The Influence of Anti-scatter Grid Usage for Knee Computerized Radiography

Luísa Vargas Cassol

Universidade Franciscana (UFN), Santa Maria, RS, Brazil.

Nataly Nogueira Favarin

Universidade Franciscana (UFN), Santa Maria, RS, Brazil.

Felipe de Bail

Universidade Franciscana (UFN), Santa Maria, RS, Brazil.

Edméia Lopes Ramai Buss

Universidade Franciscana (UFN), Santa Maria, RS, Brazil.

Laura Pizarro Trojahn Nogueira

Universidade Franciscana (UFN), Santa Maria, RS, Brazil.

Jéssica Fetzer da Costa Rosa

Universidade Franciscana (UFN), Santa Maria, RS, Brazil.

Thiago Victorino Claus *

Universidade Franciscana (UFN), Hospital Universitário de Santa Maria (HUSM), Santa Maria, RS, Brazil.

*Author to whom correspondence should be addressed.


Aims: This experimental study investigated the effect of using an anti-scatter grid in computerized knee radiography (CR) on image quality (IQ) and patient surface radiation dose (Equivalent Surface Air Kerma – Ka,e), measured with an ionization chamber.

Place and Duration of Study: The experimental study was conducted between February 2024 and April 2024, in the radiodiagnosis laboratory belonging to the Medical Physics and Radiology Technology courses at the Franciscan University (UFN) in the city of Santa Maria, Rio Grande do Sul.

Methodology: Utilizing a semi-anatomical knee phantom to simulate clinical examination conditions, ten images were acquired, with five obtained using technique 1 (70 kV, 200mA, and 20mAs) and another five with technique 2 (70 kVp, 200mA, and 5 mAs), with and without an anti-scatter grid, respectively. The phantom images were digitized in a CR system and quantified using a publicly available automatic analyzer software based on histograms and regions of interest (ROI), defined by signal and noise. The obtained results were used to calculate the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and radiographic contrast (RC), considered IQ descriptors.

Results: As a selection criterion, the percentage deviation (D%) was chosen, considering technique 1 as the reference concerning technique 2. It was observed that technique 1 showed an SNR 1.20%, RC 3.86%, and Ka,e 73.68% higher than technique 2; on the other hand, technique 2 indicated a CNR 4.76% higher compared to technique 1.

Conclusion:  It is concluded that technique 2 without an anti-scatter grid may be preferable when considering the principle of optimization, where the dose is significantly reduced without a significant loss in IQ descriptors.

Keywords: Imaging radiodiagnosis, process optimization, radiography, knee, scattering radiation, signal-to-noise ratio

How to Cite

Cassol, Luísa Vargas, Nataly Nogueira Favarin, Felipe de Bail, Edméia Lopes Ramai Buss, Laura Pizarro Trojahn Nogueira, Jéssica Fetzer da Costa Rosa, and Thiago Victorino Claus. 2024. “The Influence of Anti-Scatter Grid Usage for Knee Computerized Radiography”. Physical Science International Journal 28 (4):29-41.


Download data is not yet available.


Da rocha DGVB, Marcelino LG. Knee trauma approach and treatment: A systematic review. Brazilian Journal of Development. 2022;8(5):33902-33912.

Henner A, Ilves S, Yrjänheikki T. Demonstrating the scattering of radiation in radiographic imaging. European Congress of Radiology-ECR 2015; 2015, March.

Abela N, Couto JG, Zarb F, Mizzi D. Evaluating the use of anti-scatter grids in adult knee radiography. Radiography. 2022;28(3):663-667.

Moore CS, Wood TJ, Jones S, Saunderson JR, Beavis AW. A practical method to calibrate and optimise automatic exposure control devices for computed radiography (CR) and digital radiography (DR) imaging systems using the signal-to-noise ratio (SNR) metric. Biomedical Physics & Engineering Express. 2019; 5(3):035027.

Tompe A, Sargar K. X-ray image quality assurance; 2020.

Metaxas VI, Messaris GA, Lekatou AN, Petsas TG e Panayiotakis GS. Patient doses in common diagnostic X-ray examinations. 2019;184(1):12-27.

Dimenstein R, Ghilardi Netto T. Physical and technological bases applied to x-rays. In Physical and Technological Bases Applied to X-rays. 2005;90- 90.

Seeram E, Davidson R, Bushong S, Swan H. Optimizing the exposure indicator as a dose management strategy in computed radiography. Radiologic Technology. 2016; 87(4):380-391.

Braga LF, Pimentel RB, Dias TS, Assunção MF, Salido FS, Neves RF, Freitas MB. Methodology for analysis and interpretation of exposure indicators (EI) and their deviations (DI) in computerized radiology. Brazilian Journal of Medical Physics. 2019;13(3):33-37.

Wayne R. Software for image processing and analysis. USA: National Institute of Mental Health, java; 2024. Available:

Mraity HA, England A, Cassidy S, Eachus P, Dominguez A, Hogg P. Development and validation of a visual grading scale for assessing image quality of AP pelvis radiographic images. The British Journal of Radiology. 2016;89 (1061): 20150430.

Huda W, Abrahams RB. Radiographic techniques, contrast, and noise in x-ray imaging. American Journal of Roentgenology. 2015;204(2):W126- W131.

Bushberg JT, Boone JM. The essential physics of medical imaging. Lippincott Williams & Wilkins; 2011.