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Volumen 28 (2022): Edición 3 (September 2022)

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Volumen 27 (2021): Edición 4 (December 2021)

Volumen 27 (2021): Edición 3 (September 2021)

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Detalles de la revista
Formato
Revista
eISSN
1898-0309
Publicado por primera vez
30 Dec 2008
Periodo de publicación
4 veces al año
Idiomas
Inglés

Buscar

Volumen 28 (2022): Edición 3 (September 2022)

Detalles de la revista
Formato
Revista
eISSN
1898-0309
Publicado por primera vez
30 Dec 2008
Periodo de publicación
4 veces al año
Idiomas
Inglés

Buscar

4 Artículos
Acceso abierto

Application of therapeutic linear accelerators for the production of radioisotopes used in nuclear medicine

Publicado en línea: 28 Jul 2022
Páginas: 107 - 116

Resumen

Abstract

This review paper summarizes the possibilities of the use of therapeutic linear electron accelerators for the production of radioisotopes for nuclear medicine. This work is based on our published results and the thematically similar papers by other authors, directly related to five medical radioisotopes as 99Mo/99mTc, 198Au, 186Re, 188Re, 117mSn, produced using therapeutic linacs. Our unpublished data relating to the issues discussed have also been used here. In the experiments, two types of radiation were included in the analysis of the radioisotope production process, i.e. the therapeutic twenty-megavolt (20 MV) X-rays generated by Varian linacs and neutron radiation contaminating the therapeutic beam. Thus, the debated radioisotopes are produced in the photonuclear reactions and in the neutron ones. Linear therapeutic accelerators do not allow the production of radioisotopes with high specific activities, but the massive targets can be used instead. Thus, the amount of the produced radioisotopes may be increased. Apart from linear accelerators, more and more often, the production of radioisotopes is carried out in small medical cyclotrons. More such cyclotrons are developed, built, and sold commercially than for scientific research. The radioisotopes produced with the use of therapeutic linacs or cyclotrons can be successfully applied in various laboratory tests and in research.

Palabras clave

  • nuclear medicine
  • radioisotopes
  • therapeutic linacs
Acceso abierto

Automatic diagnosis of severity of COVID-19 patients using an ensemble of transfer learning models with convolutional neural networks in CT images

Publicado en línea: 28 Jul 2022
Páginas: 117 - 126

Resumen

Abstract

Introduction: Quantification of lung involvement in COVID-19 using chest Computed tomography (CT) scan can help physicians to evaluate the progression of the disease or treatment response. This paper presents an automatic deep transfer learning ensemble based on pre-trained convolutional neural networks (CNNs) to determine the severity of COVID -19 as normal, mild, moderate, and severe based on the images of the lungs CT.

Material and methods: In this study, two different deep transfer learning strategies were used. In the first procedure, features were extracted from fifteen pre-trained CNNs architectures and then fed into a support vector machine (SVM) classifier. In the second procedure, the pre-trained CNNs were fine-tuned using the chest CT images, and then features were extracted for the purpose of classification by the softmax layer. Finally, an ensemble method was developed based on majority voting of the deep learning outputs to increase the performance of the recognition on each of the two strategies. A dataset of CT scans was collected and then labeled as normal (314), mild (262), moderate (72), and severe (35) for COVID-19 by the consensus of two highly qualified radiologists.

Results: The ensemble of five deep transfer learning outputs named EfficientNetB3, EfficientNetB4, InceptionV3, NasNetMobile, and ResNext50 in the second strategy has better results than the first strategy and also the individual deep transfer learning models in diagnosing the severity of COVID-19 with 85% accuracy.

Conclusions: Our proposed study is well suited for quantifying lung involvement of COVID-19 and can help physicians to monitor the progression of the disease.

Palabras clave

  • severity of COVID-19
  • convolutional neural network
  • ensemble
Acceso abierto

Evaluation of the polarity effect of Roos parallel plate ionization chamber in build-up region

Publicado en línea: 23 Aug 2022
Páginas: 127 - 132

Resumen

Abstract

Purpose: Despite widespread studying of the polarity effect of Roos parallel plate ion chamber in electron beams as mentioned in several protocols, no investigations have up till now studied this effect in photon beams in the build-up region. It is important to examine its polarity effect in the build-up region for photon beams, so this is the first work that focuses in to evaluate the polarity effect of the Roos chamber in the surface and build-up region and comparing its effect with other chambers.

Methods: In this study, the Roos chamber was irradiated by a Theratron 780E 60Co beam to a known polarity effect. The Polarity effects of 5×5 up to 35×35 cm2 field sizes at positive and negative polarizing voltages were measured in the build-up region from surface to 0.7 cm in a solid water phantom.

