Update on Hand-Held X-Ray Devices in Dentistry: a Literature Review

In the last two decades, the use of portable intraoral X-ray devices, stabilized by the operator, has increased. While all radiographic devices present an inherent risk from ionizing radiation, improper use of portable devices can increase operator exposure. Use of portable devices on a tripod or powered from a protected area is recommended. However, in highly justified cases, for using without these accessories, recommendations should be followed to reduce operator exposure. Because radioprotection is essential when using X-rays, fixed dental radiographic devices should be favored over portable equipment since the first provides a lower radiation dose to the operator.

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Optimization of X-ray Investigations in Dentistry Using Optical Coherence Tomography

Sensors ◽

10.3390/s21134554 ◽

2021 ◽

Vol 21 (13) ◽

pp. 4554

Author(s):

Ralph-Alexandru Erdelyi ◽

Virgil-Florin Duma ◽

Cosmin Sinescu ◽

George Mihai Dobre ◽

Adrian Bradu ◽

...

Keyword(s):

Optical Coherence Tomography ◽

Radiation Dose ◽

Imaging Techniques ◽

Image Resolution ◽

Optical Coherence ◽

X Rays ◽

High Quality ◽

X Ray

The most common imaging technique for dental diagnoses and treatment monitoring is X-ray imaging, which evolved from the first intraoral radiographs to high-quality three-dimensional (3D) Cone Beam Computed Tomography (CBCT). Other imaging techniques have shown potential, such as Optical Coherence Tomography (OCT). We have recently reported on the boundaries of these two types of techniques, regarding. the dental fields where each one is more appropriate or where they should be both used. The aim of the present study is to explore the unique capabilities of the OCT technique to optimize X-ray units imaging (i.e., in terms of image resolution, radiation dose, or contrast). Two types of commercially available and widely used X-ray units are considered. To adjust their parameters, a protocol is developed to employ OCT images of dental conditions that are documented on high (i.e., less than 10 μm) resolution OCT images (both B-scans/cross sections and 3D reconstructions) but are hardly identified on the 200 to 75 μm resolution panoramic or CBCT radiographs. The optimized calibration of the X-ray unit includes choosing appropriate values for the anode voltage and current intensity of the X-ray tube, as well as the patient’s positioning, in order to reach the highest possible X-rays resolution at a radiation dose that is safe for the patient. The optimization protocol is developed in vitro on OCT images of extracted teeth and is further applied in vivo for each type of dental investigation. Optimized radiographic results are compared with un-optimized previously performed radiographs. Also, we show that OCT can permit a rigorous comparison between two (types of) X-ray units. In conclusion, high-quality dental images are possible using low radiation doses if an optimized protocol, developed using OCT, is applied for each type of dental investigation. Also, there are situations when the X-ray technology has drawbacks for dental diagnosis or treatment assessment. In such situations, OCT proves capable to provide qualitative images.

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Interaction of ionizing radiations with matter

10.1093/med/9780199655212.003.0002 ◽

2015 ◽

Author(s):

Colin J Martin

Keyword(s):

Radiation Dose ◽

Scattered Radiation ◽

Final Section ◽

Radioactive Decay ◽

Photoelectric Effect ◽

X Rays ◽

X Ray ◽

Radiation Fields ◽

Ionizing Radiations ◽

Radiology Image

Interactions of ionizing radiations with matter are fundamental to the practice of radiation protection. They determine the magnitude and distribution of doses in tissues, the performance of detectors and imaging devices, and the attenuating properties of shielding materials. This chapter describes briefly the processes of radioactive decay and the properties of the various particles emitted, and then goes on to consider the interactions of radiation with matter. Electron interactions with metals result in bremsstrahlung and characteristic X-rays that form the basis of X-ray production. The interaction mechanisms of X-rays with tissue, particularly the photoelectric effect and Compton scattering, are inherent in the process of radiology image formation. Understanding the physics behind X-ray interactions so that scattered radiation can be taken into account is crucial in designing methods for accurately measuring radiation dose parameters. The final section deals with the dose related variables involved in measurement of radiation fields.

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A Comparative Systematic Literature Review on Knee Bone Reports from MRI, X-Rays and CT Scans Using Deep Learning and Machine Learning Methodologies

Diagnostics ◽

10.3390/diagnostics10080518 ◽

2020 ◽

Vol 10 (8) ◽

pp. 518 ◽

Cited By ~ 1

Author(s):

Hafsa Khalid ◽

Muzammil Hussain ◽

Mohammed A. Al Ghamdi ◽

Tayyaba Khalid ◽

Khadija Khalid ◽

...

