A novel trephine design for sinus lift lateral approach. Case report

Various techniques are described in the literature, either by crestal or lateral approach. Sinus augmentation has a high percentage of success, but presents a number of intraoperative and postoperative complications. The most frequent complication is the Schneiderian membrane perforation with a percentage of perforations between 11% and 56% according to authors. The aim of this study is to describe another membrane approach technique for the sinus lateral wall osteotomy that minimizes the risk of Schneiderian membrane perforation. We present a case of a 50 year old patient attended the University Dental Clinic (UDC) of International University of Catalonia for implant and crown treatment due to the loss of a right maxillary first molar. To insert an implant in position 1.6 a computerized tomography (CT) was requested to determine with greater accuracy the quantity of residual crestal bone. It showed a height of 5 mm and width of 8 mm. The lateral osteotomy was performed with a (SLA KIT® -Neobiotech) trephine mounted in the same implant handpiece with which the field for the implant and the implant itself were prepared. It can be concluded that in the case described, the use of trephine drills of the SLA system mounted in a handpiece allows better access to lateral approach due to its perpendicular position relative to the sinus wall minimizing the membrane perforation risk

Relation between bone density and primary implant stability

Aims: This study aims to relate bone density in Hounsfield units (Hu) with the primary implant stability measured by insertion torque (Ncm) and resonance frequency analysis (ISQ). Materials and Methods: Ten patients were included in this study. A total of 54 implant sites were provided from 10 computerized tomography scans. The computerized tomography scan was used for the preoperative evaluation of bone density for each patient. The bone mean density around planned implants was determined with Physioplanet TM software. Bone quality according resistance to drilling, insertion torque and resonance frequency measurements were recorded. Results: A statistically significant relationship was observed between bone quality density and location with ISQ values. Conclusions: This research demonstrates a strong relationship between the bone density values from computerized tomography and the location in the maxillaries. A correlation exists between bone quality, according to the Lekholm and Zarb classification, and Hu computerized tomography values. The primary implant stability measured with resonance frequency analysis depends on bone density values, bone quality and implant location

A population pharmacodynamic model for lactate dehydrogenase and neuron specific enolase to predict tumor progression in small cell lung cancer patients

The development of individualized therapies poses a major challenge in oncology. Significant hurdles to overcome include better disease monitoring and early prediction of clinical outcome. Current clinical practice consists of using Response Evaluation Criteria in Solid Tumors (RECIST) to categorize response to treatment. However, the utility of RECIST is restricted due to limitations on the frequency of measurement and its categorical rather than continuous nature. We propose a population modeling framework that relates circulating biomarkers in plasma, easily obtained from patients, to tumor progression levels assessed by imaging scans (i.e., RECIST categories). We successfully applied this framework to data regarding lactate dehydrogenase (LDH) and neuron specific enolase (NSE) concentrations in patients diagnosed with small cell lung cancer (SCLC). LDH and NSE have been proposed as independent prognostic factors for SCLC. However, their prognostic and predictive value has not been demonstrated in the context of standard clinical practice. Our model incorporates an underlying latent variable (“disease level”) representing (unobserved) tumor size dynamics, which is assumed to drive biomarker production and to be influenced by exposure to treatment; these assumptions are in agreement with the known physiology of SCLC and these biomarkers. Our model predictions of unobserved disease level are strongly correlated with disease progression measured by RECIST criteria. In conclusion, the proposed framework enables prediction of treatment outcome based on circulating biomarkers and therefore can be a powerful tool to help clinicians monitor disease in SCLC