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1.
Eur Radiol ; 29(12): 6794-6804, 2019 Dec.
Article in English | MEDLINE | ID: mdl-31144074

ABSTRACT

OBJECTIVES: To compare institutional dose levels based on clinical indication and BMI class to anatomy-based national DRLs (NDRLs) in chest and abdomen CT examinations and to assess local clinical diagnostic reference levels (LCDRLs). METHODS: From February 2017 to June 2018, after protocol optimization according to clinical indication and body mass index (BMI) class (< 25; ≥ 25), 5310 abdomen and 1058 chest CT series were collected from 5 CT scanners in a Swiss multicenter group. Clinical indication-based institutional dose levels were compared to the Swiss anatomy-based NDRLs. Statistical significance was assessed (p < 0.05). LCDRLs were calculated as the third quartile of the median dose values for each CT scanner. RESULTS: For chest examinations, dose metrics based on clinical indication were always below P75 NDRL for CTDIvol (range 3.9-6.4 vs. 7.0 mGy) and DLP (164.0-211.2 vs. 250 mGycm) in all BMI classes except for DLP in BMI ≥ 25 (248.8-255.4 vs. 250.0 mGycm). For abdomen examinations, they were significantly lower or not different than P50 NDRLs for all BMI classes (3.8-9.0 vs. 10.0 mGy and 192.9-446.8 vs. 470mGycm). The estimated LCDRLs show a drop in CTDIvol (21% for chest and 32% for abdomen, on average) with respect to current DRLs. When considering BMI stratification, the largest LCDRL difference within the same clinical indication is for renal tumor (4.6 mGy for BMI < 25 vs. 10.0 mGy for BMI ≥ 25; - 117%). CONCLUSION: The results suggest the necessity of estimating clinical indication-based DRLs, especially for abdomen examinations. Stratifying per BMI class allows further optimization of the CT doses. KEY POINTS: • Our data show that clinical indication-based DRLs might be more appropriate than anatomy-based DRLs and might help in reducing large variations in dose levels for the same type of examinations. • Stratifying the data per patient-size subgroups (non-overweight, overweight) allows a better optimization of CT doses and therefore the possibility to set LCDRLs based on BMI class. • Institutions who are fostering continuous dose optimization and LDRLs should consider defining protocols based on clinical indication and BMI group, to achieve ALARA.


Subject(s)
Body Mass Index , Radiation Dosage , Radiography, Abdominal/methods , Radiography, Thoracic/methods , Tomography, X-Ray Computed/methods , Abdomen/diagnostic imaging , Adolescent , Adult , Aged , Aged, 80 and over , Female , Humans , Male , Middle Aged , Physical Examination , Prospective Studies , Reference Values , Thorax/diagnostic imaging , Young Adult
2.
Acta Radiol ; 57(3): 311-7, 2016 Mar.
Article in English | MEDLINE | ID: mdl-25838452

ABSTRACT

BACKGROUND: In chest computed tomography (CT), iterative reconstruction (IR) algorithms maintain diagnostic image quality (IQ) while significantly reducing the dose. PURPOSE: To evaluate the impact of IR on IQ of chest CT at effective doses below 0.3 mSv. MATERIAL AND METHODS: Twenty chest CT scans performed at effective dose below 0.3 mSv (CT1) were reconstructed varying three parameters: filtered back-projection and IR iDose(4) algorithms; 512 × 512 and 768 × 768 matrices; and sharp and soft kernels, thus generating eight series per patient. The qualitative evaluation of the IQ was performed by ranking series from 1 to 8 (8 corresponding to the highest rank) which was subsequently compared to quantitative assessment of IQ by using an appropriated merit formula. Intra- and inter-reader IQ ranking reliability was also evaluated using Cohen's kappa. Analysis of lung findings was finally compared between the best CT1 series and the reference CT (CT0). RESULTS: The best series in terms of qualitative and quantitative IQ was obtained using IR, 512(2) matrix and soft kernel. The best CT1 series detected nodules greater than 4 mm with an almost perfect match with CT0. CONCLUSION: Chest CT performed at effective doses below 0.3 mSv may be used to confidently diagnose lesions greater than 4 mm using iDose(4), soft kernel and 512 × 512 matrix.


Subject(s)
Lung Neoplasms/diagnostic imaging , Radiation Dosage , Radiographic Image Enhancement , Radiographic Image Interpretation, Computer-Assisted , Tomography, X-Ray Computed , Adult , Aged , Aged, 80 and over , Female , Humans , Image Processing, Computer-Assisted , Lung/diagnostic imaging , Male , Middle Aged , Reproducibility of Results , Sensitivity and Specificity
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