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1.
J Pers Med ; 12(4)2022 Apr 12.
Article in English | MEDLINE | ID: covidwho-1785791

ABSTRACT

Due to the increasing number of COVID-19-infected and vaccinated individuals, radiologists continue to see patients with COVID-19 pneumonitis and recall pneumonitis, which could result in additional workups and false-positive results. Moreover, cancer patients undergoing immunotherapy may show therapy-related pneumonitis during imaging management. This is otherwise known as immune checkpoint inhibitor-related pneumonitis. Following on from this background, radiologists should seek to know their patients' COVID-19 infection and vaccination history. Knowing the imaging features related to COVID-19 infection and vaccination is critical to avoiding misleading results and alarmism in patients and clinicians.

2.
Infect Agent Cancer ; 17(1): 8, 2022 Mar 17.
Article in English | MEDLINE | ID: covidwho-1745435

ABSTRACT

BACKGROUND: To date, no paper reports cases of lymphangitis after COVID 19 vaccination. We present a case of lymphangitis after vaccination from COVID 19, in a patient with colorectal liver metastases. METHODS: We described the case of a 56-year-old woman with history of a surgical resection of colorectal cancer and liver metastases, without any kind of drug therapy for about a month. In addition, a recent administration (2 days ago) of Spikevax (mRNA-1273, Moderna vaccine), as a booster dose, on the right arm was reported. RESULTS: The magnetic resonance (MR) examination showed the effects of the previous surgical resection and five new hepatic metastases, located in the VIII, VI, V, IV and II hepatic segments. As an accessory finding the presence of lymphadenopathy in the axillary area and lymphangitis of the right breast and chest were identified. The computed tomography scan performed a week earlier, and re-evaluated in light of the MR data, did not identify the presence of lymphadenopathy in the axillary area and lymphangitis signs. CONCLUSIONS: Lymphangitis could occur after COVID 19 vaccine and it is important to know this data to avoid alarmism in patients and clinicians and economic waste linked to the execution of various radiological investigations for the search for a tumour that probably does not exist. TRIAL REGISTRATION: Not applicable.

3.
Radiol Med ; 127(4): 369-382, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1739408

ABSTRACT

During the coronavirus disease 19 (COVID-19) pandemic, extracorporeal membrane oxygenation (ECMO) has been proposed as a possible therapy for COVID-19 patients with acute respiratory distress syndrome. This pictorial review is intended to provide radiologists with up-to-date information regarding different types of ECMO devices, correct placement of ECMO cannulae, and imaging features of potential complications and disease evolution in COVID-19 patients treated with ECMO, which is essential for a correct interpretation of diagnostic imaging, so as to guide proper patient management.


Subject(s)
COVID-19 , Extracorporeal Membrane Oxygenation , Respiratory Distress Syndrome , Extracorporeal Membrane Oxygenation/methods , Humans , Radiologists , Respiratory Distress Syndrome/diagnostic imaging , Respiratory Distress Syndrome/etiology , Respiratory Distress Syndrome/therapy , SARS-CoV-2
4.
J Pers Med ; 11(11)2021 Oct 28.
Article in English | MEDLINE | ID: covidwho-1488657

