sci. 2023, 13, 9810.
  11. Besier, T.F.; Pal, S.; Draper, C.E.; Fredericson, M.; Gold, G.E.; Delp, S.L.; Beaupré, G.S. The role of cartilage stress in patellofemoral pain. Med. Sci. Sports Exerc. 2015, 47, 2416.
  12. Chen, Y.-J.; Powers, C.M. Comparison of three-dimensional patellofemoral joint reaction forces in persons with and without patellofemoral pain. J. Appl. Biomech. 2014, 30, 493–500.
  13. Leardini, A.; Durante, S.; Belvedere, C.; Caravaggi, P.; Carrara, C.; Berti, L.; Lullini, G.; Giacomozzi, C.; Durastanti, G.; Ortolani, M. Weight-bearing CT Technology in Musculoskeletal Pathologies of the lower limbs: Techniques, initial applications, and preliminary combinations with gait-analysis measurements at the Istituto Ortopedico Rizzoli. In Seminars in Musculoskeletal Radiology; Thieme Medical Publishers: New York, NY, USA, 2019; pp. 643–656.
  14. Lullini, G.; Belvedere, C.; Busacca, M.; Moio, A.; Leardini, A.; Caravelli, S.; Maccaferri, B.; Durante, S.; Zaffagnini, S.; Marcheggiani Muccioli, G.M. Weight bearing versus conventional CT for the measurement of patellar alignment and stability in patients after surgical treatment for patellar recurrent dislocation. La Radiol. Medica 2021, 126, 869–877.
  15. Ruggeri, M.; Gill, H.S.; Leardini, A.; Zaffagnini, S.; MacLeod, A.; Ortolani, M.; Faccia, F.; Grassi, A.; Dal Fabbro, G.; Durante, S. Superimposition of ground reaction force on tibial-plateau supporting diagnostics and post-operative evaluations in high-tibial osteotomy. A novel methodology. Gait Posture 2022, 94, 144–152.
  16. Mansfield, C.; Rethman, K.; Stephens, J.; Di Stasi, S.; Vanetten, L.; Briggs, M. The association and reliability of the frontal plane projection angle during the lateral step down test on knee function in patients with patellofemoral pain. Knee 2022, 36, 87–96.
  17. Leardini, A.; Sawacha, Z.; Paolini, G.; Ingrosso, S.; Nativo, R.; Benedetti, M.G. A new anatomically based protocol for gait analysis in children. Gait Posture 2007, 26, 560–571.
  18. Ferrari, A.; Benedetti, M.G.; Pavan, E.; Frigo, C.; Bettinelli, D.; Rabuffetti, M.; Crenna, P.; Leardini, A. Quantitative comparison of five current protocols in gait analysis. Gait Posture 2008, 28, 207–216.
  19. Bazett-Jones, D.M.; Neal, B.S.; Legg, C.; Hart, H.F.; Collins, N.J.; Barton, C.J. Kinematic and kinetic gait characteristics in people with Patellofemoral Pain: A systematic review and Meta-analysis. Sports Med. 2023, 53, 519–547.
  20. Powers, C.M.; Witvrouw, E.; Davis, I.S.; Crossley, K.M. Evidence-based framework for a pathomechanical model of patellofemoral pain: 2017 patellofemoral pain consensus statement from the 4th International Patellofemoral Pain Research Retreat, Manchester, UK: Part 3. Br. J. Sports Med. 2017, 51, 1713–1723.
  21. Merican, A.M.; Amis, A.A. Iliotibial band tension affects patellofemoral and tibiofemoral kinematics. J. Biomech. 2009, 42, 1539–1546.
  22. Lorenz, A.; Müller, O.; Kohler, P.; Wünschel, M.; Wülker, N.; Leichtle, U.G. The influence of asymmetric quadriceps loading on patellar tracking—An in vitro study. Knee 2012, 19, 818–822.
  23. Belvedere, C.; Leardini, A.; Ensini, A.; Bianchi, L.; Catani, F.; Giannini, S. Three-dimensional patellar motion at the natural knee during passive flexion/extension. An in vitro study. J. Orthop. Res. 2009, 27, 1426–1431.
  24. Belvedere, C.; Ensini, A.; Leardini, A.; Dedda, V.; Feliciangeli, A.; Cenni, F.; Timoncini, A.; Barbadoro, P.; Giannini, S. Tibio-femoral and patello-femoral joint kinematics during navigated total knee arthroplasty with patellar resurfacing. Knee Surg. Sports Traumatol. Arthrosc. 2014, 22, 1719–1727.