Results: The polarity ratios (PRs) were obtained at 1.020 ± 0.00 and 1.015 ± 0.00 for field sizes 5 × 5 up to 35 × 35 cm2, respectively. For the same fields, the percentage of polarity effects (%PEs) was obtained at 1.99% ± 0.00% and 1.47% ± 0.02%, respectively. The results found that the %PEs decrease with increased field sizes and depths. Moreover, the %PEs exhibited a decrease with an increased percentage surface dose (%SD). The uncertainty of %PE was estimated as 0.01% for all measurements in this study.

Conclusions: As a result, the average %PE of the Roos chamber described here is equal to 0.756% ± 0.013% for all depths and field sizes for the 60Co γ-ray beam. It has introduced a less percentage of polarity effect than other chambers.

Palabras clave

  • Roos chamber
  • polarity effect
  • build-up region
  • cobalt Co
Acceso abierto

Automation of slice thickness measurements in computed tomography images of AAPM CT performance phantom using a non-rotational method

Publicado en línea: 23 Aug 2022
Páginas: 133 - 138

Resumen

Abstract

Purpose: The current study proposes a method for automatically measuring slice thickness using a non-rotational method on the middle stair object of the AAPM CT performance phantom image.

Method: The AAPM CT performance phantom was scanned by a GE Healthcare 128-slice CT scanner with nominal slice thicknesses of 0.625, 1.25, 2.5, 3.75, 5, 7.5 and 10 mm. The automated slice thickness was measured as the full width at half maximum (FWHM) of the profile of the middle stair object using a non-rotational method. The non-rotational method avoided rotating the image of the phantom. Instead, the lines to make the profiles were automatically rotated to confirm the stair’s location and rotation. The results of this non-rotational method were compared with those from a previous rotational method.

Results: The slice thicknesses from the non-rotational method were 1.55, 1.86, 3.27, 4.86, 6.58, 7.57, and 9.66 mm for nominal slice thicknesses of 0.625, 1.25, 2.4, 3.75, 5, 7.5, and 10 mm, respectively. By comparison, the slice thicknesses from the rotational method were 1.53, 1.87, 3.32, 4.98, 6.77, 7.75, and 9.80 mm, respectively. The results of the nonrotational method were slightly lower (i.e. 0.25%) than the results of the rotational method for each nominal slice thickness, except for the smallest slice thickness.

Conclusions: An alternative algorithm using a non-rotational method to measure the slice thickness of the middle stair object in the AAPM CT performance phantom was successfully implemented. The slice thicknesses from the nonrotational method results were slightly lower than the rotational method results for each nominal slice thickness, except at the smallest nominal slice thickness (0.625 mm).

Palabras clave

  • computed tomography
  • slice thickness
  • non-rotation method
  • AAPM CT performance phantom
4 Artículos
Acceso abierto

Application of therapeutic linear accelerators for the production of radioisotopes used in nuclear medicine

Publicado en línea: 28 Jul 2022
Páginas: 107 - 116

Resumen

Abstract

This review paper summarizes the possibilities of the use of therapeutic linear electron accelerators for the production of radioisotopes for nuclear medicine. This work is based on our published results and the thematically similar papers by other authors, directly related to five medical radioisotopes as 99Mo/99mTc, 198Au, 186Re, 188Re, 117mSn, produced using therapeutic linacs. Our unpublished data relating to the issues discussed have also been used here. In the experiments, two types of radiation were included in the analysis of the radioisotope production process, i.e. the therapeutic twenty-megavolt (20 MV) X-rays generated by Varian linacs and neutron radiation contaminating the therapeutic beam. Thus, the debated radioisotopes are produced in the photonuclear reactions and in the neutron ones. Linear therapeutic accelerators do not allow the production of radioisotopes with high specific activities, but the massive targets can be used instead. Thus, the amount of the produced radioisotopes may be increased. Apart from linear accelerators, more and more often, the production of radioisotopes is carried out in small medical cyclotrons. More such cyclotrons are developed, built, and sold commercially than for scientific research. The radioisotopes produced with the use of therapeutic linacs or cyclotrons can be successfully applied in various laboratory tests and in research.

Palabras clave

  • nuclear medicine
  • radioisotopes
  • therapeutic linacs
Acceso abierto

Automatic diagnosis of severity of COVID-19 patients using an ensemble of transfer learning models with convolutional neural networks in CT images

Publicado en línea: 28 Jul 2022
Páginas: 117 - 126

Resumen

Abstract

Introduction: Quantification of lung involvement in COVID-19 using chest Computed tomography (CT) scan can help physicians to evaluate the progression of the disease or treatment response. This paper presents an automatic deep transfer learning ensemble based on pre-trained convolutional neural networks (CNNs) to determine the severity of COVID -19 as normal, mild, moderate, and severe based on the images of the lungs CT.

