A new method of real-time skin dose visualization. Clinical evaluation of fluoroscopically guided interventions

Boujan, F.; Clauss, Nicolas; Santos, Emilie M. M.; Boon, Sjirk N.; Schouten, Greetje; Mertz, Luc; Dietemann, Jean-Louis

doi:10.1007/s00234-014-1401-8

Cited by 6 publications

(8 citation statements)

References 12 publications

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“…Events of radiation doses above critical levels (Table 2) shall be discussed in a Quality Assurance–Peer Review committee including a qualified medical physicist. If possible and necessary, appropriate steps should be taken to avoid future events [74]. In most cases, an excessive patient skin dose can be avoided by simple and clinically feasible changes of practice.…”

Section: Dose Management Before During and After The Proceduresmentioning

confidence: 99%

Radiation-Induced Skin Injuries to Patients: What the Interventional Radiologist Needs to Know

Jaschke

Schmuth

Trianni

et al. 2017

Cardiovasc Intervent Radiol

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For a long time, radiation-induced skin injuries were only encountered in patients undergoing radiation therapy. In diagnostic radiology, radiation exposures of patients causing skin injuries were extremely rare. The introduction of fast multislice CT scanners and fluoroscopically guided interventions (FGI) changed the situation. Both methods carry the risk of excessive high doses to the skin of patients resulting in skin injuries. In the early nineties, several reports of epilation and skin injuries following CT brain perfusion studies were published. During the same time, several papers reported skin injuries following FGI, especially after percutaneous coronary interventions and neuroembolisations. Thus, CT and FGI are of major concern regarding radiation safety since both methods can apply doses to patients exceeding 5 Gy (National Council on Radiation Protection and Measurements threshold for substantial radiation dose level). This paper reviews the problem of skin injuries observed after FGI. Also, some practical advices are given how to effectively avoid skin injuries. In addition, guidelines are discussed how to deal with patients who were exposed to a potentially dangerous radiation skin dose during medically justified interventional procedures.

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Section: Dose Management Before During and After The Proceduresmentioning

confidence: 99%

Radiation-Induced Skin Injuries to Patients: What the Interventional Radiologist Needs to Know

Jaschke

Schmuth

Trianni

et al. 2017

Cardiovasc Intervent Radiol

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“…In the following, skin dose and skin entrance dose are used interchangeably. Keeping the physicians aware of the radiation dose by online monitoring of overall skin dose and PSD is important to prevent skin injuries . Common metrics considered in this process are the fluoroscopic time, frame rate, dose‐area‐product (DAP), and the cumulative kerma (K

_{IRP}

) at the interventional reference point (IRP).…”

Section: Introductionmentioning

confidence: 99%

“…Thus, prevailing online skin dose tracking methods rely on the assumption of a linear relationship between air kerma measured at the IRP and skin dose . To find a good relationship between air kerma and skin dose, various correction terms can be considered to account for backscatter, material attenuation, table attenuation, and source‐to‐skin surface distance to name a few as well as some form of patient modeling.…”

Section: Introductionmentioning

confidence: 99%

“…Keeping the physicians aware of the radiation dose by online monitoring of overall skin dose and PSD is important to prevent skin injuries. 13 Common metrics considered in this process are the fluoroscopic time, frame rate, dose-area-product (DAP), and the cumulative kerma (K IRP ) at the interventional reference point (IRP). While the fluoroscopic time correlates poorly with PSD, DAP, and K IRP are considered to exhibit a generally reasonable correlation.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, prevailing online skin dose tracking methods rely on the assumption of a linear relationship between air kerma measured at the IRP and skin dose. 13,[15][16][17] To find a good relationship between air kerma and skin dose, various correction terms can be considered to account for backscatter, material attenuation, table attenuation, and source-to-skin surface distance to name a few as well as some form of patient modeling. Especially the accurate determination of backscatter contribution to the total dose distribution across the skin is crucial to quantitatively assess skin dose, since scattered radiation may increase the total dose between 30% and 60%.…”

Section: Introductionmentioning

confidence: 99%

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Physics‐driven learning of x‐ray skin dose distribution in interventional procedures

et al. 2019

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Purpose Radiation doses accumulated during very complicated image‐guided x‐ray procedures have the potential to cause stochastic, but also deterministic effects, such as skin rashes or even hair loss. To monitor and reduce radiation‐related risks to patients’ skin, x‐ray imaging devices are equipped with online air kerma monitoring components. Traditionally, such measurements have been used to estimate skin entrance dose by (a) estimating air kerma at the interventional reference point (IRP), (b) forward projecting the dose distribution, and (c) considering a backscatter factor among other correction factors. Unfortunately, the complicated interaction between incident x‐ray photons, secondary electrons, and skin tissue cannot be properly accounted for by assuming a linear relationship between forward projected air kerma and a backscatter factor. Gold standard skin dose models are therefore determined using Monte Carlo (MC) techniques. However, MC simulations are computationally complex in general and possible acceleration mainly depends on the employed hardware and variance reduction techniques. To obtain reliable and fast dose estimates, we propose to combine MC‐based simulations with learning‐based methods. Methods The basic idea of our method is to approximate the radiation physics to calculate a first‐order exposure estimate quickly. This initial estimate is then refined using prior knowledge derived from MC simulations. To this end, the primary photon propagation inside a voxelized patient model is estimated using a less accurate but fast photon ray casting (RC) simulation based on the Beer–Lambert law. The results of the RC simulation are then fed into a convolutional neural network (CNN), which maps the propagation of primary photons to the dose deposition inside the patient model. Additionally, the patient model itself including anatomy and material properties, such as mass density and mass energy‐absorption coefficients, are fed into the CNN as well. The CNN is trained using smoothed results of MC simulations as output and RC simulations of identical imaging settings and patient models as input. Results In total, 163 MC and associated RC simulations are carried out for the head, thorax, abdomen, and pelvis in three different voxel phantoms. We used 108 or 109 primarily emitted photons sampled from a 125 kV peak voltage spectrum, respectively. Edge‐preserving smoothing (EPS) is applied to reduce (a) general stochastic uncertainties and (b) stochastic uncertainty concerning MC simulations of less primary photons. The CNN is trained using seven imaging settings of the abdomen in a single phantom. Testing its performance on the remaining datasets, the CNN is capable of estimating skin dose with an error of below 10% for the majority of test cases. Conclusion The combination of deep neural networks and MC simulation of particle physics has the potential to decrease the computational complexity of accurate skin dose estimation. The proposed approach can provide dose distributions in under one second when runni...

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Feasibility of setting up generic alert levels for maximum skin dose in fluoroscopically guided procedures

et al. 2018

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A new method of real-time skin dose visualization. Clinical evaluation of fluoroscopically guided interventions

Abstract: SDM also has many advantages over the radiochromic films, such as real-time dose evaluation and easy access to critical operational parameters for physicians and technicians.

Cited by 6 publications

References 12 publications

Radiation-Induced Skin Injuries to Patients: What the Interventional Radiologist Needs to Know

Radiation-Induced Skin Injuries to Patients: What the Interventional Radiologist Needs to Know

Physics‐driven learning of x‐ray skin dose distribution in interventional procedures

Feasibility of setting up generic alert levels for maximum skin dose in fluoroscopically guided procedures

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