ABSTRACT

OBJECTIVE: To investigate two commercial software and their efficacy in the assessment of chest CT sequelae in patients affected by COVID-19 pneumonia, comparing the consistency of tools. MATERIALS AND METHODS: Included in the study group were 120 COVID-19 patients (56 women and 104 men; 61 years of median age; range: 21-93 years) who underwent chest CT examinations at discharge between 5 March 2020 and 15 March 2021 and again at a follow-up time (3 months; range 30-237 days). A qualitative assessment by expert radiologists in the infectious disease field (experience of at least 5 years) was performed, and a quantitative evaluation using thoracic VCAR software (GE Healthcare, Chicago, Illinois, United States) and a pneumonia module of ANKE ASG-340 CT workstation (HTS Med & Anke, Naples, Italy) was performed. The qualitative evaluation included the presence of ground glass opacities (GGOs) consolidation, interlobular septal thickening, fibrotic-like changes (reticular pattern and/or honeycombing), bronchiectasis, air bronchogram, bronchial wall thickening, pulmonary nodules surrounded by GGOs, pleural and pericardial effusion, lymphadenopathy, and emphysema. A quantitative evaluation included the measurements of GGOs, consolidations, emphysema, residual healthy parenchyma, and total lung volumes for the right and left lung. A chi-square test and non-parametric test were utilized to verify the differences between groups. Correlation coefficients were used to analyze the correlation and variability among quantitative measurements by different computer tools. A receiver operating characteristic (ROC) analysis was performed. RESULTS: The correlation coefficients showed great variability among the quantitative measurements by different tools when calculated on baseline CT scans and considering all patients. Instead, a good correlation (≥0.6) was obtained for the quantitative GGO, as well as the consolidation volumes obtained by two tools when calculated on baseline CT scans, considering the control group. An excellent correlation (≥0.75) was obtained for the quantitative residual healthy lung parenchyma volume, GGO, consolidation volumes obtained by two tools when calculated on follow-up CT scans, and for residual healthy lung parenchyma and GGO quantification when the percentage change of these volumes were calculated between a baseline and follow-up scan. The highest value of accuracy to identify patients with RT-PCR positive compared to the control group was obtained by a GGO total volume quantification by thoracic VCAR (accuracy = 0.75). CONCLUSIONS: Computer aided quantification could be an easy and feasible way to assess chest CT sequelae due to COVID-19 pneumonia; however, a great variability among measurements provided by different tools should be considered.

5.
J Pers Med ; 11(10)2021 Sep 30.
Article in English | MEDLINE | ID: covidwho-1444254

ABSTRACT

OBJECTIVE: To report an overview and update on Artificial Intelligence (AI) and COVID-19 using chest Computed Tomography (CT) scan and chest X-ray images (CXR). Machine Learning and Deep Learning Approaches for Diagnosis and Treatment were identified. METHODS: Several electronic datasets were analyzed. The search covered the years from January 2019 to June 2021. The inclusion criteria were studied evaluating the use of AI methods in COVID-19 disease reporting performance results in terms of accuracy or precision or area under Receiver Operating Characteristic (ROC) curve (AUC). RESULTS: Twenty-two studies met the inclusion criteria: 13 papers were based on AI in CXR and 10 based on AI in CT. The summarized mean value of the accuracy and precision of CXR in COVID-19 disease were 93.7% ± 10.0% of standard deviation (range 68.4-99.9%) and 95.7% ± 7.1% of standard deviation (range 83.0-100.0%), respectively. The summarized mean value of the accuracy and specificity of CT in COVID-19 disease were 89.1% ± 7.3% of standard deviation (range 78.0-99.9%) and 94.5 ± 6.4% of standard deviation (range 86.0-100.0%), respectively. No statistically significant difference in summarized accuracy mean value between CXR and CT was observed using the Chi square test (p value > 0.05). CONCLUSIONS: Summarized accuracy of the selected papers is high but there was an important variability; however, less in CT studies compared to CXR studies. Nonetheless, AI approaches could be used in the identification of disease clusters, monitoring of cases, prediction of the future outbreaks, mortality risk, COVID-19 diagnosis, and disease management.

6.
J Pers Med ; 11(7)2021 Jul 06.
Article in English | MEDLINE | ID: covidwho-1302361

ABSTRACT

PURPOSE: the purpose of this study was to assess the evolution of computed tomography (CT) findings and lung residue in patients with COVID-19 pneumonia, via quantified evaluation of the disease, using a computer aided tool. MATERIALS AND METHODS: we retrospectively evaluated 341 CT examinations of 140 patients (68 years of median age) infected with COVID-19 (confirmed by real-time reverse transcriptase polymerase chain reaction (RT-PCR)), who were hospitalized, and who received clinical and CT examinations. All CTs were evaluated by two expert radiologists, in consensus, at the same reading session, using a computer-aided tool for quantification of the pulmonary disease. The parameters obtained using the computer tool included the healthy residual parenchyma, ground glass opacity, consolidation, and total lung volume. RESULTS: statistically significant differences (p value ≤ 0.05) were found among quantified volumes of healthy residual parenchyma, ground glass opacity (GGO), consolidation, and total lung volume, considering different clinical conditions (stable, improved, and worsened). Statistically significant differences were found among quantified volumes for healthy residual parenchyma, GGO, and consolidation (p value ≤ 0.05) between dead patients and discharged patients. CT was not performed on cadavers; the death was an outcome, which was retrospectively included to differentiate findings of patients who survived vs. patients who died during hospitalization. Among discharged patients, complete disease resolutions on CT scans were observed in 62/129 patients with lung disease involvement ≤5%; lung disease involvement from 5% to 15% was found in 40/129 patients, while 27/129 patients had lung disease involvement between 16 and 30%. Moreover, 8-21 days (after hospital admission) was an "advanced period" with the most severe lung disease involvement. After the extent of involvement started to decrease-particularly after 21 days-the absorption was more obvious. CONCLUSIONS: a complete disease resolution on chest CT scans was observed in 48.1% of discharged patients using a computer-aided tool to quantify the GGO and consolidation volumes; after 16 days of hospital admission, the abnormalities identified by chest CT began to improve; in particular, the absorption was more obvious after 21 days.

