The integration of artificial intelligence and computer-guided technology offers the potential for improving surgical accuracy, reducing complications, and enhancing outcomes. Additionally, advancements such as electromagnetic mallets for bone manipulation and autologous dentin grafts provide promising alternatives for bone regeneration. This study aims to combine these technologies to assess the efficacy and clinical outcomes of AI-assisted, computer-guided crestal sinus lifting with immediate implant placement in periodontally compromised sites.

Implant therapy involving the posterior maxillary region in periodontally compromised patients may involve great difficulties due to the often severely reduced bone volume and the presence of a large maxillary sinus cavity. This problem is perpetuated in periodontally compromised patients. These unfavorable conditions are further compounded by the observations that osseointegration is less frequently achieved in the maxilla than the mandible, probably owing to the inferior quality of the bone in the posterior maxilla with its thin cortical bone layers and large cancellous structures. However, many clinical studies and case reports have been presented that describe methods for circumventing some of these problems through sinus membrane lift procedures, usually in conjunction with bone grafts of different types.

Bone grafts in conjunction with the placement of sinus implants are used to ensure the primary stability of the implant or to function as a scaffold for new bone formation by the host. In contrast, new bone around a sinus implant may be obtained following the placement of bone grafts. It might be expected that the mere lifting of the sinus membrane results in a void in which new bone formation would occur along the principles of guided bone regeneration.

Magneto-dynamic technology exploits the physical principles of electromagnetism to apply controlled forces on a body while minimizing the time of impact. The control and steadiness of the applied forces make the procedures safe for patients and surgeons. William Bonwill patented the first electrified dental mallet in 1873. In the 21st century, the Magnetic Mallet (MM) device exploits magneto-dynamic technology in dental surgery. The MM is composed of a handpiece energized by a power control device, delivering forces by the timing of application. Different inserts could be attached to the handpiece, which pushes a shock wave on its tip according to the surgical procedures. Four force modes are available: 75, 90, 130, and 260 daN. Several authors describe the application of MM in dental extractions, crestal sinus lift, ridge expansion, implant placement, and implant site preparation (osseodensification).

Cone beam computed tomography (CBCT) imaging developments went hand in hand with the increasing use of 3D imaging applications for presurgical planning and transfer of oral implant treatment. The main reasons for the triumph of CBCT are its capabilities of volumetric jaw bone imaging at reasonable costs and doses, with the relative advantage of having compact, affordable, and nearby equipment. For the clinicians involved in implant rehabilitation, the power of a dental 3D dataset is not only situated in the diagnostic field but also in the potential of gathering integrated patient information for presurgical and treatment applications related to oral implant placement. Nowadays, rapid advances in digital technology and computer-aided design/computer-aided manufacturing (CAD/CAM) systems are indeed creating challenging opportunities for diagnosis, surgical implant planning, and delivery of implant-supported prostheses.

Several studies used digital superimposition of optical impressions taken at different time points to assess the volumetric changes that occur after the sinus lifting technique. The rational beyond this was the higher accuracy and the less invasiveness of this assessment method.

Artificial intelligence (AI), a branch of computer science, is a fast-growing field in healthcare. The recent narrative review of Altalhi et al. in 2023, emphasized the integration and implications of AI in dental implantology. Authors concluded that AI's influence is unmistakable, enhancing treatment planning precision, enabling implant brand differentiation, fostering innovative implant designs with finite element analysis, and even venturing into outcome prediction and the promising realm of robotic-guided implant surgeries.

The integration of artificial intelligence (AI) and computer-guided technology offers the potential for improving surgical accuracy, reducing complications, and enhancing outcomes. Additionally, advancements such as electromagnetic mallets (EMMs) for bone manipulation and autologous dentin grafts provide promising alternatives for bone regeneration. This study aims to combine these technologies to assess the efficacy and clinical outcomes of AI-assisted, computer-guided crestal sinus lifting (CSL) with immediate implant placement in periodontally compromised sites.

Inclusion Criteria:

• • Patients requiring sinus augmentation with insufficient bone height (4-7 mm).

  • Indicated for single or multiple implant placements.
  • No systemic contraindications for implant surgery.

Exclusion Criteria:

• • Severe sinus pathology (e.g., chronic sinusitis).

  • History of radiation therapy in the maxillofacial region.
  • Smokers
  • Presence of acute (active) periapical infection.
  • Large chronic periapical lesion.