Through the reworking of a software created for monitoring the earth's crust, researchers have come to develop a type capable of reprocessing the images of radiographs into CT images.
The development of research and high technologies carried out by INGV also finds application in many other branches of scientific research. It is the case of the study “Pipeline for Advanced Contrast Enhancement (PACE) of Chest X-ray in Evaluating COVID-19 Patients by Combining Bidimensional Empirical Mode Decomposition and Contrast Limited Adaptive Histogram Equalization (CLAHE)” recently published in the MDPI 'Sustainability' magazine, conducted in collaboration with the University of Messina and the University of Catania, for the development of a software application called “PACE” produced to offer a very important support to radiologists in the diagnosis and treatment of serious lung diseases such as those caused by COVID-19.
In fact, the diagnostic imaging applied to patients suffering from lung pathologies has come to the aid of the one normally used by INGV to characterize the "state of health" of the earth's crust.
"The analogy between the interior of the Earth and the interior of the lungs may appear quite bold." says Massimo Chiappini, INGV researcher and co-author of the initiative. "However, this research was born from the intuition of using the same image treatment techniques on medical images that we normally use for the representation of the subsoil in areas subject to seismic, volcanic or environmental risk".
In fact, it is known that for patients suffering from serious lung diseases such as COVID-19 in recent times, the radiological evaluation of lung lesions is essential both for monitoring the evolution of the disease and for evaluating the response to specific therapies. However, this activity is complicated by the fact that patients, especially in the acute phases of the disease, are not cooperative and/or are in intensive care. Furthermore, in these situations, radiograms are often performed with portable radiographic instruments which often produce artifact images which reduce their readability.
Therefore, the PACE software, developed by the multidisciplinary team of researchers from INGV, University of Messina (led by Prof. Giovanni Finocchio of the Department of Mathematical and Computer Sciences, Physical Sciences and Earth Sciences (MIFT) and by Prof. Giuseppe Cicero of the Department of Biomedical, Dental and Morphological and Functional Imaging Sciences) and of the University of Catania (led by Prof. Giulio Siracusano and Aurelio La Corte), was designed to solve these graphic representation problems by maximizing the contrast of chest radiographic images.
To date, given the urgency, the doctors have applied it to the images collected on the COVID-19 patients of the "G. Martino” of Messina: with PACE the reading of the radiogram by the radiologist has significantly improved. The algorithm, in fact, combines the state of the art of numerical image processing applications, such as two-dimensional empirical decomposition, homomorphic filtering and histogram adaptive equalization in a suitable way.
“Clinically” - says the prof. Gaeta of the Department of Biomedical, Dental and Morphological and Functional Imaging Sciences of the University of Messina, "it was essential to verify that the additional information produced by PACE was real. To do this, chest X-rays and traditional CT scans were jointly performed and compared: the great success was to verify that the additional lesions that the PACE software detected in the simple radiographic images were all confirmed by the CT scans".
“The impact of the software created by INGV and the Sicilian Universities is very relevant in the social sphere” says Massimo Chiappini. “Among the advantages, in fact, in addition to the evident reduction in costs and times deriving from the non-essentiality of CT machinery to obtain identical useful diagnostic results, with the use of PACE it is sufficient to carry out a single operation on the patient for the radiographic examination with a lower risk of spreading viral diseases even among healthcare workers as in the case of COVID-19. Furthermore, this technology offers the possibility of applying it even in extreme conditions where access to CT diagnostics is not easy due both to the high number of patients involved and to the costs of the machine itself and, in economically underdeveloped areas, such as Africa and South America, represents a prohibitive instrumentation”.
Given the high level of interest in the medical field, all research results have been freely made available to the scientific community.
link:
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From the monitoring of seismic and volcanic territories to medical therapies PACE: the software that replaces the CT scan, is born
Through the reworking of a software created for monitoring the earth's crust, the researchers have come to develop a type capable of reworking the images of the radiographs into CT images.
