A comprehensive assessment of physical image quality of five different scanners for head CT imaging as clinically used at a single hospital centre—A phantom study

Abstract

Nowadays, given the technological advance in CT imaging and increasing heterogeneity in characteristics of CT scanners, a number of CT scanners with different manufacturers/technologies are often installed in a hospital centre and used by various departments. In this phantom study, a comprehensive assessment of image quality of 5 scanners (from 3 manufacturers and with different models) for head CT imaging, as clinically used at a single hospital centre, was hence carried out. Helical and/or sequential acquisitions of the Catphan-504 phantom were performed, using the scanning protocols (CTDIvol range: 54.7–57.5 mGy) employed by the staff of various Radiology/Neuroradiology departments of our institution for routine head examinations. CT image quality for each scanner/acquisition protocol was assessed through noise level, noise power spectrum (NPS), contrast-to-noise ratio (CNR), modulation transfer function (MTF), low contrast detectability (LCD) and non-uniformity index analyses. Noise values ranged from 3.5 HU to 5.7 HU across scanners/acquisition protocols. NPS curves differed in terms of peak position (range: 0.21–0.30 mm-1). A substantial variation of CNR values with scanner/acquisition protocol was observed for different contrast inserts. The coefficient of variation (standard deviation divided by mean value) of CNR values across scanners/acquisition protocols was 18.3%, 31.4%, 34.2%, 30.4% and 30% for teflon, delrin, LDPE, polystyrene and acrylic insert, respectively. An appreciable difference in MTF curves across scanners/acquisition protocols was revealed, with a coefficient of variation of f50%/f10% of MTF curves across scanners/acquisition protocols of 10.1%/7.4%. A relevant difference in LCD performance of different scanners/acquisition protocols was found. The range of contrast threshold for a typical object size of 3 mm was 3.7–5.8 HU. Moreover, appreciable differences in terms of NUI values (range: 4.1%-8.3%) were found. The analysis of several quality indices showed a non-negligible variability in head CT imaging capabilities across different scanners/acquisition protocols. This highlights the importance of a physical in-depth characterization of image quality for each CT scanner as clinically used, in order to optimize CT imaging procedures.

CT image quality metrics implementation during thorax SPECT/CT clinic studies

“…Las diferencias encontradas en este indicador (RCR), que en este caso se considera tarea orientado por la definición directa en estructuras o tejidos anatómicos de interés, tienen una amplia variación en la literatura de los últimos años, especialmente por la importancia que ha ganado la optimización de dosis, y las diversas definiciones matemáticas empleadas. Este término fue definido en maniquíes de control de calidad (donde el fondo es de material uniforme y en una sola región), y en su aplicación orientada a tareas clínicas, ha encontrado como sustituto, en algunas investigaciones científicas, una definición de ruido asociada a una sola estructura anatómica, que varía con el reporte de cada autor, al igual que sus resultados (15)(16)(17)(18)(19)(20)(21)(22). Este trabajo sugiere que, para estimar y comparar las RCRc, es favorable tener en cuenta las estructuras que realmente se relacionan entre sí de forma visual, y que las relaciones de estructuras de mayor contraste pueden ser más sensibles estadísticamente a cambios relacionados con la calidad de la imagen y su percepción.…”

“…La propuesta de este trabajo, opta por emplear, como métricas de calidad dos que no utilizan imagen de referencia: la relación contraste ruído, definida de forma típica para las imágenes de Toráx y relacionada con los órganos críticos implicados en la evaluación de la imagen de tórax (directamente relacionada con la resolución de contraste); y define además otro parámetro que puede caracterizar la imagen clínica concreta, que se relaciona directamente con la resolución espacial de las estructuras de la misma región. Ambas variables son componentes y descriptores importantes de la detectabilidad que brinda la imagen (1,3,19,21,23). Esta alternativa, que combina ambas métricas, podrían esclarecer favorablemente las interrogantes plateadas por algunos autores, sobre el impacto de los nuevos métodos avanzados de Reconstrucción Iterativa que, al producir una disminución significativa de los niveles de ruido, pueden afectar la resolución de bordes y de bajo contraste y por ende la capacidad de diagnosticar favorablemente (24)(25)(26)(27).…”

A Review of Imaging Methods to Assess Ultrasound-Mediated Ablation

“…This translates into a reduction of the attenuation coefficient and thus a decrease in measured Hounsfield units (HU) of ~0.5 HU per °C [ 68 ]. Given that typical noise levels on clinical scanners range from 3 to 6 HU [ 69 ], this is sufficient temperature resolution for thermal HIFU but lacks the temperature SNR achieved with MR thermometry. Additionally, CT has ample temporal resolution to guide ablative therapies in real time.…”

Investigation of a potential upstream harmonization based on image appearance matching to improve radiomics features robustness: a phantom study

“…Phantoms are physical models that mimic biological tissue and its properties in medical imaging. They are typically used for both quality control in clinical practice and research (Barca et al 2018, Barca et al 2021. Indeed, unlike patients, who require considerations regarding radiation dose delivery, phantoms are particularly suitable for exploring imaging settings across different scanners and parameters.…”