Methods: The UBE approach targeted the ventral part of the superior articular process in the transforaminal UBE setup, specifically for upper lumbar disc herniation, with an approach angle of approximately 30º on the axial plane. Intraoperative navigation was employed to improve puncture accuracy for this relatively unfamiliar surgical technique. Navigation-assisted transforaminal UBE lumbar discectomy was performed on four patients presenting with back or leg discomfort due to disc herniation at the L1–L2 or L2–L3 levels. Results: All patients experienced symptom relief and were discharged on postoperative day 2. Conclusions Transforaminal UBE lumbar discectomy is a viable therapeutic option for upper lumbar paracentral disc herniation, which is typically associated with poor prognosis. Integrating navigation integration into this novel approach enhances precision and safety.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

For patients with a few remaining abutment teeth, traditional removable partial dentures and implant-supported fixed prostheses are common treatment options.However, removable dentures often struggle to provide stability, especially as bone resorption occurs over time. Implant-supported fixed prostheses offer longterm stability but are costly and affected by anatomical and medical factors. A newer option is implant-assisted removable partial dentures, which use a minimal number of implants combined with a surveyed crown. This approach enhances support, retention, and stability while reducing financial and surgical burdens. It also improves the prognosis of the remaining teeth, increases patient satisfaction, and enhances masticatory function, making it a promising alternative to conventional removable dentures.

In cases of partially edentulous patients with insufficient remaining teeth, rotational movement of the denture occurs and prognosis of the remaining teeth is uncertain when restoring with a removable partial denture. Recently, implant-assisted removable partial dentures, where a small number of implants are placed and surveyed crowns are fabricated on the implants to be used as abutments, have been suggested. In this case, the patient had only one remaining tooth in the mandible and implants were placed in both posterior regions to be used as surveyed crowns to restore the patient with an implant-assisted removable partial denture. This approach improved the support, retention, and stability of the denture, resulting in functionally and aesthetically satisfactory outcomes.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

For patients with a few remaining abutment teeth, traditional removable partial dentures and implant-supported fixed prostheses are common treatment options.However, removable dentures often struggle to provide stability, especially as bone resorption occurs over time. Implant-supported fixed prostheses offer longterm stability but are costly and affected by anatomical and medical factors. A newer option is implant-assisted removable partial dentures, which use a minimal number of implants combined with a surveyed crown. This approach enhances support, retention, and stability while reducing financial and surgical burdens. It also improves the prognosis of the remaining teeth, increases patient satisfaction, and enhances masticatory function, making it a promising alternative to conventional removable dentures.

In cases of partially edentulous patients with insufficient remaining teeth, rotational movement of the denture occurs and prognosis of the remaining teeth is uncertain when restoring with a removable partial denture. Recently, implant-assisted removable partial dentures, where a small number of implants are placed and surveyed crowns are fabricated on the implants to be used as abutments, have been suggested. In this case, the patient had only one remaining tooth in the mandible and implants were placed in both posterior regions to be used as surveyed crowns to restore the patient with an implant-assisted removable partial denture. This approach improved the support, retention, and stability of the denture, resulting in functionally and aesthetically satisfactory outcomes.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

For patients with a few remaining abutment teeth, traditional removable partial dentures and implant-supported fixed prostheses are common treatment options.However, removable dentures often struggle to provide stability, especially as bone resorption occurs over time. Implant-supported fixed prostheses offer longterm stability but are costly and affected by anatomical and medical factors. A newer option is implant-assisted removable partial dentures, which use a minimal number of implants combined with a surveyed crown. This approach enhances support, retention, and stability while reducing financial and surgical burdens. It also improves the prognosis of the remaining teeth, increases patient satisfaction, and enhances masticatory function, making it a promising alternative to conventional removable dentures.

In cases of partially edentulous patients with insufficient remaining teeth, rotational movement of the denture occurs and prognosis of the remaining teeth is uncertain when restoring with a removable partial denture. Recently, implant-assisted removable partial dentures, where a small number of implants are placed and surveyed crowns are fabricated on the implants to be used as abutments, have been suggested. In this case, the patient had only one remaining tooth in the mandible and implants were placed in both posterior regions to be used as surveyed crowns to restore the patient with an implant-assisted removable partial denture. This approach improved the support, retention, and stability of the denture, resulting in functionally and aesthetically satisfactory outcomes.