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1.
Eur Radiol ; 31(12): 9188-9197, 2021 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-34003348

RESUMEN

OBJECTIVES: Radiation dose index monitoring (RDIM) systems may help identify CT dose reduction opportunities, but variability and complexity of imaging procedures make consistent dose optimization and standardization a challenge. This study aimed to investigate the feasibility to standardize and optimize CT protocols through the implementation of a Dose Excellence Program within a European healthcare network. METHODS: The Dose Excellence Program consisted of a multidisciplinary team that developed standardized organizational adult CT protocols and thresholds for relevant radiation dose indices (RDIs). Baseline data were collected retrospectively from the RDIM (Phase I, 2015). Organization's protocols were implemented and monitored from the RDIM for deviations (Phase II, 2016). Following standardization, radiation dose optimization was initiated (Phase III, 2017). Data from the three most used protocols were retrospectively extracted and grouped by country for all phases. The mean number of series (RS) and RDIs were compared between phases and with organizational reference levels. A Mann-Whitney test was conducted; p < .05 was considered as significant. RESULTS: Data from 9588, 12638, and 6093 examinations were analyzed from General Chest, General Head, and Thorax/Abdomen/Pelvis (TAP) multiphase respectively. Overall, after Phase III, mean RS and CTDIvol p75 were below the organizational reference levels in all countries for the three protocols. The CTDIvol decreased by 45% in Switzerland (p < .00001), 32% in Turkey (p < .00001), and 28% in Switzerland (p = .0027) for General Chest, General Head, and TAP multiphase respectively. CONCLUSIONS: The implementation of a Dose Excellence Program within a large-scale healthcare organization allowed unifying protocols and optimizing radiation dose across countries. KEY POINTS: • Engaging a multidisciplinary team can enhance the use of an RDIM system for CT dose management in a multinational healthcare environment. • Deep dive of baseline data and standardization of CT practices by defining organizational clinical indication CT protocols with RPIDs is an essential step before optimization of radiation dose. • Following the implementation of the program, the mean RS and CTDIvol were below or equal to the organizational reference levels in all countries.


Asunto(s)
Tórax , Tomografía Computarizada por Rayos X , Adulto , Atención a la Salud , Humanos , Dosis de Radiación , Estudios Retrospectivos
2.
Eur Radiol ; 30(7): 3951-3959, 2020 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-32100091

RESUMEN

OBJECTIVES: To assess the impact on image quality and dose reduction of a new deep learning image reconstruction (DLIR) algorithm compared with a hybrid iterative reconstruction (IR) algorithm. METHODS: Data acquisitions were performed at seven dose levels (CTDIvol : 15/10/7.5/5/2.5/1/0.5 mGy) using a standard phantom designed for image quality assessment. Raw data were reconstructed using the filtered back projection (FBP), two levels of IR (ASiR-V50% (AV50); ASiR-V100% (AV100)), and three levels of DLIR (TrueFidelity™ low, medium, high). Noise power spectrum (NPS) and task-based transfer function (TTF) were computed. Detectability index (d') was computed to model a large mass in the liver, a small calcification, and a small subtle lesion with low contrast. RESULTS: NPS peaks were higher with AV50 than with all DLIR levels and only higher with DLIR-H than with AV100. The average NPS spatial frequencies were higher with DLIR than with IR. For all DLIR levels, TTF50% obtained with DLIR was higher than that with IR. d' was higher with DLIR than with AV50 but lower with DLIR-L and DLIR-M than with AV100. d' values were higher with DLIR-H than with AV100 for the small low-contrast lesion (10 ± 4%) and in the same range for the other simulated lesions. CONCLUSIONS: New DLIR algorithm reduced noise and improved spatial resolution and detectability without changing the noise texture. Images obtained with DLIR seem to indicate a greater potential for dose optimization than those with hybrid IR. KEY POINTS: • This study assessed the impact on image quality and radiation dose of a new deep learning image reconstruction (DLIR) algorithm as compared with hybrid iterative reconstruction (IR) algorithm. • The new DLIR algorithm reduced noise and improved spatial resolution and detectability without perceived alteration of the texture, commonly reported with IR. • As compared with IR, DLIR seems to open further possibility of dose optimization.


Asunto(s)
Algoritmos , Aprendizaje Profundo , Fantasmas de Imagen , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Tomografía Computarizada por Rayos X/métodos , Humanos , Dosis de Radiación
3.
Eur Radiol ; 28(5): 1977-1985, 2018 May.
Artículo en Inglés | MEDLINE | ID: mdl-29168007

RESUMEN

OBJECTIVES: To determine the degree of relationship between iodine concentrations derived from dual-energy CT (DECT) and perfusion CT parameters in patients with advanced HCC under treatment. METHODS: In this single-centre IRB approved study, 16 patients with advanced HCC treated with sorafenib or radioembolization who underwent concurrent dynamic perfusion CT and multiphase DECT using a single source, fast kV switching DECT scanner were included. Written informed consent was obtained for all patients. HCC late-arterial and portal iodine concentrations, blood flow (BF)-related and blood volume (BV)-related perfusion parameters maps were calculated. Mixed-effects models of the relationship between iodine concentrations and perfusion parameters were computed. An adjusted p value (Bonferroni method) < 0.05 was considered significant. RESULTS: Mean HCC late-arterial and portal iodine concentrations were 22.7±12.7 mg/mL and 18.7±8.3 mg/mL, respectively. Late-arterial iodine concentration was significantly related to BV (mixed-effects model F statistic (F)=28.52, p<0.0001), arterial BF (aBF, F=17.62, p<0.0001), hepatic perfusion index (F=28.24, p<0.0001), positive enhancement integral (PEI, F=66.75, p<0.0001) and mean slope of increase (F=32.96, p<0.0001), while portal-venous iodine concentration was mainly related to BV (F=29.68, p<0.0001) and PEI (F=66.75, p<0.0001). CONCLUSIONS: In advanced HCC lesions, DECT-derived late-arterial iodine concentration is strongly related to both aBF and BV, while portal iodine concentration mainly reflects BV, offering DECT the ability to evaluate both morphological and perfusion changes. KEY POINTS: • Late-arterial iodine concentration is highly related to arterial BF and BV. • Portal iodine concentration mainly reflects tumour blood volume. • Dual-energy CT offers significantly decreased radiation dose compared with perfusion CT.


Asunto(s)
Carcinoma Hepatocelular/diagnóstico por imagen , Neoplasias Hepáticas/diagnóstico por imagen , Imagen Radiográfica por Emisión de Doble Fotón/métodos , Tomografía Computarizada por Rayos X/métodos , Anciano , Anciano de 80 o más Años , Carcinoma Hepatocelular/patología , Medios de Contraste/metabolismo , Femenino , Humanos , Yodo/metabolismo , Yopamidol/análogos & derivados , Yopamidol/metabolismo , Hígado/diagnóstico por imagen , Neoplasias Hepáticas/patología , Masculino , Persona de Mediana Edad , Imagen de Perfusión/métodos , Estudios Prospectivos , Intensificación de Imagen Radiográfica/métodos , Reproducibilidad de los Resultados
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