Nasal Skin Reconstruction: Time to Rethink the Reconstructive Ladder

Computed tomography (CT) represents the current standard for imaging of patients with acute life-threatening diseases. As some patients present with circulatory arrest, they require cardiopulmonary resuscitation. Automated chest compression devices are used to continue resuscitation during CT examinations, but tend to cause motion artifacts degrading diagnostic evaluation of the chest. The aim was to investigate and evaluate a CT protocol for motion-free imaging of thoracic structures during ongoing mechanical resuscitation. The standard CT trauma protocol and a CT protocol with ECG triggering using a simulated ECG were applied in an experimental setup to examine a compressible thorax phantom during resuscitation with two different compression devices. Twenty-eight phantom examinations were performed, 14 with AutoPulse® and 14 with corpuls cpr®. With each device, seven CT examinations were carried out with ECG triggering and seven without. Image quality improved significantly applying the ECG-triggered protocol (p < 0.001), which allowed almost artifact-free chest evaluation. With the investigated protocol, radiation exposure was 5.09% higher (15.51 mSv vs. 14.76 mSv), and average reconstruction time of CT scans increased from 45 to 76 s. Image acquisition using the proposed CT protocol prevents thoracic motion artifacts and facilitates diagnosis of acute life-threatening conditions during continuous automated chest compression.

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Deep learning–based reconstruction may improve non-contrast cerebral CT imaging compared to other current reconstruction algorithms

European Radiology ◽

10.1007/s00330-020-07668-x ◽

2021 ◽

Author(s):

Luuk J. Oostveen ◽

Frederick J. A. Meijer ◽

Frank de Lange ◽

Ewoud J. Smit ◽

Sjoert A. Pegge ◽

...

Keyword(s):

Deep Learning ◽

White Matter ◽

Image Quality ◽

Iterative Reconstruction ◽

Quality Characteristics ◽

Model Based ◽

Hybrid Iterative Reconstruction ◽

Contrast Ct ◽

Lower Noise ◽

Reconstruction Time

Abstract Objectives To evaluate image quality and reconstruction times of a commercial deep learning reconstruction algorithm (DLR) compared to hybrid-iterative reconstruction (Hybrid-IR) and model-based iterative reconstruction (MBIR) algorithms for cerebral non-contrast CT (NCCT). Methods Cerebral NCCT acquisitions of 50 consecutive patients were reconstructed using DLR, Hybrid-IR and MBIR with a clinical CT system. Image quality, in terms of six subjective characteristics (noise, sharpness, grey-white matter differentiation, artefacts, natural appearance and overall image quality), was scored by five observers. As objective metrics of image quality, the noise magnitude and signal-difference-to-noise ratio (SDNR) of the grey and white matter were calculated. Mean values for the image quality characteristics scored by the observers were estimated using a general linear model to account for multiple readers. The estimated means for the reconstruction methods were pairwise compared. Calculated measures were compared using paired t tests. Results For all image quality characteristics, DLR images were scored significantly higher than MBIR images. Compared to Hybrid-IR, perceived noise and grey-white matter differentiation were better with DLR, while no difference was detected for other image quality characteristics. Noise magnitude was lower for DLR compared to Hybrid-IR and MBIR (5.6, 6.4 and 6.2, respectively) and SDNR higher (2.4, 1.9 and 2.0, respectively). Reconstruction times were 27 s, 44 s and 176 s for Hybrid-IR, DLR and MBIR respectively. Conclusions With a slight increase in reconstruction time, DLR results in lower noise and improved tissue differentiation compared to Hybrid-IR. Image quality of MBIR is significantly lower compared to DLR with much longer reconstruction times. Key Points • Deep learning reconstruction of cerebral non-contrast CT results in lower noise and improved tissue differentiation compared to hybrid-iterative reconstruction. • Deep learning reconstruction of cerebral non-contrast CT results in better image quality in all aspects evaluated compared to model-based iterative reconstruction. • Deep learning reconstruction only needs a slight increase in reconstruction time compared to hybrid-iterative reconstruction, while model-based iterative reconstruction requires considerably longer processing time.

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Maxillofacial Bony Considerations in Facial Transplantation

Facial Plastic Surgery ◽

10.1055/s-0041-1726443 ◽

2021 ◽

Author(s):

Aurora G. Vincent ◽

Anne E. Gunter ◽

Yadranko Ducic ◽

Likith Reddy

Keyword(s):

Soft Tissue ◽

Current Literature ◽

Preoperative Planning ◽

Surgical Anatomy ◽

The Past ◽

Facial Transplantation ◽

Tissue Transfer ◽

Reconstructive Ladder ◽

The Face ◽

Facial Wounds

AbstractAlloplastic facial transplantation has become a new rung on the proverbial reconstructive ladder for severe facial wounds in the past couple of decades. Since the first transfer including bony components in 2006, numerous facial allotransplantations across many countries have been successfully performed, many incorporating multiple bony elements of the face. There are many unique considerations to facial transplantation of bone, however, beyond the considerations of simple soft tissue transfer. Herein, we review the current literature and considerations specific to bony facial transplantation focusing on the pertinent surgical anatomy, preoperative planning needs, intraoperative harvest and inset considerations, and postoperative protocols.