  25. Belvedere, C.; Ensini, A.; Tamarri, S.; d’Amato, M.; Barbadoro, P.; Feliciangeli, A.; Rao, A.; Leardini, A. Does navigated patellar resurfacing in total knee arthroplasty result in proper bone cut, motion and clinical outcomes? Clin. Biomech. 2019, 69, 168–177.
  26. Belvedere, C.; Tamarri, S.; Ensini, A.; Durante, S.; Ortolani, M.; Leardini, A. Can Computer-Assisted Total Knee Arthroplasty Support the Prediction of Postoperative Three-Dimensional Kinematics of the Tibiofemoral and Patellofemoral Joints at the Replaced Knee? J. Knee Surg. 2021, 34, 1014–1025.
  27. Bley, A.S.; Correa, J.C.F.; Reis, A.C.D.; Rabelo, N.D.D.A.; Marchetti, P.H.; Lucareli, P.R.G. Propulsion phase of the single leg triple hop test in women with patellofemoral pain syndrome: A biomechanical study. PLoS ONE 2014, 9, e97606.
  28. Dos Reis, A.C.; Correa, J.C.F.; Bley, A.S.; Rabelo, N.D.d.A.; Fukuda, T.Y.; Lucareli, P.R.G. Kinematic and kinetic analysis of the single-leg triple hop test in women with and without patellofemoral pain. J. Orthop. Sports Phys. Ther. 2015, 45, 799–807.
  29. Ferreira, A.S.; de Oliveira Silva, D.; Briani, R.V.; Ferrari, D.; Aragão, F.A.; Pazzinatto, M.F.; de Azevedo, F.M. Which is the best predictor of excessive hip internal rotation in women with patellofemoral pain: Rearfoot eversion or hip muscle strength? Exploring subgroups. Gait Posture 2018, 62, 366–371.
  30. Kalytczak, M.M.; Lucareli, P.R.G.; Dos Reis, A.C.; Bley, A.S.; Biasotto-Gonzalez, D.A.; Correa, J.C.F.; Politti, F. Kinematic and electromyographic analysis in patients with patellofemoral pain syndrome during single leg triple hop test. Gait Posture 2016, 49, 246–251.
  31. Kalytczak, M.M.; Lucareli, P.R.G.; Dos Reis, A.C.; Bley, A.S.; Biasotto-Gonzalez, D.A.; Correa, J.C.F.; Politti, F. Female PFP patients present alterations in eccentric muscle activity but not the temporal order of activation of the vastus lateralis muscle during the single leg triple hop test. Gait Posture 2018, 62, 445–450.
  32. de Almeida Novello, A.; Garbelotti, S., Jr.; dos Anjos Rabelo, N.D.; Ferraz, A.N.; Bley, A.S.; Correa, J.C.F.; Politti, F.; Lucareli, P.R.G. Descending stairs: Good or bad task to discriminate women with patellofemoral pain? Gait Posture 2018, 65, 26–32.
  33. Sayer, T.; Hinman, R.; Paterson, K.; Bennell, K.; Fortin, K.; Timmi, A.; Pivonka, P.; Bryant, A. Differences in hip and knee landing moments across female pubertal development. Med. Sci. Sports Exerc. 2019, 51, 123–131.
  34. Sayer, T.A.; Hinman, R.S.; Paterson, K.L.; Bennell, K.L.; Fortin, K.; Kasza, J.; Bryant, A.L. Differences and mechanisms underpinning a change in the knee flexion moment while running in stability and neutral footwear among young females. J. Foot Ankle Res. 2019, 12, 1.
  35. Thomas, S.; Rupiper, D.; Stacy, G.S. Imaging of the patellofemoral joint. Clin. Sports Med. 2014, 33, 413–436.
  36. Demehri, S.; Thawait, G.K.; Williams, A.A.; Kompel, A.; Elias, J.J.; Carrino, J.A.; Cosgarea, A.J. Imaging characteristics of contralateral asymptomatic patellofemoral joints in patients with unilateral instability. Radiology 2014, 273, 821–830.
  37. Mariani, S.; La Marra, A.; Arrigoni, F.; Necozione, S.; Splendiani, A.; Di Cesare, E.; Barile, A.; Masciocchi, C. Dynamic measurement of patello-femoral joint alignment using weight-bearing magnetic resonance imaging (WB-MRI). Eur. J. Radiol. 2015, 84, 2571–2578.
  38. Tanaka, M.J.; Elias, J.J.; Williams, A.A.; Demehri, S.; Cosgarea, A.J. Characterization of patellar maltracking using dynamic kinematic CT imaging in patients with patellar instability. Knee Surg. Sports Traumatol. Arthrosc. 2016, 24, 3634–3641.
