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We propose a new technique, with double bundle, double tibial tunnels with a bridge between them, using the hamstrings as auto-grafts, retaining either their central or peripheral attachment. A prospective series of 41 patients underwent primary reconstruction of the anterior cruciate ligament by one surgeon, arthroscopically and electronically assisted; 37 were men and 4 were women with a mean age of 24.7 years. The mean follow-up was 19.05 (12-30) months. Normal function and joint stability was achieved. The patients returned to full occupational activities within 3-6 months after the operation. The function of hamstrings was not disturbed. Two patients have sustained a new injury without rupture of the grafts. The Noulis-Lachman test was negative in 35 knees. Positive Pivot shift, post-operatively, was present in 15.45% of patients. The IKDC score was 84.55. In the proposed ACL reconstruction technique, the two tendons are transferred and used as grafts, with gracillis and semitendinosus retaining their distal and central attachment, respectively; the former superimposed upon the latter while entering the femoral tunnel. The tibial tunnels leave a bone bridge ranging between 12 and 15 mm within the footprints of ACL. The two bundles are tensioned, each at different angle. This configuration imitates both the anatomy and the function of ACL and controls not only the anterior translation, but also the rotatory stability. With this innovative technique, the final outcome is improved, thus being closer to normal, as evidenced from previous experiments and the present prospective series. [ABSTRACT FROM AUTHOR]

This paper provides an in-depth analysis of the clinical applications of artificial intelligence (AI) in Nuclear Medicine, focusing on three key areas: neurology, cardiology, and oncology. Beginning with neurology, specifically Alzheimer's disease and Parkinson's disease, the paper examines reviews on diagnosis and treatment planning. The same pattern is followed in cardiology studies. In the final section on oncology, the paper explores the various AI applications in multiple cancer types, including lung, head and neck, lymphoma, and pancreatic cancer., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

No one can deny the significant impact of artificial intelligence (AI) on everyday life, especially in the health sector where it has emerged as a crucial and beneficial tool in Nuclear Medicine (NM) and molecular imaging. The objective of this review is to provide a summary of the various applications of AI in single-photon emission computed tomography (SPECT) and positron emission tomography (PET), with or without anatomical information (CT or magnetic resonance imaging (MRI)). This review analyzes subsets of AI, such as machine learning (ML) and Deep Learning (DL), and elaborates on their applications in NM imaging (NMI) physics, including the generation of attenuation maps, estimation of scattered events, depth of interaction (DOI), time of flight (TOF), NM image reconstruction (optimization of the reconstruction algorithm), and low dose imaging.

Introduction: Carotid cavernous fistulas (CCFs) are rare, usually follow head trauma or aneurysmal rupture. Recent treatment options include endovascular techniques such as flow diversion devices (FDDs)., Objective: To present our case treated with FDD application with transarterial cavernous-sinus coiling and present a systematic review on the use and effectiveness of FDDs in CCF treatment., Materials and Methods: We present our case of CCF treatment with FDD. A search was also conducted in PubMed, EMBASE and Cochrane until November 2020. Reference lists were also cross-checked., Results: Including our case, thirty-eight patients were identified with a CCF that was treated with FDDs in sixteen studies. Twenty-two patients were females, nine were males and the rest unidentified. The mean age was 52,6 years (range 17-86, SD± 19.28). Thirty-six patients suffered from direct and two from indirect CCFs. Single FDD was used in four cases, single FDD with embolic materials in eleven cases, multiple overlapping FDDs were used in six cases and multiple overlapping FDDs with embolic materials were used in seventeen cases. Thirty-five patients (92,1%) had clinical improvement, immediate angiographic occlusion was seen in 44,7% of the cases, while long-term occlusion rate was 100% but with variable follow-up periods. One patient (2,6%) presented with a neurological deficit related to FDD deployment., Conclusion: Targeted treatment of CCFs with single or overlapping FDDs with or without adjunct embolic agents offers a high success rate, both clinically and long-term angiographically compared to other endovascular methods alone. However, further research with multi-center prospective trials is warranted.

Objective: In this study, the three-dimensional (3D) modification of root canal curvature was measured, after the application of Reciproc instrumentation technique, by using cone beam computed tomography (CBCT) imaging and a special algorithm developed for the 3D measurement of the curvature of the root canal., Materials and Methods: Thirty extracted upper molars were selected. Digital radiographs for each tooth were taken. Root curvature was measured by using Schneider method and they were divided into three groups, each one consisting of 10 roots, according to their curvature: Group 1 (0°-20°), Group 2 (21°-40°), Group 3 (41°-60°). CBCT imaging was applied to each tooth before and after its instrumentation, and the data were examined by using a specially developed CBCT image analysis algorithm., Results: The instrumentation with Reciproc led to a decrease of the curvature by 30.23% (on average) in all groups., Conclusions: The proposed methodology proved to be able to measure the curvature of the root canal and its 3D modification after the instrumentation.

Subspace learning (SL) is one of the most useful tools for image analysis and recognition. A large number of such techniques have been proposed utilizing a priori knowledge about the data. In this paper, new subspace learning techniques are presented that use symmetry constraints in their objective functions. The rational behind this idea is to exploit the a priori knowledge that geometrical symmetry appears in several types of data, such as images, objects, faces, and so on. Experiments on artificial, facial expression recognition, face recognition, and object categorization databases highlight the superiority and the robustness of the proposed techniques, in comparison with standard SL techniques.

The planar topography of the anterior cruciate ligament (ACL) insertion was investigated and correlated to the use of the double-bundle/double tibial tunnel ACL reconstruction technique within the ACL tibial insertion area. The anteroposterior and mediolateral length of the tibial ACL attachment and the distances of the tibial insertion area from the anterior and posterior tibial borders were measured and the stability of the joint was tested using the double-bundle/double tibial tunnel ACL reconstruction technique. The anteroposterior length, 19.54 mm in men and 17.36 mm in women, of the ACL insertion, averaged approximately 40% of the total intercondylar anteroposterior dimension of the plateau. This broad distribution of insertion fibres ensures ligament tension and hence joint stability. The reported anteroposterior broad insertion of ACL fibres to the tibia is not sufficiently reproduced by the use of one or more bundles having a common tibial tunnel for the ACL reconstruction. In our view, this might be better achieved with two different bundles, with separate tunnels, and independent tensioning in different knee angles. This technique might achieve better results in human knee stability as opposed to other reported techniques.