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This study compared the efficacy of low-level laser therapy (LLLT) versus laser acupuncture therapy (LAT) in patients with temporomandibular disorders (TMDs). In this randomized, double-blind clinical trial, 45 TMD patients were randomly divided into three groups. In group 1 (LLLT), a GaAlAs laser was applied on painful masticatory muscles and TMJs (810 nm, 200 mW, 30 s per point, Gaussian beam, spot size 0.28 cm 2 , 21 J/cm 2 ) two times a week for 5 weeks. In group 2 (LAT), the laser was emitted bilaterally on acupuncture points (ST6, ST7, LI4) with the same settings as the LLLT group. Group 3 (placebo) underwent treatment with sham laser. The patients were evaluated before treatment (T1), after 5 (T2) and 10 (T3) laser applications, and 1 month later (T4). The mandibular range of motion as well as pain intensity in masticatory system was recorded at each interval. There was no significant difference in mouth opening between the groups ( p  > 0.05), but the amount of lateral excursive and protrusive movements was significantly greater in LLLT and LAT groups than the placebo group at some intervals ( p  < 0.05). The overall pain intensity and pain degree at masticatory muscles (except temporal muscle) and TMJs were significantly lower in both experimental groups than the placebo group at most intervals after therapy ( p  < 0.05). Both LLLT and LAT were effective in reducing pain and increasing excursive and protrusive mandibular motion in TMD patients. LAT could be suggested as a suitable alternative to LLLT, as it provided effective results while taking less chair time.

Accurate localisation of mandibular canals in lower jaws is important in dental implantology, in which the implant position and dimensions are currently determined manually from 3D CT images by medical experts to avoid damaging the mandibular nerve inside the canal. Here we present a deep learning system for automatic localisation of the mandibular canals by applying a fully convolutional neural network segmentation on clinically diverse dataset of 637 cone beam CT volumes, with mandibular canals being coarsely annotated by radiologists, and using a dataset of 15 volumes with accurate voxel-level mandibular canal annotations for model evaluation. We show that our deep learning model, trained on the coarsely annotated volumes, localises mandibular canals of the voxel-level annotated set, highly accurately with the mean curve distance and average symmetric surface distance being 0.56 mm and 0.45 mm, respectively. These unparalleled accurate results highlight that deep learning integrated into dental implantology workflow could significantly reduce manual labour in mandibular canal annotations.

ObjectivesMandibular reconstruction after segmental mandibulectomy can be challenging without virtual surgical planning and osteotomy guides. The purpose of this study was to analyze anatomic parameters to facilitate the evaluation of ideal fibula wedge osteotomies to reconstruct the neomandibula in a simple and cost-effective manner without the need for preoperative virtual planning.Materials and methodsComputed tomography scans were acquired from randomly selected patients, and all images were obtained from routine clinical diagnostics, e.g., tumor staging, or preoperatively before reconstruction. Data was used to calculate stereolithographic models of the mandible for length and angle measurements. Statistical analysis was performed (p < 0.05).ResultsCT scans of 100 patients were analyzed: 39 were female and 61 were male patients, mean age was 59.08a. The mandibular arch angle proved to be constant with 241.07 ± 2.39°. The outside B-segment length was 80.05 ± 5.16 mm; the anterior S-segment length was 27.69 ± 3.16 mm. The angle of the mandibular arch showed differences in means (p = 0.004) between age groups, but effect was proved low. No relevant statistical significances were detected.ConclusionsThe development of a mandible reconstruction template tool would benefit the majority of head and neck patients, which is due to a constant mandibular arch angle and symphysis segment length throughout the general patient population, allowing the mimicking of a harmonic mandibular arch with up to three fibula segments.Clinical relevanceThe developed mandible reconstruction template tool can facilitate the fibula wedge osteotomies necessary for reconstruction of an ideal neomandibula providing a novel approach which is simple and cost-effective.