7.
Int J Environ Res Public Health ; 18(12)2021 06 14.
Article in English | MEDLINE | ID: covidwho-1270052

ABSTRACT

The infection caused by novel beta-coronavirus (SARS-CoV-2) was officially declared a pandemic by the World Health Organization in March 2020. However, in the last 20 years, this has not been the only viral infection to cause respiratory tract infections leading to hundreds of thousands of deaths worldwide, referring in particular to severe acute respiratory syndrome (SARS), influenza H1N1 and Middle East respiratory syndrome (MERS). Although in this pandemic period SARS-CoV-2 infection should be the first diagnosis to exclude, many other viruses can cause pulmonary manifestations and have to be recognized. Through the description of the main radiological patterns, radiologists can suggest the diagnosis of viral pneumonia, also combining information from clinical and laboratory data.


Subject(s)
COVID-19 , Influenza A Virus, H1N1 Subtype , Influenza, Human , Middle East Respiratory Syndrome Coronavirus , Pneumonia, Viral , Humans , SARS-CoV-2
8.
J Pers Med ; 11(5)2021 May 06.
Article in English | MEDLINE | ID: covidwho-1224054

ABSTRACT

BACKGROUND: During the COVID-19 public health emergency, our breast cancer screening activities have been interrupted. In June 2020, they resumed, calling for mandatory safe procedures to properly manage patients and staff. METHODS: A protocol supporting medical activities in breast cancer screening was created, based on six relevant articles published in the literature and in the following National and International guidelines for COVID-19 prevention. The patient population, consisting of both screening and breast ambulatory patients, was classified into one of four categories: 1. Non-COVID-19 patient; 2. Confirmed COVID-19 in an asymptomatic screening patient; 3. suspected COVID-19 in symptomatic or confirmed breast cancer; 4. Confirmed COVID-19 in symptomatic or confirmed breast cancer. The day before the radiological exam, patients are screened for COVID-19 infection through a telephone questionnaire. At a subsequent in person appointment, the body temperature is checked and depending on the clinical scenario at stake, the scenario-specific procedures for medical and paramedical staff are adopted. RESULTS: In total, 203 mammograms, 76 breast ultrasound exams, 4 core needle biopsies, and 6 vacuum-assisted breast biopsies were performed in one month. Neither medical nor paramedical staff were infected on any of these occasions. CONCLUSION: Our department organization model can represent a case of implementation of National and International guidelines applied in a breast cancer screening program, assisting hospital personnel into COVID-19 infection prevention.

