# Mid-Flexion Instability in Total Knee Arthroplasty: Insights from Robotic-Assisted Surgery
## 9 Challenges, Limitations, and Future Perspectives  
With new insight into MFI, some concerns remain [1; 9]. First, few studies, such as clinical trials, investigate MFI after both conventional and rTKA [1; 9]; moreover, most are laboratory-based or cadaveric [1; 11]. As reported by several authors, this heterogeneity is probably due to the absence of accurate diagnostic criteria because MFI diagnosis is insidious due to the presentation of subtle symptoms [1; 9]. While more recent papers agree to identify MFI as a distinct entity, some studies questioned whether it is separate from flexion and extension instability [1; 9]. In addition, MFI is usually assessed intraoperatively without a preoperative evaluation, and it is essential to underline that this entity does not always lead to postoperative symptoms [9]. Due to the lack of diagnosis, treatment algorithms are not present, so surgeons are trying to mainly address the RFs [1; 9; 15]. Novel technologies such as robotics have gained prominence in contemporary surgical settings to enhance soft tissue balance and prosthetic component placement precision [2; 6; 7; 8; 13; 14; 15; 46]. Through rTKA, robotics are addressing and improving RFs, potentially reducing the risk of MFI [2; 6; 7; 8; 13; 14; 15]. This promising development, however, is not without its challenges. Even in this field, direct studies analyzing mid-flexion are lacking [2; 6; 7; 8; 13; 14; 15]. In this regard, [PERSON] et al. reported an almost anatomical restoration of the joint line position through robotics concerning the conventional method, but only indirectly citing the MFI concept [15]. The adoption of robotics in TKA remains a topic of debate, with an inconclusive demonstration of clear benefits in PROMs [2; 6; 7; 8; 13; 36]. Moreover, incorporating robotics in the operating room means higher costs than traditional techniques [2]. Despite these challenges, the potential of robotics in addressing MFI and improving patient outcomes is a reason for optimism in the field of TKA surgeries. [PERSON] et al. analyzed patients experiencing staged bilateral knee arthroplasty, with one TKA performed with a manual approach and the other with a robotic one [14]. Despite comparable PROMs, rTKA was perceived as more natural and made patients satisfied or very satisfied [14]. For this reason, patients would recommend rTKA to other individuals [14]. A significant issue in the current literature [32; 34; 37; 41] on rTKA is the lack of distinction between robotic systems, particularly image-based versus image-less systems, and various alignment strategies [37; 41; 46]. These factors could play a role in the occurrence of MFI. Image-based systems utilize preoperative imaging to guide the surgery, potentially offering more precise alignment and component positioning. In contrast, image-less systems rely on intraoperative data and may vary in accuracy [32; 41; 46]. Similarly, strategies such as mechanical, kinematic, and functional alignment have different implications for knee joint stability and the risk of MFI [32; 34; 42; 43]. Future studies comparing these variables could provide essential insights into better understanding the impact of rTKA on MFI and improving surgical outcomes. Finally, studies need to clarify diagnostic criteria to make the literature more uniform regarding MFI. Indeed, starting from a definite diagnosis, a correct management algorithm could be performed. Risk factors (RFs) should be evaluated, and their possible impact on MFI should be carefully analyzed. Moreover, MFI should be investigated as a parameter during the surgical procedure and as a postoperative outcome [9]. New risk factors could also be introduced; for instance, [PERSON] et al. presented a potential unexplored factor requiring investigation: the patellar resurfacing effect on MFI [9]. Identifying patients at risk of MFI before surgery is crucial to prevent this outcome by utilizing the most appropriate techniques and implants.