Handheld Optical System for Pectus Excavatum Assessment

Abstract

Disruptive 3D technologies, such as reverse engineering (RE) and additive manufacturing (AM), when applied in the medical field enable the development of new methods for personalized and non-invasive treatments. When referring to the monitoring of pectus excavatum, one of the most common thoracic malformations, 3D acquisition of the patient chest proved to be a straightforward method for assessing and measuring chest deformation. Unfortunately, such systems are usually available in a dedicated facility, can be operated only by specialized doctors with the support of engineers and can be used only with patients on site. It is therefore impossible to perform any routine check-up when the patient is unable to reach the outpatient clinic. The COVID19 pandemic situation has placed even greater restrictions on patient mobility, worsening this problem. To deal with this issue, a new low-cost portable optical scanner for monitoring pectus excavatum is proposed in this work. The scanner, named Thor 2.0, allows a remote diagnostic approach, offering the possibility to perform routine check-ups telematically. Usability tests confirmed the user-friendly nature of the devised system. The instrument was used at the Meyer Children’s Hospital (Florence, Italy) chest-malformations center to treat PE patients. The performed measurements proved to be in line with the current state of the art.

Disruption Potential Assessment of the Power-to-Methane Technology

“…The disruptive technology theory is usually applied in business and innovation management research and is less frequently applied in technical contexts or for examining new energy technologies. In broader context, technology-and disruption-focused scholars currently pay attention to digital solutions (e.g., [21][22][23][24][25]), and there are few similar disruption-focused studies in energy research (e.g., [26][27][28][29]). For example, Ullah et al [30] examined the adoption of blockchain technology for energy management in developing countries discussing the distributed ledger technology as disruptive.…”

Assessment and treatment of pectus deformities: a review of reverse engineering and 3D printing techniques

“…These studies have proposed several new severity indices, which expand the definition of HI. Instead, other studies have adapted the CI to optical scanning (Lain et al , 2017; Uccheddu et al , 2018; Servi et al , 2020a, 2020b, 2020c, Daemen et al , 2021a, 2021b, 2021c, Fuentes et al , 2021; Servi et al , 2021), also in this case defining a new set of indices. Studies that proposed alternative indices are (Lain et al , 2017) that introduced the “Banana Index” and the “Titanic Index” (Figure 5a and Figure 5b), (Bliss et al , 2019) that used the “Pectus Surface area” and the “Pectus surface Volume ratio”, (Scalabre et al , 2019) that introduced the “External Anthropometric Index” and “External Asymmetry Index”, (Servi et al , 2020a, 2020b, 2020c) that used “Width”, “Area”, “External Asymmetry Index” and “External Eccentricity Index”.…”

“…The second category of targets is the main topic of Glinkowski et al (2009), Lain et al (2017), Uccheddu et al (2018), Kidane et al (2019), Deng et al (2020a, 2020b), Song et al (2020), Servi et al (2021). Perez et al (2006) analyzed the accuracy, resolution and repeatability of the VistusSmart (Human Solutions; Kaiserslautern), concluding that the 3D scanner is suitable for tracking the progression of the deformity and to analyze pre- and post-surgical pathological condition.…”

“…The study showed that the three scanners are comparable in terms of reproducibility, but only the Artec Leo and 3dMD can be considered clinically accurate (with mean accuracies of 0.81 ± 0.71 mm and 0.89 ± 0.66 mm, respectively). On the other hand, several studies (Glinkowski et al , 2009; Lain et al , 2017; Uccheddu et al , 2018; Kidane et al , 2019; Deng et al , 2020a, 2020b, Song et al , 2020; Servi et al , 2021) proposed ad-hoc devices for chest acquisition, combining commercial devices (including Microsoft Kinect v1, Microsoft Kinect v2, Intel RealSense D415) with hardware structures specifically designed to better acquire the region of interest. The realized devices can be divided into multi-camera (Glinkowski et al , 2009; Lain et al , 2017) or single-camera (Uccheddu et al , 2018; Kidane et al , 2019; Deng et al , 2020a, 2020b, Song et al , 2020; Servi et al , 2021) scanners with manual (Deng et al , 2020a, 2020b, Servi et al , 2021), or automatic (Glinkowski et al , 2009; Lain et al , 2017; Uccheddu et al , 2018; Kidane et al , 2019; Song et al , 2020) handling.…”

Morphological characteristics of X-ray thorax images of COVID-19 patients using the Bradley thresholding segmentation

“…We used a standard thorax model from Ercleve [24] as a reference to determine thoracic abnormalities in COVID-19 sufferers. Several other research that use thorax imagery in identifying COVID-19 are the use of the internet of things (IoT) [25], adaptive stratification [26], social approachment [27], blood cell ratio [28], thoraxic surgery [29], tomography images [30], otolaryngology surgery [31], handheld optical system [32], SOM-LWL method [33], therapeutic effects [34], upper respiratory tract [35].…”