9.
J Pers Med ; 11(4)2021 Apr 08.
Article in English | MEDLINE | ID: covidwho-1178321

ABSTRACT

Globally, at the time of writing (20 March 2021), 121.759.109 confirmed COVID-19 cases have been reported to the WHO, including 2.690.731 deaths. Globally, on 18 March 2021, a total of 364.184.603 vaccine doses have been administered. In Italy, 3.306.711 confirmed COVID-19 cases with 103.855 deaths have been reported to WHO. In Italy, on 9 March 2021, a total of 6.634.450 vaccine doses have been administered. On 15 March 2021, Italian Medicines Agency (AIFA) decided to temporarily suspend the use of the AstraZeneca COVID-19 vaccine throughout the country as a precaution, pending the rulings of the European Medicines Agency (EMA). This decision was taken in line with similar measures adopted by other European countries due to the death of vaccinated people. On 18 March 2021, EMA's safety committee concluded its preliminary review about thromboembolic events in people vaccinated with COVID-19 Vaccine AstraZeneca at its extraordinary meeting, confirming the benefits of the vaccine continue to outweigh the risk of side effects, however, the vaccine may be associated with very rare cases of blood clots associated with thrombocytopenia, i.e., low levels of blood platelets with or without bleeding, including rare cases of cerebral venous thrombosis (CVT). We report the case of a 54-year-old woman who developed disseminated intravascular coagulation (DIC) with multi-district thrombosis 12 days after the AstraZeneca COVID-19 vaccine administration. A brain computed tomography (CT) scan showed multiple subacute intra-axial hemorrhages in atypical locations, including the right frontal and the temporal lobes. A plain old balloon angioplasty (POBA) of the right coronary artery was performed, without stent implantation, with restoration of distal flow, but with persistence of extensive thrombosis of the vessel. A successive thorax angio-CT added the findings of multiple contrast filling defects with multi-vessel involvement: at the level of the left upper lobe segmental branches, of left interlobar artery, of the right middle lobe segmental branches and of the right interlobar artery. A brain magnetic resonance imaging (MRI) in the same day showed the presence of an acute basilar thrombosis associated with the superior sagittal sinus thrombosis. An abdomen angio-CT showed filling defects at the level of left portal branch and at the level of right suprahepatic vein. Bilaterally, it was adrenal hemorrhage and blood in the pelvis. An evaluation of coagulation factors did not show genetic alterations so as the nasopharyngeal swab ruled out a COVID-19 infection. The patient died after 5 days of hospitalization in intensive care.

11.
Biology (Basel) ; 10(3)2021 Mar 11.
Article in English | MEDLINE | ID: covidwho-1125047

ABSTRACT

During a spontaneous and autonomous study, we assessed the ultrasound finding of lymphadenopathy after BNT162b2 Pfizer vaccine. We enrolled 18 patients with 58 lymphadenopathies: in 10 patients, they were in the laterocervical side, while in 8 patients in the axillar site. The largest diameter was 16 mm with a range from 7 to 16 mm (median value = 10 mm). In the same patient, we found different ultrasound nodal findings. A total of 25 nodes showed eccentric cortical thickening with wide echogenic hilum and oval shape. In total, 19 nodes showed asymmetric eccentric cortical thickening with wide echogenic hilum and oval shape. Overall, 10 nodes showed concentric cortical thickening with reduction in the width of the echogenic hilum and oval shape. A total of four nodes showed huge reduction and displacement of the echogenic hilum and round or oval shape. No anomaly was found at the Doppler echocolor study. In conclusion, eccentric cortical thickening with wide echogenic hilum and oval shape, asymmetric eccentric cortical thickening with wide echogenic hilum and oval shape, concentric cortical thickening with reduction in the width of the echogenic hilum and oval shape, and a huge reduction and displacement of the echogenic hilum and round shape are the features that we found in post BNT162b2 Covid-19 Vaccine lymphadenopathies.

12.
Radiol Oncol ; 55(2): 121-129, 2021 03 05.
Article in English | MEDLINE | ID: covidwho-1119525

ABSTRACT

BACKGROUND: COVID-19 infection is particularly aggressive in frail patients, as cancer patients. Therefore, the more suitable management of the oncological patient requires a multidisciplinary assessment, to identify which patients should be treated, as inpatients or outpatients, and which treatments can be procrastinated. CONCLUSIONS: The role of radiologist is crucial, and, all cancer patients who need an imaging evaluation will need to be studied, using the most appropriate imaging tools related to the clinical question and paying a special attention to preserve public health. Guidelines are necessary in the correct organization of a radiology unit to manage patients with suspected or confirmed COVID-19 infection, and whenever possible, a satellite radiography center with dedicated equipment should be used to decrease the transmission risk.


