Götz Richter, Medical Director, Katharinenhospital Stuttgart, Germany, shares practical pointers on reducing the radiation dose when performing uterine fibroid embolization (UFE) and prostatic artery embolization (PAE).
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Professor Richter, how did your experience with UFE inform your PAE practice?
Richter: We started offering PAE around six years ago. Katharinenhospital is a center for multidisciplinary uterine fibroid treatment and we have vast experience with UFE, which we began offering to patients in 1999. There are significant similarities between the male and female vascular anatomies, although the uterine artery is usually a much larger vessel than the arterial supply to the prostate gland. PAE is similar to UFE, but much more complex. Still, we have found very high rates of patient satisfaction with the procedure as it is virtually painless for patients and the hospital stay is very short. The improvement in clinical symptoms, although slower than with resection, is clear and the procedure is satisfactory to patients in around 90% of cases, as measured using several objective parameters.
What does your research show with regard to dose optimization achieved by changing procedural and imaging aspects?
Richter: A very recent (April 30, 2019) evaluation of the dose area products of all our UFE patients (27) reveals that the radiation dose has dropped significantly to an average of 654 cGy·cm2 (range 198-3,071) by changing imaging aspects. In 2016, we published our dose area product (DAP) for UFE procedures. On average values, our values were a little over 1,100 cGy·cm2. In 2017, having included 43 patients (with an average body mass index of 21.7), it was calculated to be 961 cGy·cm2. This significant reduction was achieved by reducing the number of digital subtraction angiography (DSA) runs and replacing them with fluoroscopy.
In order to position the catheter, we can then use 2D overlay techniques after choosing a well-contrasted image from the fluoro run as provided by our Artis zeego1 system.
In PAE patients, the DAP is usually higher as we apply cone-beam CT prior to the procedure, so we reach an average of around 6,500 cGy·cm2. We do not perform prior pelvic CT examinations, as some other institutions do, because this contributes to a higher radiation dose.
I would strongly recommend that beginners first perform either a highquality pelvic CT or use cone-beam CT, as we do, to identify the vascular anatomy. Furthermore, high frequency fluoroscopy and DSA should be avoided and collimation should be perfect. Then, the DAP of the procedure alone (i.e., when the dose of cone-beam CT is not taken into account), can and should be below 5,000 cGy·cm2.
What measures do you recommend for reducing operator dose?
Richter: Before embarking on dose reduction strategies, first and foremost, operators need to achieve an adequate expertise with the pelvic vascular anatomy. Once this is achieved, it is important to set a low frame rate for fluoroscopy (4/s); low frame rate for DSA (1/s or 0.5/s) and the best possible collimations. Additionally, it is critical to avoid DSA whenever possible by using fluoroscopy overlay technology and to use a minimum number of oblique projections. Whenever possible, it is also useful to employ image fusion guidance. All these measures will result in dose reductions for both the operator and the patient.
Have you established a well-defined PAE workflow at your hospital?
Richter: Our workflow is highly standardized and includes pre-interventional imaging, lab values, objective and symptomatic urologic assessment, which are based on the applicable guidelines. Then, during the procedure (with a Foley catheter)
syngo DynaCT is used to identify the pelvic vascular anatomy. Embolization is performed with a microcatheter (2–2.7 F) using embolic particles < 400 microns.
Professor Richter, thank you for taking the time to talk with us.
The current product is ARTIS pheno.
The statements by Siemens Healthineers customers described herein are based on results that were achieved in the customer’s unique setting. Since there is no “typical” hospital and many variables exist (e.g., hospital size, case mix, level of IT adoption) there can be no guarantee that other customers will achieve the same results.