Mayfield: do epônimo ao centro cirúrgico

Introdução: A estabilidade e o correto posicionamento do paciente são alguns dos diversos fatores que influenciam no êxito de uma neurocirurgia. Nesse contexto, o Dr. Frank Mayfield contribuiu com a criação do fixador craniano de três pinos. Objetivo: Avaliar as contribuições do Dr. Mayfield à Neurocirurgia e discutir as principais indicações, cuidados e complicações decorrentes do uso do fixador craniano. Métodos: Busca no banco de dados Pubmed, em quatro etapas, empregando as seguintes combinações: “Mayfield” AND “Neurosurgery” AND “Biography”; “Skull clamp” AND “hemodynamic”; “Mayfield clamp” AND “Surgical instrument” e “Mayfield clamp” AND “Complications”. Ao final, 21 artigos foram incluídos no estudo. Discussão: Frank Mayfield foi um grande neurocirurgião, sendo responsável pela criação de relevantes instrumentos neurocirúrgicos e dentre eles, o fixador craniano de três pinos. Sua utilização, apesar de segura, não é isenta de riscos e demanda do neurocirurgião amplo conhecimento da anatomia craniana. Ainda que incomuns, diferentes complicações já foram descritas, como embolia gasosa venosa, hematoma epidural e fraturas ósseas. Conclusão: É fundamental, ao neurocirurgião, o conhecimento das possíveis complicações associadas ao uso do fixador craniano de Mayfield, bem como o correto manejo de tais eventos adversos.

Real Time Estimator to Perform Targeted Biopsies With a Free-Wrist Robot Despite Large Deformations of the Insertion Orifice

In the context of keyhole surgery, and more particularly of uterine biopsy, the fine automatic movements of a surgical instrument held by a robot with 3 active DOF’s require an exact knowledge of the point of rotation of the instrument. However, this center of rotation is not fixed and moves during an examination. This paper deals with a new method of detecting and updating the interaction matrix linking the movements of the robot with the surgical instrument. This is based on the method of updating the Jacobian matrix which is named the “Broyden method”. It is able to take into account body tissue deformations in real time in order to improve the pointing task for automatic movements of a surgical instrument in an unknown environment.

On dissection of the uterine wall during laparoscopic myomectomy

BACKGROUND: Laparoscopic myomectomy is becoming the leading method of surgical treatment of uterine fibroids while preserving reproductive and menstrual functions. Increasingly, ultrasound energy is used to dissect the myometrium. Meanwhile, the mode and direction of the ultrasound energy supply to minimize damage to the underlying tissues have not been specified. AIM: The aim of this study was to perform a comparative analysis of the myometrium and the fibroid pseudocapsule in the projection of the myoma nodule after dissection using ultrasound energy with different initial characteristics of the surgical instrument. MATERIALS AND METHODS: For comparison, we selected two instruments with a longitudinal ultrasound energy supply with an output frequency of 80 MHz ... 2.5 GHz and 47 kHz at intermittent operating mode of 5/10 sec and one torsion instrument with a transverse ultrasound energy supply with an output frequency of 36 kHz at intermittent operating mode of 3/30 sec. RESULTS: Our study has shown that the smallest zone of irreversible changes is formed when using ultrasound energy with an output frequency of 36 kHz at intermittent operating mode of 3/30 sec with its transverse feed at 90 degrees to the blade, and the largest zone of irreversible changes is formed when using ultrasound energy with an output frequency of 47 kHz at intermittent operating mode of 5/10 sec with its longitudinal feed. CONCLUSIONS: Morphometric studies with an analysis of the depth of necrotic and necrobiotic changes in the myometrial tissue showed that from the standpoint of reproductive surgery, it is preferable to use USE with an output frequency of 36 kHz at intermittent operating mode of 3/30 sec with its transverse feed.

Polyp and Surgical Instrument Segmentation with Double Encoder-Decoder Networks

This paper describes a solution for the MedAI competition, in which participants were required to segment both polyps and surgical instruments from endoscopic images. Our approach relies on a double encoder-decoder neural network which we have previously applied for polyp segmentation, but with a series of enhancements: a more powerful encoder architecture, an improved optimization procedure, and the post-processing of segmentations, based on tempered model ensembling. Experimental results show that our method produces segmentations that show a good agreement with manual delineations provided by medical experts.