Keyword(s):

Machine Learning ◽

Deep Learning ◽

Literature Review ◽

Ct Scan ◽

Systematic Literature Review ◽

Machine Learning Techniques ◽

Ct Scans ◽

X Rays ◽

X Ray ◽

Learning Techniques

The purpose of this research was to provide a “systematic literature review” of knee bone reports that are obtained by MRI, CT scans, and X-rays by using deep learning and machine learning techniques by comparing different approaches—to perform a comprehensive study on the deep learning and machine learning methodologies to diagnose knee bone diseases by detecting symptoms from X-ray, CT scan, and MRI images. This study will help those researchers who want to conduct research in the knee bone field. A comparative systematic literature review was conducted for the accomplishment of our work. A total of 32 papers were reviewed in this research. Six papers consist of X-rays of knee bone with deep learning methodologies, five papers cover the MRI of knee bone using deep learning approaches, and another five papers cover CT scans of knee bone with deep learning techniques. Another 16 papers cover the machine learning techniques for evaluating CT scans, X-rays, and MRIs of knee bone. This research compares the deep learning methodologies for CT scan, MRI, and X-ray reports on knee bone, comparing the accuracy of each technique, which can be used for future development. In the future, this research will be enhanced by comparing X-ray, CT-scan, and MRI reports of knee bone with information retrieval and big data techniques. The results show that deep learning techniques are best for X-ray, MRI, and CT scan images of the knee bone to diagnose diseases.

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UJI KELAYAKAN PESAWAT SINAR-X TERHADAP PROYEKSI PA (POSTERO-ANTERIOR) DAN LAT (LATERAL) PADA TEKNIK PEMERIKSAAN FOTO THORAX

BULETIN FISIKA ◽

10.24843/bf.2017.v18.i01.p05 ◽

2017 ◽

Vol 18 (1) ◽

pp. 27

Author(s):

Kadek Miniati ◽

Gusti Ngurah Sutapa ◽

I Wayan Balik Sudarsana

Keyword(s):

Radiation Dose ◽

X Rays ◽

Tube Voltage ◽

Limit Values ◽

X Ray ◽

Limit Value ◽

Irradiation Field ◽

Interval Distance ◽

Dosage Guidelines ◽

Feasibility Test

Research has been conducted to determine feasibility test of the X-ray planePA and LAT projections on chest x-ray techniques. The study using a water phantom object as a substitute for patients with variations in interval distance ofthe 100-180 cm. Measurement of radiation dose X-rays performed five repetitions , measurable doses had be read on the device electrometer. Exposition factors to the PA projection using a tube voltage of 75 kV, current and time of 3,2 mAs, the irradiation field areaof (30 x 30) cm2.For the LAT projection tube voltage of 80 kV, current and time of 6,3 mAs, and the irradiation field area of (20 x 30) cm2. It the study of the radiation dose X-ray plane projection PA and LAT is optimal is below the limit value at the level of dosage guidelines BAPETEN No 08 of 2011. Obtained PA projections are below the value of 0,4 mGy while LAT projection is below the value of 1,5 mGy. The radiation dose X-rays plane using a variation of 100-180 cm distance is still below the dose limit values ??, thus meeting the objectives anssurance quality and quality control.

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Evaluation of stray radiation to the operator for five hand-held dental X-ray devices

Dentomaxillofacial Radiology ◽

10.1259/dmfr.20180301 ◽

2019 ◽

Vol 48 (5) ◽

pp. 20180301 ◽

Cited By ~ 1

Author(s):

Richard Smith ◽

Richard Tremblay ◽

Graeme M Wardlaw

Keyword(s):

Digital Image ◽

Protected Area ◽

Ionization Chamber ◽

Portable Devices ◽

X Ray ◽

Air Kerma ◽

Tissue Equivalent ◽

Stray Radiation ◽

The Mean ◽

Occupational Radiation

Objectives: Evaluate stray radiation to the operator, as represented by a plane within the significant zone of occupancy (SZO), produced by five models of hand-held intraoral dental X-ray devices (HIDXDs). Methods: The stray radiation for five models of HIDXDs was measured, using an anthropomorphic tissue-equivalent head phantom as a scattering object. An ionization chamber was used to measure the air kerma (μGy) at 63 positions in a 160 cm high by 60 cm wide plane that was 10 cm behind the X-ray device, identified as being within the SZO. Results: Based on the measured air kerma from stray radiation of five different HIDXDs, the estimated annual air kerma at all measured spatial positions was calculated. When calculated using a median air kerma of 0.8 mGy at the distal end of the cone, as typically required for digital image receptors, 1 the ranges for estimated annual air kerma in the SZO across the devices were 0.14–0.77 mGy for the median, 0.41–1.01 mGy for the mean, and 1.32–2.55 mGy for the maximum. Similarly, when calculated using a median air kerma of 1.6 mGy as typically required for D-speed film, 2 the ranges for estimated annual air kerma across the devices were 0.28–1.54 mGy for the median, 0.83–2.03 mGy for the mean, and 2.64–5.10 mGy for the maximum. Conclusions: From measured air kerma values of stray radiation in the SZO, estimated annual exposures to the operator for HIDXDs are expected to be greater than from conventional wall-mounted or portable devices activated from a protected area (at a distance or behind shielding). HIDXDs should therefore only be used when patient accessibility makes their use necessary and the use of a portable device on a stand or a wall-mounted device is not reasonably feasible. This approach would keep occupational radiation exposures of dental workers as low as reasonably achievable.