  39. Yang, J.-S.; Fredericson, M.; Choi, J.-H. The effect of patellofemoral pain syndrome on patellofemoral joint kinematics under upright weight-bearing conditions. PLoS ONE 2020, 15, e0239907.
  40. Pal, S.; Choi, J.H.; Delp, S.L.; Fredericson, M. Botulinum neurotoxin type A improves vasti muscle balance, patellar tracking, and pain in patients with chronic patellofemoral pain. J. Orthop. Res. 2023, 41, 962–972.
  41. Barg, A.; Bailey, T.; Richter, M.; de Cesar Netto, C.; Lintz, F.; Burssens, A.; Phisitkul, P.; Hanrahan, C.J.; Saltzman, C.L. Weightbearing computed tomography of the foot and ankle: Emerging technology topical review. Foot Ankle Int. 2018, 39, 376–386.
  42. Bailey, J.; Solan, M.; Moore, E. Cone-beam computed tomography in orthopaedics. Orthop. Trauma 2022, 36, 194–201.
  43. Richter, M.; Lintz, F.; de Cesar Netto, C.; Barg, A.; Burssens, A. Results of more than 11,000 scans with weightbearing CT—Impact on costs, radiation exposure, and procedure time. Foot Ankle Surg. 2020, 26, 518–522.
  44. Gallina, A.; Hunt, M.A.; Hodges, P.W.; Garland, S.J. Vastus lateralis motor unit firing rate is higher in women with patellofemoral pain. Arch. Phys. Med. Rehabil. 2018, 99, 907–913.
  45. Gallina, A.; Wakeling, J.M.; Hodges, P.W.; Hunt, M.A.; Jayne Garland, S. Regional vastus medialis and vastus lateralis activation in females with patellofemoral pain. Med. Sci. Sports Exerc. 2019, 51, 411–420.
  46. Martinez-Valdes, E.; Laine, C.; Falla, D.; Mayer, F.; Farina, D. High-density surface electromyography provides reliable estimates of motor unit behavior. Clin. Neurophysiol. 2016, 127, 2534–2541.
  47. Falla, D.; Gallina, A. New insights into pain-related changes in muscle activation revealed by high-density surface electromyography. J. Electromyogr. Kinesiol. 2020, 52, 102422.
  48. Gallina, A.; Garland, S.J.; Wakeling, J.M. Identification of regional activation by factorization of high-density surface EMG signals: A comparison of Principal Component Analysis and Non-negative Matrix factorization. J. Electromyogr. Kinesiol. 2018, 41, 116–123.
  49. Drost, G.; Stegeman, D.F.; van Engelen, B.G.; Zwarts, M.J. Clinical applications of high-density surface EMG: A systematic review. J. Electromyogr. Kinesiol. 2006, 16, 586–602.
  50. Cheng, R.; Crouzier, M.; Hug, F.; Tucker, K.; Juneau, P.; McCreedy, E.; Gandler, W.; McAuliffe, M.J.; Sheehan, F.T. Automatic quadriceps and patellae segmentation of MRI with cascaded U2-Net and SASSNet deep learning model. Med. Phys. 2022, 49, 443–460.
  51. Yao, J.; Yang, B.; Niu, W.; Zhou, J.; Wang, Y.; Gong, H.; Ma, H.; Tan, R.; Fan, Y. In vivo measurements of patellar tracking and finite helical axis using a static magnetic resonance based methodology. Med. Eng. Phys. 2014, 36, 1611–1617.
  52. Robert, B.; Boulanger, P. Automatic Bone Segmentation from MRI for Real-Time Knee Tracking in Fluoroscopic Imaging. Diagnostics 2022, 12, 2228.
  53. Reddy, S.; Fox, J.; Purohit, M.P. Artificial intelligence-enabled healthcare delivery. J. R. Soc. Med. 2019, 112, 22–28.
  54. Bisson, L.J.; Komm, J.T.; Bernas, G.A.; Fineberg, M.S.; Marzo, J.M.; Rauh, M.A.; Smolinski, R.J.; Wind, W.M. How accurate are patients at diagnosing the cause of their knee pain with the help of a web-based symptom checker? Orthop. J. Sports Med. 2016, 4, 2325967116630286.
  55. Dagneaux, L.; Allal, R.; Pithioux, M.; Chabrand, P.; Ollivier, M.; Argenson, J.-N. Femoral malrotation from diaphyseal fractures results in changes in patellofemoral alignment and higher patellofemoral stress from a finite element model study. Knee 2018, 25, 807–813.
