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1 Radiation Protection Dosimetry (2005), Vol. 117, No. 1 3, pp doi: /rpd/nci719 Advance Access published on February 3, 2006 REFERENCE LEVELS IN PTCA AS A FUNCTION OF PROCEDURE COMPLEXITY A. Peterzol 1,2,, E. Quai 2, R. Padovani 2, G. Bernardi 2, C. J. Kotre 3 and A. Dowling 4 1 Dipartimento di Fisica, Università di Trieste, Via Valerio 2, Trieste, Italy 2 Azienda Ospedaliera S. Maria della Misericordia, Udine, Italy 3 Regional Medical Physics Department, Newcastle General Hospital, Newcastle Upon Tyne NE4 6BE, UK 4 Medical Physics and Bioengineering Department, Saint James s Hospital, Dublin 8, Ireland The multicentre assessment of a procedure complexity index (CI) for the introduction of reference levels (RLs) in percutaneous transluminal coronary angioplasties (PTCA) is presented here. PTCAs were investigated based on methodology proposed by Bernardi et al. Multiple linear stepwise regression analysis, including clinical, anatomical and technical factors, was performed to obtain fluoroscopy time predictors. Based on these regression coefficients, a scoring system was defined and CI obtained. CI was used to classify dose values into three groups: low, medium and high complexity procedures, since there was good correlation (r ¼ 0.41; P < 0.001) between dose area product (DAP) and CI. CI groups were determined by an ANOVA test, and the resulting DAP and fluoroscopy time third quartiles suggested as preliminary RLs in PTCA, as a function of procedure complexity. PTCA preliminary RLs for DAP are 54, 76 and 127 Gy cm 2, and 12, 20 and 27 min for fluoroscopy time, for the three CI groups. INTRODUCTION Interventional radiology and interventional cardiology are the X-ray procedures in which patients receive the greatest radiation doses. In some complex cases, patient skin doses can cross the threshold for deterministic effects, producing skin injuries (1). The radiation dose depends on a number of factors, including patient size, equipment, technique and type of examination (2 6). Based on the methodology proposed by Bernardi et al. (7), the study presented here focused attention on the relationship between patient irradiation parameters and procedure complexity (7 12) in 204, 75 and 104 percutaneous transluminal coronary angioplasties (PTCAs) coming from three different centres. A procedure severity-based complexity index (CI) was defined and used for the introduction of reference levels (RLs) in PTCA as a function of procedure complexity. MATERIALS AND METHODS A total of 204, 75 and 104 PTCAs from three different centres were investigated. Exposure data collected by the angiographic systems were fluoroscopy time (FT) (expressed in seconds), dose area product (DAP) during fluoroscopy and DAP during cineangiography giving the total DAP. DAP is expressed in Gy cm 2 and was measured with a large-area parallelplate ionisation chamber. The following procedure was used to calibrate the DAP metres. An ionisation Corresponding author: angela.peterzol@insa-lyon.fr chamber with a calibration traceable to national standards was set up to measure the air kerma under relatively scatter-free conditions (the chamber was positioned 10 cm from the input face of the image intensifier). An arbitrary field size, set using the unit s collimators, was kept constant during the calibration. The X-ray tube voltage was then manually set or forced to 60, 80 and 100 kv using copper attenuators positioned on the intensifier side of the ionisation chamber. Fluoroscopy was performed until a reasonable reading was obtained on the DAP meter and this value, together with the corresponding ionisation chamber reading, was noted. The ionisation chamber was then removed and a computed radiography (CR) plate or film cassette placed in the same plane. The plate/cassette was screened briefly to produce an image of the field and the area of the irradiated field determined from the image. For each tube voltage used, the ionisation chamber reading was corrected using the chamber calibration factor and the result multiplied by the area of the irradiated field. This gives the true DAP. The DAP meter calibration was obtained by dividing the true DAP by the DAP meter reading. The mean of these three calibration factors was used as the DAP meter calibration. The clinical factors recorded were as follows: age, sex, weight, height, multivessel disease single (S), double (D) or triple (T) ejection fraction (EF), previous acute myocardial infarction (AMI), previous coronary artery bypass graft (CABG), presence and class of unstable angina, presence and class of stable angina and presence of actual AMI. Anatomical factors were assessed based on the modified American Heart Association/American College Ó The Author Published by Oxford University Press. All rights reserved. For Permissions, please journals.permissions@oxfordjournals.org