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Characterization of the Theorectical Radiation Dose Enhancement from Nanoparticles

Technology in Cancer Research & Treatment ◽

10.1177/153303460700600504 ◽

2007 ◽

Vol 6 (5) ◽

pp. 395-401 ◽

Cited By ~ 87

Author(s):

John C. Roeske ◽

Luis Nuñez ◽

Mark Hoggarth ◽

Edwardine Labay ◽

Ralph R. Weichselbaum

Keyword(s):

Radiation Dose ◽

Enhancement Factor ◽

Low Energy ◽

External Beam ◽

X Rays ◽

Nanoparticle Concentration ◽

Dose Enhancement ◽

X Ray ◽

Delivered Dose

Recently, nanoparticles have been considered as a method of providing radiation dose enhancement in tumors. In order to quantify this affect, a dose enhancement factor (DEF) is defined that represents the ratio of the dose deposited in tumor with nanoparticles, divided by the dose deposited in the tumor without nanoparticles. Materials with atomic numbers (Z) ranging from 25 to 90 are considered in this analysis. In addition, the energy spectrum for a number of external beam x-ray sources and common radionuclides are evaluated. For a nanoparticle concentration of 5 mg/ml, the DEF is < 1.05 for Co-60, Ir-192, Au-198, Cs-137, 6, 18, and 25 MV x-rays for all materials considered. However, relatively large increases in the DEF are observed for 50, 80, 100, and 140 KVp x-rays as well as Pd-103 and I-125. The DEF increases for all sources as Z varies from 25–35. From Z = 40–60, the DEF plateaus or slightly decreases. For higher Z materials (Z>70), the DEF increases and is a maximum for the highest Z materials. High atomic number nanoparticles coupled with low energy external beam x-rays or brachytherapy sources offer the potential of significantly enhancing the delivered dose.

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Deep convolutional approaches for the analysis of Covid-19 using chest X-Ray images from portable devices

10.1101/2020.06.18.20134593 ◽

2020 ◽

Author(s):

Joaquim de Moura ◽

Lucía Ramos ◽

Plácido L. Vidal ◽

Milena Cruz ◽

Laura Abelairas ◽

...

Keyword(s):

Network Architecture ◽

Clinical Decision Making ◽

Clinical Decision ◽

World Health ◽

Portable Devices ◽

Learning Approaches ◽

Portable Equipment ◽

Convolutional Network ◽

X Ray ◽

Chest X Ray

The recent human coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been declared as a global pandemic on 11 March 2020 by the World Health Organization. Given the effects of COVID-19 in pulmonary tissues, chest radiography imaging plays an important role for the screening, early detection and monitoring of the suspected individuals. Hence, as the pandemic of COVID-19 progresses, there will be a greater reliance on the use of portable equipment for the acquisition of chest X-Ray images due to its accessibility, widespread availability and benefits regarding to infection control issues, minimizing the risk of cross contamination. This work presents novel fully automatic approaches specifically tailored for the classification of chest X-Ray images acquired by portable equipment into 3 different clinical categories: normal, pathological and COVID-19. For this purpose, two complementary deep learning approaches based on a densely convolutional network architecture are herein presented. The joint response of both approaches allows to enhance the differentiation between patients infected with COVID-19, patients with other diseases that manifest characteristics similar to COVID-19 and normal cases. The proposed approaches were validated over a dataset provided by the Radiology Service of the Complexo Hospitalario Universitario A Coruña (CHUAC) specifically retrieved for this research. Despite the poor quality of chest X-Ray images that is inherent to the nature of the portable equipment, the proposed approaches provided satisfactory results, allowing a reliable analysis of portable radiographs, to support the clinical decision-making process.