  56. Ho, K.-Y.; Keyak, J.H.; Powers, C.M. Comparison of patella bone strain between females with and without patellofemoral pain: A finite element analysis study. J. Biomech. 2014, 47, 230–236.
  57. Islam, K.; Duke, K.; Mustafy, T.; Adeeb, S.M.; Ronsky, J.L.; El-Rich, M. A geometric approach to study the contact mechanisms in the patellofemoral joint of normal versus patellofemoral pain syndrome subjects. Comput. Methods Biomech. Biomed. Eng. 2015, 18, 391–400.
  58. Liao, T.-C.; Keyak, J.H.; Powers, C.M. Runners with patellofemoral pain exhibit greater peak patella cartilage stress compared with pain-free runners. J. Appl. Biomech. 2018, 34, 298–305.
  59. Liao, T.-C.; Powers, C.M. Tibiofemoral kinematics in the transverse and frontal planes influence the location and magnitude of peak patella cartilage stress: An investigation of runners with and without patellofemoral pain. Clin. Biomech. 2019, 62, 72–78.
  60. Liao, T.-C.; Yang, N.; Ho, K.-Y.; Farrokhi, S.; Powers, C.M. Femur Rotation Increases Patella Cartilage Stress in Females with Patellofemoral Pain. Med. Sci. Sports Exerc. 2015, 47, 1775–1780.
  61. Pal, S.; Besier, T.F.; Gold, G.E.; Fredericson, M.; Delp, S.L.; Beaupre, G.S. Patellofemoral cartilage stresses are most sensitive to variations in vastus medialis muscle forces. Comput. Methods Biomech. Biomed. Eng. 2019, 22, 206–216.
  62. Graf, E.S.; Stefanyshyn, D. The effect of shoe torsional stiffness on lower extremity kinematics and biomechanical risk factors for patellofemoral pain syndrome during running. Footwear Sci. 2012, 4, 199–206.
  63. Diekfuss, J.A.; Grooms, D.R.; Nissen, K.S.; Coghill, R.C.; Bonnette, S.; Barber Foss, K.D.; Dudley, J.A.; Berz, K.; Logan, K.; Gubanich, P. Does central nervous system dysfunction underlie patellofemoral pain in young females? Examining brain functional connectivity in association with patient-reported outcomes. J. Orthop. Res. 2022, 40, 1083–1096.
  64. Ho, K.-Y.; Liang, J.N.; Budge, S.; Madriaga, A.; Meske, K.; Nguyenton, D. Brain and Spinal Cord Adaptations Associated with Patellofemoral Pain: A Systematic Review and Meta-Analysis. Front. Integr. Neurosci. 2022, 16, 4.
  65. Foss, K.D.B.; Slutsky-Ganesh, A.B.; Diekfuss, J.A.; Grooms, D.R.; Simon, J.E.; Schneider, D.K.; Jayanthi, N.; Lamplot, J.D.; Hill, D.; Pombo, M. Brain Activity During Experimental Knee Pain and Its Relationship with Kinesiophobia in Patients With Patellofemoral Pain: A Preliminary Functional Magnetic Resonance Imaging Investigation. J. Sport Rehabil. 2022, 31, 589–598.
  66. Callaghan, M.J.; McKie, S.; Richardson, P.; Oldham, J.A. Effects of patellar taping on brain activity during knee joint proprioception tests using functional magnetic resonance imaging. Phys. Ther. 2012, 92, 821–830.
  67. Pattyn, E.; Verdonk, P.; Steyaert, A.; Van Tiggelen, D.; Witvrouw, E. Muscle functional MRI to evaluate quadriceps dysfunction in patellofemoral pain. Med. Sci. Sports Exerc. 2013, 45, 1023–1029.
  68. Slutsky-Ganesh, A.B.; Diekfuss, J.A.; Grooms, D.R.; Simon, J.E.; Anand, M.; Lamplot, J.D.; Jayanthi, N.; Wong, P.K.; Lyle, M.A.; Myer, G.D. A preliminary investigation of the effects of patellar displacement on brain activation and perceived pain in young females with patellofemoral pain. J. Sci. Med. Sport 2022, 25, 385–390.
  69. Te, M.; Baptista, A.F.; Chipchase, L.S.; Schabrun, S.M. Primary motor cortex organization is altered in persistent patellofemoral pain. Pain Med. 2017, 18, 2224–2234.