2 of Cardiology (AHA/ACC) grading system classification (13). Occlusion 3 months and the presence of moderate tortuosity (one bend 90 ) and severe tortuosity (two or more bends 90 ) were also measured separately. All lesions were classified as simple if they were type A or had one or two type B characteristics (A, B1 or B2) or complex if they had three or more type B characteristics or were type C. Technical factors identified were as follows: number of vessels, number of lesions treated, the double wire or double balloon technique, simple stenting, ostial stenting (stenting the origin of a major vessel: right coronary, left anterior descending, circumflex or left main artery), bifurcation stenting (stenting the main vessel, the parent vessel or both), directional coronary atherectomy (DCA), rotablator, intravascular ultrasonography (IVUS), extraction atherectomy (EA), laser, flow and pressure wire or any other special devices. A multiple linear stepwise regression analysis was performed in order to obtain the predictors of fluoroscopy time. The model for multiple linear regression is (14) y ¼ b 0 þ b 1 x 1 þ b 2 x 2 þ þb p x p, ð1þ where y is the dependent variable, x 1 p are the independent variables hypothesised to be predictive of y and b 1 p are the regression parameters. A P(twotail) (of the associated variable x i ) < 0.05 was deemed significant. Based on the regression coefficients a scoring system was defined, and a CI was obtained by adding together the single scores for each individual procedure: CI ¼ b 0 1 x 1 þ b 0 2 x 2 þþb 0 p x p: b i b 0 i ¼ : min b 1 ; b 2 ;...; b p ð2þ The correlation between the resulted CI and DAP values was then compared with that between DAP and the equivalent diameter (d e ) of a person, by assuming them to be a cylinder with the density of water d e ¼ 2sqrtðw=phÞ ð3þ with h being the height in cm and w the weight in grams. It has been shown that energy imparted to patients correlates more closely with d e than with weight or patient thickness (15). As suggested by previous work (16), an exponential relationship was assumed between DAP and d e ln DAP ¼ kd e þ c: ð4þ The analysis described above was first performed separately with data from each centre. Since the REFERENCE LEVELS IN PTCA 55 three sets of cases presented some common aspects (several FT predictors belonged to all three models emerged from the multivariate regression), and energy imparted to patients depended mainly on the complexity of the procedure rather than the patient size, an overall CI (CI tot ) was assessed by performing the multiple linear regression with all collected data (383 cases). The latter, which correlated well with DAP, was used to divide dose value results into three groups, which were determined by performing an ANOVA test: different sets of groups were explored until the matrix of pairwise comparison probabilities reached a minimum value. The resulting DAP and FT third quartiles corresponding to each CI group were tentatively suggested as preliminary RLs in PTCA as a function of procedure complexity. RESULTS Sample 1 To find the possible predictors of FT, the simple correlation r of FT vs. all factors was first calculated. Multiple linear regressions were then performed using all factors whose P-value was significant (Table 1). The resulting model is reported in Table 2. Some of the factors with high correlation (Table 1) with FT were not included into the final model (Table 2). This was in part due to the presence of correlations among the possible predictors of Table 1. For example, number of lesions was high correlated with FT (P < 0.001), but was also high correlated with both number of vessels (P < 0.001) and number of complex lesions (P < 0.001). Based on the regression coefficients, a CI was defined in agreement with Equation 2. CI was well correlated with DAP values (r ¼ 0.552; P < 0.001). Correlation between CI and DAP values was compared with that between DAP and d e. A linear fit of the data for lndap vs. d e gave a value for k of cm 1 and a correlation r of (P ¼ 0.001), which was less than the correlation between DAP and CI. Sample 2 The final model resulting from multiple linear regression analysis this time consisted of only two variables (Table 3). A possible reason may be the lower number of cases considered, but it should be noted that the two variables were also found to be predictors of FT in the first trial (Table 2). Anyhow, there was a good correlation between CI2 (CI resulting from second data trial) and DAP values (r ¼ 0.383; P ¼ 0.001). Performing linear fit for ln DAP vs. d e gave a value for k of cm 1 and a correlation r of (P ¼ 0.003). In this second trial DAP

3 A. PETERZOL ET AL. Table 1. Probabilities of null correlation between FT and all investigated factors for first data sample. Factors P Factors P Age Number of simple lesions Sex Number of complex lesions <0.001 Equivalent diameter wire techniques <0.001 S/D/T vessel disease balloon techniques <0.001 EF Number of simple stenting Prev. AMI Number of ostial stenting Prev. CABG Number of bifurc. stenting <0.001 Unstable angina (presented) Number of occlusion 3 months Stable angina (class) Number of mod. tortuosity Actual AMI Number of severe tortuosity <0.001 Number of vessels <0.001 Number of DCA Number of lesions <0.001 IVUS (yes ¼ 1; no ¼ 0) Table 2. First data sample multiple regression analysis Table 4. Third data sample multiple regression analysis Number of vessels Number of complex lesions < wire techniques balloon techniques Number of bifurcation stenting Number of severe tortuosity Table 3. Second data sample multiple regression analysis Number of complex lesions Number of severe tortuosity values also correlated better with CI, rather