The development of research and high technologies carried out by INGV also finds application in many other branches of scientific research. This is the case of the study"Pipeline for Advanced Contrast Enhancement (PACE) of Chest X-ray in Evaluating COVID-19 Patients by Combining Bidimensional Empirical Mode Decomposition and Contrast Limited Adaptive Histogram Equalization (CLAHE)" recently published in the MDPI 'Sustainability' journal. The study was conducted in collaboration with the University of Messina and the University of Catania, for the development of a software application called "PACE" produced to offer extremely important support to radiologists in the diagnosis and treatment of severe lung diseases such as those caused by COVID-19.
In fact, the diagnostic imaging normally used by INGV to characterize the “state of health” of the earth's crust has come to the aid of diagnostic imaging applied to patients suffering from pulmonary diseases.
“The analogy between the interior of the Earth and the interior of the lungs can appear quite bold", says Massimo Chiappini, researcher at INGV and co-author of the initiative. "However, this research arises precisely from the intuition of using the same image processing techniques on medical images that we normally use for the representation of the subsoil in areas subject to seismic, volcanic or environmental risk”.
In fact, it is known that for patients suffering from serious lung diseases such as, in recent times, COVID-19, the radiological evaluation of lung lesions is essential both for monitoring the evolution of the disease and for assessing the response to specific therapies. However, this activity is made complex by the fact that patients, especially in the acute phases of the disease, are not cooperative and/or are in intensive care. Furthermore, in such situations, radiograms are often performed with portable radiographic instruments which often produce artificial images that reduce their readability.
Therefore, the PACE software, developed by the multidisciplinary team of researchers from INGV, of the University of Messina (led by Prof. Giovanni Finocchio of the Department of Mathematical and Computer Sciences, Physical Sciences and Earth Sciences (MIFT) and by Prof. Giuseppe Cicero of the Department of Biomedical, Dental and Morphological and Functional Imaging Sciences) and of the University of Catania (led by Profs Giulio Siracusano and Aurelio La Corte), was designed to solve these graphical representation problems by maximizing the contrast of chest radiographic images.
To date, given the urgency, doctors have applied it to the images collected on COVID-19 patients at the University Hospital “G. Martino” in Messina: with PACE, the radiologist's reading of the radiogram significantly improved. The algorithm, in fact, combines the state of the art of numerical image processing applications, such as the two-dimensional empirical decomposition, the homomorphic filter and the adaptive equalization of the histogram in an appropriate way.
“From a clinical point of view” - says prof. Gaeta of the Department of Biomedical, Dental and Morphological and Functional Imaging Sciences of the University of Messina, “it was essential to verify that the additional information produced by PACE was real. To do this, chest radiographs and conventional CT scans were taken and compared jointly: the great success was to verify that the additional lesions that the PACE software detected in the simple radiographic images were all confirmed by the CT scans”.
"The fallout of the software designed by INGV and the Sicilian Universities is very relevant in the social sphere”, says Massimo Chiappini. “Among the advantages, in fact, in addition to the evident reduction in costs and time deriving from the non-espensability of CT machines to have identical useful diagnostic results, with the use of PACE it is sufficient to carry out a single intervention on the patient for the examination radiographic with a lower risk of spreading viral diseases even among health professionals as in the case of COVID-19. Furthermore, this technology offers the possibility of applying it even in extreme conditions where access to CT diagnostics is not easy both due to the high number of patients involved and the costs of the machine itself and, in economically underdeveloped areas, such as Africa and South America represent a prohibitive instrumentation”.
Given the high interest found in the medical field, all research results have been freely made available to the scientific community.
link:
picture 1 - The figure shows an example of the application of PACE, through the comparison between the following images: (a) traditional radiography, (b) image obtained with CT and (c) radiographic image processed with PACE. Thanks to an improvement in the contrasts, it is possible to recognize how processing with PACE highlights a number of lung lesions, indicated with the black arrow, not present in traditional radiography. The magnifications (d, e, f) make the comparison and the power of the method even more visible, confirmed by the CT images.
Picture #1 - The figure shows an example of the application of PACE, by comparing the following images: (a) traditional radiography, (b) image obtained with CT and (c) radiographic image processed with PACE. Thanks to an improvement in contrasts, it is possible to recognize how the processing with PACE highlights a number of lung lesions, indicated by the black arrow, not present in traditional radiography. The magnifications (d, e, f) make the comparison and the power of the method, confirmed by the CT images, even more visible