Subject(s)
COVID-19/complications , COVID-19/diagnosis , Clinical Protocols , Neoplasms/complications , Neoplasms/diagnosis , Radiology Department, Hospital/organization & administration , COVID-19/therapy , COVID-19/transmission , COVID-19 Testing , Cross Infection/prevention & control , Humans , Incidental Findings , Neoplasms/therapy , Patient Care Team/organization & administration , Patient Isolation , Personal Protective Equipment , SARS-CoV-2 , Triage
14.
Biology (Basel) ; 10(2)2021 Jan 25.
Article in English | MEDLINE | ID: covidwho-1045466

ABSTRACT

To assess the performance of the second reading of chest compute tomography (CT) examinations by expert radiologists in patients with discordance between the reverse transcription real-time fluorescence polymerase chain reaction (RT-PCR) test for COVID-19 viral pneumonia and the CT report. Three hundred and seventy-eight patients were included in this retrospective study (121 women and 257 men; 71 years median age, with a range of 29-93 years) and subjected to RT-PCR tests for suspicious COVID-19 infection. All patients were subjected to CT examination in order to evaluate the pulmonary disease involvement by COVID-19. CT images were reviewed first by two radiologists who identified COVID-19 typical CT patterns and then reanalyzed by another two radiologists using a CT structured report for COVID-19 diagnosis. Weighted к values were used to evaluate the inter-reader agreement. The median temporal window between RT-PCRs execution and CT scan was zero days with a range of (-9,11) days. The RT-PCR test was positive in 328/378 (86.8%). Discordance between RT-PCR and CT findings for viral pneumonia was revealed in 60 cases. The second reading changed the CT diagnosis in 16/60 (26.7%) cases contributing to an increase the concordance with the RT-PCR. Among these 60 cases, eight were false negative with positive RT-PCR, and 36 were false positive with negative RT-PCR. Sensitivity, specificity, positive predictive value and negative predictive value of CT were respectively of 97.3%, 53.8%, 89.0%, and 88.4%. Double reading of CT scans and expert second readers could increase the diagnostic confidence of radiological interpretation in COVID-19 patients.

15.
Radiol Med ; 126(4): 553-560, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-932604

ABSTRACT

OBJECTIVE: To calculate by means of a computer-aided tool the volumes of healthy residual lung parenchyma, of emphysema, of ground glass opacity (GGO) and of consolidation on chest computed tomography (CT) in patients with suspected viral pneumonia by COVID-19. MATERIALS AND METHODS: This study included 116 patients that for suspected COVID-19 infection were subjected to the reverse transcription real-time fluorescence polymerase chain reaction (RT-PCR) test. A computer-aided tool was used to calculate on chest CT images healthy residual lung parenchyma, emphysema, GGO and consolidation volumes for both right and left lung. Expert radiologists, in consensus, assessed the CT images using a structured report and attributed a radiological severity score at the disease pulmonary involvement using a scale of five levels. Nonparametric test was performed to assess differences statistically significant among groups. RESULTS: GGO was the most represented feature in suspected CT by COVID-19 infection; it is present in 102/109 (93.6%) patients with a volume percentage value of 19.50% and a median value of 0.64 L, while the emphysema and consolidation volumes were low (0.01 L and 0.03 L, respectively). Among quantified volume, only GGO volume had a difference statistically significant between the group of patients with suspected versus non-suspected CT for COVID-19 (p < < 0.01). There were differences statistically significant among the groups based on radiological severity score in terms of healthy residual parenchyma volume, of GGO volume and of consolidations volume (p < < 0.001). CONCLUSION: We demonstrated that, using a computer-aided tool, the COVID-19 pneumonia was mirrored with a percentage median value of GGO of 19.50% and that only GGO volume had a difference significant between the patients with suspected or non-suspected CT for COVID-19 infection.


Subject(s)
COVID-19/diagnostic imaging , Lung/diagnostic imaging , Pulmonary Emphysema/diagnostic imaging , Radiographic Image Interpretation, Computer-Assisted , Tomography, X-Ray Computed , Adult , Aged , Aged, 80 and over , COVID-19/diagnosis , COVID-19/pathology , COVID-19 Nucleic Acid Testing , Female , Humans , Lung/pathology , Male , Middle Aged , Pulmonary Emphysema/pathology , SARS-CoV-2 , Software
16.
Sci Rep ; 10(1): 17236, 2020 10 14.
Article in English | MEDLINE | ID: covidwho-872725