  70. Ebrahimi, N.; Rojhani-Shirazi, Z.; Yoosefinejad, A.K.; Nami, M. The effects of virtual reality training on clinical indices and brain mapping of women with patellofemoral pain: A randomized clinical trial. BMC Musculoskelet. Disord. 2021, 22, 900.
  71. Botanlioglu, H.; Kantarci, F.; Kaynak, G.; Unal, Y.; Ertan, S.; Aydingoz, O.; Erginer, R.; Unlu, M.C.; Mihmanli, I.; Babacan, M. Shear wave elastography properties of vastus lateralis and vastus medialis obliquus muscles in normal subjects and female patients with patellofemoral pain syndrome. Skelet. Radiol. 2013, 42, 659–666.
  72. Engelina, S.; Robertson, C.J.; Moggridge, J.; Killingback, A.; Adds, P. Using ultrasound to measure the fibre angle of vastus medialis oblique: A cadaveric validation study. Knee 2014, 21, 107–111.
  73. Jeon, H.; Donovan, L.; Thomas, A.C. Exercise-Induced Changes in Femoral Cartilage Thickness in Patients with Patellofemoral Pain. J. Athl. Train. 2023, 58, 128–135.
  74. Sjoerdsma, M.; Caresio, C.; Tchang, B.; Meeder, A.; van de Vosse, F.; Lopata, R. The feasibility of dynamic musculoskeletal function analysis of the vastus lateralis in endurance runners using continuous, hands-free ultrasound. Appl. Sci. 2021, 11, 1534.
  75. Shark, L.-K.; Chen, H.; Quan, W.; Goodacre, J. Acoustic emission and angular movement variations from early adulthood healthy knees to late adulthood osteoarthritic knees. In Proceedings of the 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA, 16–20 August 2016; pp. 2382–2385.
  76. Schlüter, D.K.; Spain, L.; Quan, W.; Southworth, H.; Platt, N.; Mercer, J.; Shark, L.-K.; Waterton, J.C.; Bowes, M.; Diggle, P.J. Use of acoustic emission to identify novel candidate biomarkers for knee osteoarthritis (OA). PLoS ONE 2019, 14, e0223711.
  77. Ozmen, G.C.; Safaei, M.; Lan, L.; Inan, O.T. A novel accelerometer mounting method for sensing performance improvement in acoustic measurements from the knee. J. Vib. Acoust. 2021, 143, 031006.
  78. Scherpereel, K.L.; Bolus, N.B.; Jeong, H.K.; Inan, O.T.; Young, A.J. Estimating knee joint load using acoustic emissions during ambulation. Ann. Biomed. Eng. 2021, 49, 1000–1011.
  79. López-de-Celis, C.; Pérez-Bellmunt, A.; Bueno-Gracia, E.; Fanlo-Mazas, P.; Zárate-Tejero, C.A.; Llurda-Almuzara, L.; Cadellans Arróniz, A.; Rodriguez-Rubio, P.R. Effect of diacutaneous fibrolysis on the muscular properties of gastrocnemius muscle. PLoS ONE 2020, 15, e0243225.
  80. Alentorn-Geli, E.; Alvarez-Diaz, P.; Ramon, S.; Marin, M.; Steinbacher, G.; Boffa, J.J.; Cuscó, X.; Ballester, J.; Cugat, R. Assessment of neuromuscular risk factors for anterior cruciate ligament injury through tensiomyography in male soccer players. Knee Surg. Sports Traumatol. Arthrosc. 2015, 23, 2508–2513.
  81. Zeinalzadeh, A.; Nazary-Moghadam, S.; Hoseinian, S.H.S.; Ebrahimzadeh, M.H.; Imani, E.; Karimpour, S. Intra-and Inter-Session Reliability of Methods for Measuring Reaction Time in Participants with and without Patellofemoral Pain Syndrome. Arch. Bone Jt. Surg. 2021, 9, 102.
  82. Nazary-Moghadam, S.; Imani, E.; Hosseinian, S.H.S.; Zeinalzadeh, A.; Karimpour, S.; Negahban, H. Visuomotor reaction time difference between patellofemoral pain syndrome and healthy individuals: Cross-sectional study. J. Bodyw. Mov. Ther. 2021, 27, 274–280.
  83. Lafortune, M.A.; Lake, M.J.; Hennig, E. Transfer function between tibial acceleration and ground reaction force. J. Biomech. 1995, 28, 113–117.
  84. Raper, D.P.; Witchalls, J.; Philips, E.J.; Knight, E.; Drew, M.K.; Waddington, G. Use of a tibial accelerometer to measure ground reaction force in running: A reliability and validity comparison with force plates. J. Sci. Med. Sport 2018, 21, 84–88.
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