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Surgical Strategies to Promote Cutaneous Healing

Medical Sciences ◽

10.3390/medsci9020045 ◽

2021 ◽

Vol 9 (2) ◽

pp. 45

Author(s):

Ines Maria Niederstätter ◽

Jennifer Lynn Schiefer ◽

Paul Christian Fuchs

Keyword(s):

Wound Healing ◽

Wound Closure ◽

Chronic Wounds ◽

Treatment Algorithm ◽

Surgical Site Infections ◽

Repair Process ◽

Suture Technique ◽

The Body ◽

Wound Debridement ◽

Reconstructive Ladder

Usually, cutaneous wound healing does not get impeded and processes uneventfully, reaching wound closure easily. The goal of this repair process is to restore the integrity of the body surface by creating a resilient and stable scar. Surgical practice and strategies have an impact on the course of wound healing and the later appearance of the scar. By considering elementary surgical principles, such as the appropriate suture material, suture technique, and timing, optimal conditions for wound healing can be created. Wounds can be differentiated into clean wounds, clean–contaminated wounds, contaminated, and infected/dirty wounds, based on the degree of colonization or infection. Furthermore, a distinction is made between acute and chronic wounds. The latter are wounds that persist for longer than 4–6 weeks. Care should be taken to avoid surgical site infections in the management of wounds by maintaining sterile working conditions, using antimicrobial working techniques, and implementing the principles of preoperative antibiotics. Successful wound closure is influenced by wound debridement. Wound debridement removes necrotic tissue, senescent and non-migratory cells, bacteria, and foreign bodies that impede wound healing. Additionally, the reconstructive ladder is a viable and partially overlapping treatment algorithm in plastic surgery to achieve successful wound closure.

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Hand skin reconstruction from skeletal landmarks

International Journal of Legal Medicine ◽

10.1007/s00414-007-0204-4 ◽

2007 ◽

Vol 121 (6) ◽

pp. 511-515 ◽

Cited By ~ 3

Author(s):

P. Lefèvre ◽

S. Van Sint Jan ◽

J. P. Beauthier ◽

M. Rooze

Keyword(s):

Skin Reconstruction

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Revisiting the Reconstructive Ladder

Plastic & Reconstructive Surgery ◽

10.1097/01.prs.0000222224.03137.d5 ◽

2006 ◽

Vol 118 (1) ◽

pp. 267-268 ◽

Cited By ~ 13

Author(s):

Alexandra J. Turner ◽

Nicholas Parkhouse

Keyword(s):

Reconstructive Ladder

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The Reconstructive Ladder

Orthopedic Clinics of North America ◽

10.1016/s0030-5898(20)31815-0 ◽

1993 ◽

Vol 24 (3) ◽

pp. 393-409 ◽

Cited By ~ 24

Author(s):

L. Scott Levin

Keyword(s):

Reconstructive Ladder

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Gene expression advances skin reconstruction and wound repair better on silk fibroin-based materials than on collagen-based materials

Materialia ◽

10.1016/j.mtla.2019.100519 ◽

2020 ◽

Vol 9 ◽

pp. 100519 ◽

Cited By ~ 3

Author(s):

Tomoko Hashimoto ◽

Katsura Kojima ◽

Yasushi Tamada

Keyword(s):

Gene Expression ◽

Silk Fibroin ◽

Wound Repair ◽

Skin Reconstruction

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Reliable Reconstruction of Fine-grained Proofs in a Proof Assistant

Automated Deduction – CADE 28 - Lecture Notes in Computer Science ◽

10.1007/978-3-030-79876-5_26 ◽

2021 ◽

pp. 450-467

Author(s):

Hans-Jörg Schurr ◽

Mathias Fleury ◽

Martin Desharnais

Keyword(s):

Success Rate ◽

Failure Rate ◽

Proof Assistant ◽

Proof Checking ◽

Smt Solver ◽

Fine Grained ◽

Simple Rules ◽

Detailed Evaluation ◽

Reconstruction Time

AbstractWe present a fast and reliable reconstruction of proofs generated by the SMT solver veriT in Isabelle. The fine-grained proof format makes the reconstruction simple and efficient. For typical proof steps, such as arithmetic reasoning and skolemization, our reconstruction can avoid expensive search. By skipping proof steps that are irrelevant for Isabelle, the performance of proof checking is improved. Our method increases the success rate of Sledgehammer by halving the failure rate and reduces the checking time by 13%. We provide a detailed evaluation of the reconstruction time for each rule. The runtime is influenced by both simple rules that appear very often and common complex rules.

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