ABSTRACT

To assess the use of a structured report in the Chest Computed Tomography (CT) reporting of patients with suspicious viral pneumonia by COVID-19 and the evaluation of the main CT patterns. This study included 134 patients (43 women and 91 men; 68.8 years of mean age, range 29-93 years) with suspicious COVID-19 viral infection evaluated by reverse transcription real-time fluorescence polymerase chain reaction (RT-PCR) test. All patients underwent CT examinations at the time of admission. CT images were reviewed by two radiologists who identified COVID-19 CT patterns using a structured reports. Temporal difference mean value between RT-PCRs and CT scan was 0.18 days ± 2.0 days. CT findings were positive for viral pneumonia in 94.0% patients while COVID-19 was diagnosed at RT-PCR in 77.6% patients. Time mean value to complete the structured report by radiologist was 8.5 min ± 2.4 min. The disease on chest CT predominantly affected multiple lobes and the main CT feature was ground glass opacity (GGO) with or without consolidation (96.8%). GGO was predominantly bilateral (89.3%), peripheral (80.3%), multifocal/patching (70.5%). Consolidation disease was predominantly bilateral (83.9%) with prevalent peripheral (87.1%) and segmental (47.3%) distribution. Additional CT signs were the crazy-paving pattern in 75.4% of patients, the septal thickening in 37.3% of patients, the air bronchogram sign in 39.7% and the "reversed halo" sign in 23.8%. Less frequent characteristics at CT regard discrete pulmonary nodules, increased trunk diameter of the pulmonary artery, pleural effusion and pericardium effusion (7.9%, 6.3%, 14.3% and 16.7%, respectively). Barotrauma sign was absent in all the patients. High percentage (54.8%) of the patients had mediastinal lymphadenopathy. Using a Chest CT structured report, with a standardized language, we identified that the cardinal hallmarks of COVID-19 infection were bilateral, peripheral and multifocal/patching GGO and bilateral consolidation with peripheral and segmental distribution.


Subject(s)
Coronavirus Infections/diagnosis , Electronic Health Records , Pneumonia, Viral/diagnosis , Thorax/diagnostic imaging , Tomography, X-Ray Computed , Adult , Aged , Aged, 80 and over , Betacoronavirus/genetics , Betacoronavirus/isolation & purification , COVID-19 , Coronavirus Infections/virology , Female , Humans , Italy , Male , Middle Aged , Pandemics , Pneumonia, Viral/virology , RNA, Viral/metabolism , Real-Time Polymerase Chain Reaction , Retrospective Studies , SARS-CoV-2
17.
International Journal of Environmental Research and Public Health ; 17(18):6914, 2020.
Article | MDPI | ID: covidwho-783872

ABSTRACT

Purpose: To compare different commercial software in the quantification of Pneumonia Lesions in COVID-19 infection and to stratify the patients based on the disease severity using on chest computed tomography (CT) images. Materials and methods: We retrospectively examined 162 patients with confirmed COVID-19 infection by reverse transcriptase-polymerase chain reaction (RT-PCR) test. All cases were evaluated separately by radiologists (visually) and by using three computer software programs: (1) Thoracic VCAR software, GE Healthcare, United States;(2) Myrian, Intrasense, France;(3) InferRead, InferVision Europe, Wiesbaden, Germany. The degree of lesions was visually scored by the radiologist using a score on 5 levels (none, mild, moderate, severe, and critic). The parameters obtained using the computer tools included healthy residual lung parenchyma, ground-glass opacity area, and consolidation volume. Intraclass coefficient (ICC), Spearman correlation analysis, and non-parametric tests were performed. Results: Thoracic VCAR software was not able to perform volumes segmentation in 26/162 (16.0%) cases, Myrian software in 12/162 (7.4%) patients while InferRead software in 61/162 (37.7%) patients. A great variability (ICC ranged for 0.17 to 0.51) was detected among the quantitative measurements of the residual healthy lung parenchyma volume, GGO, and consolidations volumes calculated by different computer tools. The overall radiological severity score was moderately correlated with the residual healthy lung parenchyma volume obtained by ThoracicVCAR or Myrian software, with the GGO area obtained by the ThoracicVCAR tool and with consolidation volume obtained by Myrian software. Quantified volumes by InferRead software had a low correlation with the overall radiological severity score. Conclusions: Computer-aided pneumonia quantification could be an easy and feasible way to stratify COVID-19 cases according to severity;however, a great variability among quantitative measurements provided by computer tools should be considered.

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