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Tinjauan Literatur Sistematik tentang Deteksi Covid-19 menggunakan Convolutional Neural Networks

Creative Information Technology Journal ◽

10.24076/citec.2021v8i1.261 ◽

2021 ◽

Vol 8 (1) ◽

pp. 9

Author(s):

Buyut Khoirul Umri ◽

Ema Utami ◽

Mei P Kurniawan

Keyword(s):

Neural Network ◽

Neural Networks ◽

Literature Review ◽

Transfer Learning ◽

Convolutional Neural Networks ◽

Large Scale ◽

Image Data ◽

X Rays ◽

X Ray ◽

Chest X Ray

Covid-19 menyerang sel-sel epitel yang melapisi saluran pernapasan sehingga dalam kasus ini dapat memanfaatkan gambar x-ray dada untuk menganalisis kesehatan paru-paru pada pasien. Menggunakan x-ray dalam bidang medis merupakan metode yang lebih cepat, lebih mudah dan tidak berbahaya yang dapat dimanfaatkan pada banyak hal. Salah satu metode yang paling sering digunakan dalam klasifikasi gambar adalah convolutional neural networks (CNN). CNN merupahan jenis neural network yang sering digunakan dalam data gambar dan sering digunakan dalam mendeteksi dan mengenali object pada sebuah gambar. Model arsitektur pada metode CNN juga dapat dikembangkan dengan transfer learning yang merupakan proses menggunakan kembali model pre-trained yang dilatih pada dataset besar, biasanya pada tugas klasifikasi gambar berskala besar. Tinjauan literature review ini digunakan untuk menganalisis penggunaan transfer learning pada CNN sebagai metode yang dapat digunakan untuk mendeteksi covid-19 pada gambar x-ray dada. Hasil sistematis review menunjukkan bahwa algoritma CNN dapat digunakan dengan akruasi yang baik dalam mendeteksi covid-19 pada gambar x-ray dada dan dengan pengembangan model transfer learning mampu mendapatkan performa yang maksimal dengan dataset yang besar maupun kecil.Kata Kunci—CNN, transfer learning, deteksi, covid-19Covid-19 attacks the epithelial cells lining the respiratory tract so that in this case it can utilize chest x-ray images to analyze the health of the lungs in patients. Using x-rays in the medical field is a faster, easier and harmless method that can be utilized in many ways. One of the most frequently used methods in image classification is convolutional neural networks (CNN). CNN is a type of neural network that is often used in image data and is often used in detecting and recognizing objects in an image. The architectural model in the CNN method can also be developed with transfer learning which is the process of reusing pre-trained models that are trained on large datasets, usually on the task of classifying large-scale images. This literature review review is used to analyze the use of transfer learning on CNN as a method that can be used to detect covid-19 on chest x-ray images. The systematic review results show that the CNN algorithm can be used with good accuracy in detecting covid-19 on chest x-ray images and by developing transfer learning models able to get maximum performance with large and small datasets.Keywords—CNN, transfer learning, detection, covid-19

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WHY MEASUREMENT OF RADIATION DOSE BY MEDICAL PHYSICIST AND RADIATION ONCOLOGIST BOTH?

10.36106/gjra/1014375 ◽

2021 ◽

pp. 219-222

Author(s):

Rubina Rubina ◽

Baig M.Q ◽

Kumar Dev

Keyword(s):

Radiation Dose ◽

Gamma Rays ◽

Biological Effect ◽

Radiation Energy ◽

The Body ◽

X Rays ◽

Radiation Oncologist ◽

X Ray ◽

Γ Rays ◽

Different Tissues

Many years after the discovery of X-ray's and gamma rays. They have been used empirically in medicine, later on realized that this approach was dangerous mainly in radiotherapy and up to some extent in diagnostic radiology. Thus Means of measuring x-ray/γ-rays had to be found in terms of unit of x-rays quantity dened and accepted. The magnitude of the biological effect desirable in case therapy and undesirable in case of diagnosis. It depends upon how much radiation energy is absorbed by irradiated material. X-ray dosimetry is the measurement of energy absorbed in any material particularly in different tissues of the body.

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STUDIES ON X-RAY EFFECTS

Journal of Experimental Medicine ◽

10.1084/jem.33.3.299 ◽

1921 ◽

Vol 33 (3) ◽

pp. 299-313 ◽

Cited By ~ 11

Author(s):

James B. Murphy ◽

Raymond G. Hussey ◽

Waro Nakahara ◽

Ernest Sturm

Keyword(s):

Histological Examination ◽

Protected Area ◽

Normal Skin ◽

X Rays ◽

X Ray ◽

Small Areas ◽

Subcutaneous Tissues ◽

Ray Effects

Small areas of the skin in the groin of mice were subjected to an erythema dose of x-rays and a week later a cancer graft was inoculated intracutaneously into the area and at the same time a like graft was inoculated in the same manner in the opposite groin protected from x-rays. The graft in the x-rayed area showed a low percentage of takes, while that in the normal skin gave the usual high percentage When the graft was introduced into the subcutaneous tissues it grew equally as well in the x-rayed area as in the protected area. Histological examination shows the skin layers, a few days after x-ray treatment, to be markedly infiltrated with round cells of the lymphoid type. The reaction did not extend deeper than the skin layers. It is suggested that this local lymphoid reaction induced by the x-rays controls the graft made into the skin, while its absence in deeper tissues accounts for the growth of the grafts more deeply implanted.

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