than patient d e. Sample 3 Executing the multivariate regression analysis on the third sample data gave the model reported in Table 4. The latter consisted of five FT predictors and some of them (number of complex lesions, number of double balloon techniques and number of severe tortuosity) were found to belong to the first sample model as well. Also in this case, good correlation between CI3 (CI resulting from third data trial) and DAP values (r ¼ 0.475; P < 0.001) was found, but no correlation Number of complex lesions < balloon techniques Number of moderate tortuosity Number of severe tortuosity Laser emerged between ln DAP and d e (r ¼ 0.056; P ¼ 0.53). This was an unexpected result, since fluoroscopic devices are usually equipped with an automatic exposure control (AEC) system, the aim of which is to adjust the radiation exposure in order to maintain constant image brightness at image intensifier output window, irrespective of the transmittance of the irradiated region. For this purpose, AEC increases the tube current ma s and the tube potential kv p values when a larger patient is presented to the system, resulting in a dose increase. In addition, it is interesting to point out that all three models did not include clinical factors, only anatomical and technical details. All data In Table 5 the model obtained by grouping all collected data is shown. The latter was quite similar to that related to first sample. A reason could be the larger number of cases belonging to that sample. In any case, the CI obtained from the final model regression coefficients (CI tot ) was well correlated with DAP values (r ¼ 0.41; P < 0.001). Therefore CI tot was used to divide dose values into three groups. The resulting three classes of DAP were defined as follows: Class 1, CI tot 0.7; Class 2, 0.7 < C tot < 1.5; 56

4 Table 5. All collected data sample multiple regression analysis Number of vessels Number of complex lesions < wire techniques Number of bifurcation stenting <0.001 Number of moderate tortuosity Number of severe tortuosity <0.001 REFERENCE LEVELS IN PTCA In a recent work (5), preliminary RLs for DAP and FT in PTCA were tentatively suggested as the 75th percentile of all investigated data coming from six European centres (Greece, Italy, Spain, England, Ireland and Finland) to which the three centres considered here also belonged. The preliminary RLs proposed by Neofotistou et al. (5) (it is noted that in this case no classification of procedure complexity was performed) were as follows: 94 Gy cm 2 and 16 min for DAP and FT, respectively. These values fall in between the simple and the complex levels proposed in this work (Figure 1) and are close to medium values. The results presented in this work are not in contradiction with those reported by Neofotistou et al. (5), despite being obtained using a smaller number of cases. CONCLUSIONS In this study the complexity of interventional procedures was addressed, defining a CI from multiple linear regression analysis having FT as the dependent variable. Since the emerging CI correlated well with patient dose values (DAP correlated better with CI rather than patient size), the process of patient dose optimisation in interventional cardiology can be improved by use of a defined index of procedure complexity. ACKNOWLEDGEMENTS This study received funding from the EC 5th Framework Programme ( ) Nuclear Fission and Radiation Protection Contract DIMOND 111 Nuclear FIGM-CT Figure 1. (a) DAP and (b) FT third quartile values as preliminary reference levels in PTCA for three different classes of procedure complexity: simple (CI 0.7), medium (0.7 < CI < 1.5) and complex (CI 1.5). and Class 3, CI tot 1.5. The corresponding DAP mean values were 41.7, 60.7 and 94.3 Gy cm 2 for the three groups, respectively; whereas the DAP third quartiles (Figure 1a) were 53.8, 76.4 and Gy cm 2, respectively, for the three classes. The FT statistics produced the following: mean values were 8.6, 14 and 22.7 min and third quartiles (Figure 1b) were 12, 20 and 27 min for the three groups, respectively. Hence, the third quartiles of both DAP and FT obtained for the three above defined CI groups were tentatively suggested as preliminary RLs (Figure 1) of DAP and FT values in PTCA as a function of procedure complexity. REFERENCES 1. Vaño, E., Arranz, L., Sastre, J. M., Moro, C., Ledo, A., Garate, M. T. and Minguez, I. Dosimetric and radiation protection considerations based on some cases of patient skin injuries in interventional cardiology. Br. J. Radiol. 71(845), (1998). 2. Vehmas, T. Radiation exposure during standard and complex interventional procedures. Br. J. Radiol. 70, (1997). 3. Marshall, N. W., Chapple, C. L. and Kotre, C. J. Diagnostic reference levels in interventional radiology. Phys. Med. Biol. 45(12), (2000). 4. Mahesh, M. Fluoroscopy: patient radiation exposure issues. Radiographics 21(4), (2001). 5. Neofotistou, V., Vano, E., Padovani, R., Kotre, J., Dowling, A., Toivonen, M., Kottou, S., Tsapaki, V., Willis, S., Bernardi, G. and Faulkner, K. Preliminary reference levels in interventional cardiology. Eur. Radiol. 13(10), (2003). 6. Padovani, R. and Maffessanti, M. Impact of EC directive 97/43 EURATOM in interventional radiology. Radiat. Prot. Dosim. 90, (2000). 57

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