Material and methods: In this study, two different deep transfer learning strategies were used. In the first procedure, features were extracted from fifteen pre-trained CNNs architectures and then fed into a support vector machine (SVM) classifier. In the second procedure, the pre-trained CNNs were fine-tuned using the chest CT images, and then features were extracted for the purpose of classification by the softmax layer. Finally, an ensemble method was developed based on majority voting of the deep learning outputs to increase the performance of the recognition on each of the two strategies. A dataset of CT scans was collected and then labeled as normal (314), mild (262), moderate (72), and severe (35) for COVID-19 by the consensus of two highly qualified radiologists.

Results: The ensemble of five deep transfer learning outputs named EfficientNetB3, EfficientNetB4, InceptionV3, NasNetMobile, and ResNext50 in the second strategy has better results than the first strategy and also the individual deep transfer learning models in diagnosing the severity of COVID-19 with 85% accuracy.

Conclusions: Our proposed study is well suited for quantifying lung involvement of COVID-19 and can help physicians to monitor the progression of the disease.

Palabras clave

  • severity of COVID-19
  • convolutional neural network
  • ensemble
Acceso abierto

Evaluation of the polarity effect of Roos parallel plate ionization chamber in build-up region

Publicado en línea: 23 Aug 2022
Páginas: 127 - 132

Resumen

Abstract

Purpose: Despite widespread studying of the polarity effect of Roos parallel plate ion chamber in electron beams as mentioned in several protocols, no investigations have up till now studied this effect in photon beams in the build-up region. It is important to examine its polarity effect in the build-up region for photon beams, so this is the first work that focuses in to evaluate the polarity effect of the Roos chamber in the surface and build-up region and comparing its effect with other chambers.

Methods: In this study, the Roos chamber was irradiated by a Theratron 780E 60Co beam to a known polarity effect. The Polarity effects of 5×5 up to 35×35 cm2 field sizes at positive and negative polarizing voltages were measured in the build-up region from surface to 0.7 cm in a solid water phantom.

Results: The polarity ratios (PRs) were obtained at 1.020 ± 0.00 and 1.015 ± 0.00 for field sizes 5 × 5 up to 35 × 35 cm2, respectively. For the same fields, the percentage of polarity effects (%PEs) was obtained at 1.99% ± 0.00% and 1.47% ± 0.02%, respectively. The results found that the %PEs decrease with increased field sizes and depths. Moreover, the %PEs exhibited a decrease with an increased percentage surface dose (%SD). The uncertainty of %PE was estimated as 0.01% for all measurements in this study.

Conclusions: As a result, the average %PE of the Roos chamber described here is equal to 0.756% ± 0.013% for all depths and field sizes for the 60Co γ-ray beam. It has introduced a less percentage of polarity effect than other chambers.

Palabras clave

  • Roos chamber
  • polarity effect
  • build-up region
  • cobalt Co
Acceso abierto

Automation of slice thickness measurements in computed tomography images of AAPM CT performance phantom using a non-rotational method

Publicado en línea: 23 Aug 2022
Páginas: 133 - 138

Resumen

Abstract

Purpose: The current study proposes a method for automatically measuring slice thickness using a non-rotational method on the middle stair object of the AAPM CT performance phantom image.

Method: The AAPM CT performance phantom was scanned by a GE Healthcare 128-slice CT scanner with nominal slice thicknesses of 0.625, 1.25, 2.5, 3.75, 5, 7.5 and 10 mm. The automated slice thickness was measured as the full width at half maximum (FWHM) of the profile of the middle stair object using a non-rotational method. The non-rotational method avoided rotating the image of the phantom. Instead, the lines to make the profiles were automatically rotated to confirm the stair’s location and rotation. The results of this non-rotational method were compared with those from a previous rotational method.

Results: The slice thicknesses from the non-rotational method were 1.55, 1.86, 3.27, 4.86, 6.58, 7.57, and 9.66 mm for nominal slice thicknesses of 0.625, 1.25, 2.4, 3.75, 5, 7.5, and 10 mm, respectively. By comparison, the slice thicknesses from the rotational method were 1.53, 1.87, 3.32, 4.98, 6.77, 7.75, and 9.80 mm, respectively. The results of the nonrotational method were slightly lower (i.e. 0.25%) than the results of the rotational method for each nominal slice thickness, except for the smallest slice thickness.

Conclusions: An alternative algorithm using a non-rotational method to measure the slice thickness of the middle stair object in the AAPM CT performance phantom was successfully implemented. The slice thicknesses from the nonrotational method results were slightly lower than the rotational method results for each nominal slice thickness, except at the smallest nominal slice thickness (0.625 mm).

Palabras clave

  • computed tomography
  • slice thickness
  • non-rotation method
  • AAPM CT performance phantom

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