A surgical stapling device particularly suited for endoscopic procedures is described The device includes a handle assembly and an elongated body extending distally from the handle assembly The distal end of the elongated body is adapted to engage a disposable loading unit A control rod having a proximal end operatively connected to the handle assembly includes a distal end extending through the elongated body A control rod locking member is provided to prevent movement of the control rod until the disposable loading unit is fully secured to the elongated body of the stapling device

Surgical Stapling Apparatus

A surgical stapling instrument (1) comprises a body portion (2, 3), a handle (4) and a staple fastening assembly (8). The staple fastening assembly (8) includes a curved cartridge (10), which comprises at least one curved open row of staples, and a curved anvil (22), which is adapted to cooperate with the cartridge (10) for forming the ends of the staples exiting from the cartridge (10). The staple fastening assembly (8) is adapted to allow unobstructed access towards the concave inner faces of the cartridge (10) and the anvil (22). The cartridge (10) can be moved towards the anvil (22) from a spaced position for positioning tissue therebetween to a closed position for clamping the tissue. Preferably, a knife is contained within the cartridge (10) and is positioned such that there is at least one row of staples on at least one side of the knife.

Surgical stapling instrument

Newness and distinctiveness is claimed in the features of ornamentation as shown inside the broken line circle in the accompanying representation.

Display screen or portion thereof with graphical user interface

A surgical instrument can comprise a channel configured to support a staple cartridge and, in addition, an anvil pivotable between open and closed positions relative to the channel. The surgical instrument can further comprise a cutting member configured to incise tissue positioned captured between the staple cartridge and the anvil and, in addition, means for stopping the cutting member prior to a distal end datum, wherein the distal end datum can be defined by the distal-most staple cavity in the staple cartridge. In such embodiments, the incision within the tissue may not extend beyond the portion of the tissue that has been stapled.

Surgical stapling instrument with an articulatable end effector

A surgical severing and stapling instrument, suitable for laparoscopic and endoscopic clinical procedures, clamps tissue within an end effector of an elongate channel pivotally opposed by an anvil. An E-beam firing bar moves distally through the clamped end effector to sever tissue and to drive staples on each side of the cut. The E-beam firing bar affirmatively spaces the anvil from the elongate channel to assure properly formed closed staples, especially when an amount of tissue is clamped that is inadequate to space the end effector. In particular, an upper pin of the firing bar longitudinally moves through an anvil slot and a channel slot is captured between a lower cap and a middle pin of the firing bar to assure a minimum spacing. Forming the E-beam from a thickened distal portion and a thinned proximal strip enhances manufacturability and facilitates use in such articulating surgical instruments.

Articulating surgical stapling instrument incorporating a two-piece e-beam firing mechanism

Endoscopic steering instrument is provided, including an endoscope (80) having distal (82) and proximal (98) ends thereof. In a preferred embodiment, at least one proximal cylinder (92) is disposed in a vicinity of the proximal end, and at least one proximal piston (94) is slidably coupled to the at least one proximal cylinder. A first distal cylinder (88) is disposed at the distal end, and a first distal piston (90) is slidably coupled to the first distal cylinder. A second distal cylinder (88) is disposed at the distal end, and a second distal piston (90) is slidably coupled to the second distal cylinder. A first tube (86) is coupled to the first distal cylinder and a second tube (86) is coupled to the second distal cylinder.

Piston-actuated endoscopic steering system

<h3>Introduction</h3> CT angiography (CTA), the modality of choice for detection of intracranial aneurysms (IA), is widely available at all care levels. Implementing deep learning algorithms (DLA) in the radiologists’ workflow could result in higher detection rates, particularly in smaller centers. We present results of multicenter pre-clinical experience with a new IA detection DLA. <h3>Methods</h3> A DLA was developed at Site 1 to predict the existence and locations of IAs &gt;2 mm in 3D head CTA volumes. It localizes IAs using an improved 3D UNet to regress the bounding boxes of suspicious locations. IA presence is confirmed by a multi-resolution 3D DenseNet at each suspicious location. The model was trained on 436 studies and tested on 696 studies from site 1. To validate robustness against protocol variability, it was retrospectively tested on 337 volumes (149 positives, 188 negatives) from 4 additional sites with various types of scanners. A neuroradiologist/trained fellow from each site annotated bounding boxes around the IAs with 3DSlicer. The model’s performance was assessed by comparing its predicted aneurysm locations to the annotated boxes. <h3>Results</h3> The model achieved a lesion-level sensitivity of 0.72 (95% CI: 0.66 - 0.75) with 1.4 false positives per volume (FPPV, 95% CI: 1.22 - 1.57). Sensitivity ranged 0.84 (1.72 FPPV) - 0.67 (1.40 FPPV) amongst 5 sites. Performance variation was secondary to testing on images from scanners the model had not been trained on (unseen). Removing unseen scanners, the model achieved sensitivity of 0.77 (95% CI: 0.68 - 0.84) with 1.51 FPPV (95% CI: 1.24 - 1.82). Patient-level area under curves (AUCs) on the external sites were comparable to that of site 1 dataset, which was 0.88 (95% CI: 0.84 - 0.92). The model performed better in the detection of internal carotid and anterior communicating artery IAs &gt; 3 mm. <h3>Conclusions</h3> This DLA for IA detection showed robust performance in detecting IAs &gt; 3 mm. DLAs may reliably help detection of IAs on CTA, particularly in the community practices less familiar with intracranial vascular imaging. Different scanners can lead to performance variability. This can be avoided by training with data from different scanners. <h3>Disclosures</h3> <b>D. Wu:</b> 1; C; National Institute of Health. <b>E. Orru’:</b> None. <b>S. Ferraciolli:</b> None. <b>A. Ashok:</b> 1; C; NIHR Academic Clinical Fellowship. <b>A. Sorby-Adams:</b> None. <b>M. Guindy:</b> None. <b>D. Montes:</b> None. <b>A. Medina:</b> None. <b>G. Bianco:</b> None. <b>J. Kaggie:</b> 1; C; NIHR Cambridge BRC. <b>D. Rabina:</b> None. <b>O. Ashush:</b> None. <b>X. Han:</b> None. <b>Y. Baror:</b> None. <b>M. Patel:</b> 4; C; Rhino HealthTech Inc. <b>I. Dayan:</b> 4; C; Rhino HealthTech Inc.. <b>J. Romero:</b> None. <b>R. González:</b> 1; C; National Institute of Health. 2; C; MR Access, Inc.. 4; C; MR Access, Inc.. <b>C. Wald:</b> None. <b>F. Kitamura:</b> 2; C; MD.ai, GE Healthcare. <b>P. Kuriki:</b> None. <b>T. Matys:</b> 1; C; NIHR Cambridge BRC. 2; C; NHS. <b>Q. Li:</b> 1; C; National Institute of Health. 

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Yakov Baror

Papers

Piston-actuated endoscopic steering system

E-107 Multi-center study of a deep learning model for intracranial aneurysm detection in computed tomography angiography