It has been demonstrated that development of three-dimensional printing technology has supported the researchers and surgeons to apply the bone tissue engineering to the oromandibular reconstruction. In this study, poly caprolactone/beta tricalcium phosphate (PCL/β-TCP) scaffolds were fabricated by multi-head deposition system. The feasibility of the three-dimensionally (3D) -printed PCL/β-TCP scaffolds for mandibular reconstruction was examined on critical-sized defect of canine mandible. The scaffold contained the heterogeneous pore sizes for more effective bone ingrowth and additional wing structures for more stable fixation. They were implanted into the mandibular critical-sized defect of which periosteum was bicortically resected. With eight 1-year-old male beagle dogs, experimental groups were divided into 4 groups (n = 4 defects per group, respectively). (a) no further treatment (control), (b) PCL/β-TCP scaffold alone (PCL/TCP), (c) PCL/β-TCP scaffold with recombinant human bone morphogenetic protein-2 (rhBMP-2) (PCL/TCP/BMP2) and (d) PCL/β-TCP scaffold with autogenous bone particles (PCL/TCP/ABP). In micro-computed tomography, PCL/TCP/BMP2 and PCL/TCP/ ABP groups showed significant higher bone volume in comparison to Control and PCL/TCP groups (P < 0.05). In histomorphometric analysis, a trend towards more bone formation was observed in PCL/TCP/BMP2 and PCL/TCP/ABP groups, but the results lacked statistical significance (P = 0.052). Within the limitations of the present study, 3D-printed PCL/β-TCP scaffolds showed acceptable potential for oromandibular reconstruction.

Background This study assessed the clinical outcomes of fixed and removable implant-assisted prostheses for the rehabilitation of atrophied distal extension mandibular ridges. Methods Thirty partially edentulous patients with atrophied distal extension mandibular ridges were randomized to three groups ( n  = 10/group). Group ALF received long implants following alveolar ridge augmentation to support fixed restorations. Group SF received short implants to support fixed restorations. Group OVD received two long implants to support a removable partial denture. The plaque index (MPI), gingival index (MGI), Pocket depth (PD), implant stability (IS), and crestal bone loss (CBL) were assessed: immediately after the prosthesis insertion (T0), six months (T6), and twelve months (T12) later. All groups were assessed for patient satisfaction after 12 months using a visual analogue scale (VAS) survey. Results Implant survival rates were 89.7%, 91.7%, and 85% in the ALF, SF, and OVD groups (Chi-square = 0.972, log-rank test, p  =.673). The ALF and SF groups had significantly greater plaque and gingival scores ( P  <.05) than the OVD group At T6 and T12. The ALF group exhibited significantly higher PD and IS values ( P ˂ 0.05) compared to the OVD group At T6 and T12. The OVD group had the greatest significant CBL values ( P  <.05) at T6 and T12, whereas the SF group presented the lowest significant values. The ALF and SF groups showed the highest significant satisfaction levels ( P  <.05) regarding appearance, esthetics, retention, stability, chewing, bolus quality, and occlusion. On the other hand, the OVD group expressed the highest significant satisfaction ( P  <.05) with surgery, healing, and cleaning. Conclusions Fixed restorations supported by either short implants or long implants inserted in augmented bone are equally successful in the rehabilitation of the atrophic posterior mandible, with improved patient satisfaction than implant-assisted partial dentures. Nevertheless, the SF group had favorable peri-implant soft tissue health and decreased marginal bone loss compared to the ALF group. Conversely, implant-assisted partial overdentures demonstrated favorable peri-implant soft tissue health and increased patient satisfaction regarding surgery and healing compared to fixed restoration. Trial registration Current Trial NCT05978115 (28/07/2023) “Retrospectively registered”.

Computer assisted technologies based on algorithmic software segmentation are an increasing topic of interest in complex surgical cases. However-due to functional instability, time consuming software processes, personnel resources or licensed-based financial costs many segmentation processes are often outsourced from clinical centers to third parties and the industry. Therefore, the aim of this trial was to assess the practical feasibility of an easy available, functional stable and licensed-free segmentation approach to be used in the clinical practice. In this retrospective, randomized, controlled trail the accuracy and accordance of the open-source based segmentation algorithm GrowCut was assessed through the comparison to the manually generated ground truth of the same anatomy using 10 CT lower jaw data-sets from the clinical routine. Assessment parameters were the segmentation time, the volume, the voxel number, the Dice Score and the Hausdorff distance. Overall semi-automatic GrowCut segmentation times were about one minute. Mean Dice Score values of over 85% and Hausdorff Distances below 33.5 voxel could be achieved between the algorithmic GrowCut-based segmentations and the manual generated ground truth schemes. Statistical differences between the assessment parameters were not significant (p<0.05) and correlation coefficients were close to the value one (r > 0.94) for any of the comparison made between the two groups. Complete functional stable and time saving segmentations with high accuracy and high positive correlation could be performed by the presented interactive open-source based approach. In the cranio-maxillofacial complex the used method could represent an algorithmic alternative for image-based segmentation in the clinical practice for e.g. surgical treatment planning or visualization of postoperative results and offers several advantages. Due to an open-source basis the used method could be further developed by other groups or specialists. Systematic comparisons to other segmentation approaches or with a greater data amount are areas of future works.