Clinical Focus: Mastering BED And EQD2 With ClearCheck

First Thoughts

We covered the background and basics of the BED and EQD2 model and its applications in a previous post that includes a handy calculator. This supplement intends to provide the clinical context of the BED concepts using ClearCheck software. We provide some examples of how to do this below.

As a quick review, BED is a value that serves to quantify the biologically effective dose delivered using a tissue characterization parameter called the α/β ratio, the fractional dose, and the total number of fractions. Using the same parameters, one can arrive at EQD2, which gives the equivalent dose needed in 2 Gy/fx to achieve that effective dose.

The power of BED and EQD2 lies in the α/β ratio, which characterizes a tissue’s sensitivity to radiation. Tissues that are relatively resistant to the effects of radiation are given a low value, typically 3 Gy, and are called “late responding tissues.” In contrast, relatively radio-sensitive tissues usually have a larger value of around 10 Gy and are called “early responding tissues.” Each tissue has ratios derived from empirical research. However, 3 Gy and 10 Gy are often used for late and early tissues for general clinical purposes, respectively.

ClearCheck QuickStart

Let’s dive in to get started using these valuable quantities in the clinic. We’ll provide a few examples to illustrate the BED/EQD2 functionality offered in ClearCheck. These examples apply for all ClearCheck versions 2.5.12 and newer. If you are using an earlier version of ClearCheck and would like to utilize the BED/EQD2 tools, we strongly recommend upgrading to the latest version for the most accurate results.

To begin, we need to have the correct course and plan opened and the desired constraint template. In the example below, we will be doing a 1000cGy x 5 SBRT Lung following RTOG 0813 dose constraints.

With ClearCheck open, we can click on the template manager (folder-shaped icon below) to add BED or EQD2 calculations.

In the window that opens, ensure that the correct patient constraint template is selected in the top left window. Then, below the center constraints window are two small checkboxes labeled BED and EQD2.

By selecting a box, a new column titled “α/β” will appear next to the “Constraint Type” allowing the user to enter individual α/β ratios for each structure. When saved, ClearCheck will recalculate the DVH for that structure using the BED or EQD2 formulation accounting for specific tissue characterization effects. If no α/β value is entered, ClearCheck will default to the standard calculation without α/β ratio. In our example, I will add an α/β of 4 for the spinal cord and 6 for the lung.

For easy comparison, we suggest duplicating the structure of interest and adding the α/β ratio to the copy. After saving the updated template, we can return to the main ClearCheck window. The structures with α/β ratios will be bolded and appear next to the original structure on this page.

 

When To Use BED/EQD2

BED/EQD2 are useful quantities in assessing the effectiveness of different fractionations. The conversion to standard 2 Gy/fx doses allows for a more familiar constraint comparison. BED/EQD2 are broadly applicable for most clinical treatments, with some caveats. Adjustments are needed for treatments like LDR since repopulation effects must be included in the model due to the low dose rate. Additionally, questions have been raised by some researchers about low dose hypersensitivity (<5 cGy/fx) and the linearity of the model at very high doses (> 20Gy/fx).

EQD2 constraints are most commonly used to convert HDR brachytherapy doses (generally 5-8 Gy/fx) to an equivalent 2Gy fraction dose to be compared to conventional dose fractionation constraints. It can also combine the doses from courses of treatment that do not have a similar fractionation scheme. One example would be to evaluate the cumulative Spinal cord max dose from a previous treatment plan (treated with 200cGy x 30) to the current SBRT treatment plan (treated as 600cGy x 5). Many retreatment limits on the cord, brainstem, bowel, etc., are defined based on EQD2/BED, so the SBRT plan dose would need to be converted before a proper evaluation can take place.

 

Take Your Pick: Standard and Conservative Calculations

Clinically, BED/EQD2 can be used to evaluate patient plan sums when undergoing retreatment or multiple treatments. In ClearCheck, the method of summation of dose between plans within the plan sum is performed using standard BED/EQD2 and conservative BED/EQD2. For individual plans, the two methods will return identical results as there is no temporal or spatial uncertainty in the dose.

The standard approach uses the entire plan sum DVH based on the re-binning of dose voxels in each plan with appropriate fraction numbers applied. This is the recommended method for plan sums with the same CT/structure Set used for each plan or for plan sums where there is similar patient setup and organ position.

Conservative BED/EQD2 will sum equivalent dose values directly from each plan—as these values will lack spatial information—providing a worst-case dose scenario. This is the recommended method for two plans with very different patient setup or organ positions.

 

Plan Sums: When is it appropriate to merge the DVH from multiple plans? And how?

BED calculations often ignore time/spatial dependence when a plan sum DVH is used in Eclipse. For plan sums created from two unique structure sets where significant organ motion may have occurred, Eclipse can only display the plan sum DVH for combined dose applied on one structure set rather than showing the summed DVH calculated uniquely from each plan. Eclipse does not display this sum, as structure volume/position differences between the plan would result in an incorrect estimation.

The biggest issue with Plan Sums is that there is no single parameter describing whether or not multiple plans are treated concurrently or sequentially, as this will affect the number of fractions required for the BED calculation. Here we’ll describe three potential plan sum situations encountered clinically. Each requires a different approach in terms of how constraints and DVH values are interpreted and merged. We’ll address each separately here:

Setup: The planning structure position and volumes match and are treated with the same number of fractions in the same course of treatment.
Example: Plan sum consisting of 3F Breast Tangents + SCV (25Fx) where two plans are treated together on same CT/Structure Set Data.
Operation: By setting both plans to “Phase 1,” ClearCheck will convert the Plan Sum DVH to BED/EQD2 directly as if it is a single plan.

 

Setup: The planning structure position and volumes match and are treated with the same number of fractions in a different course of treatment.

 

Rationale: Dose voxels are rebinned and converted via BED/EQD2 separately and then summed into a new DVH. This is necessary as the BED/EQD2 equation is quadratic and does not scale linearly.

Example: PriorTx (1000 cGy x 5fx) + CurrentTx (1000cGy x 5fx)

N.B. If the phases were incorrectly assigned as both Phase 1, then the non-EQD2 values would be summed prior to conversion (51.55 Gy + 52.18 Gy = 103.73 Gy), resulting in an incorrect value of approximately 266 Gy, as shown here.

Setup: The planning structure position and volumes match but are part of separate, sequential plans.

Rationale: Since the DVH doesn’t provide any information about where the dose levels are within a particular structure volume, rebinning individual dose voxels becomes necessary as the hot and cold spots within the structure may be different between the two plans.

Example: Plan Sum: consisting of Prostate Nodes (25fx) + Prostate Only Boost (20 Fx)

Operation: Each plan’s dose volume is converted based on that plan’s fraction number.

If we look at the location of the maximum bladder dose for each plan, it’s apparent that they are in noticeably different locations.

Below is the maximum bladder dose location for the Nodes 3D plan.

Similarly, the maximum bladder dose location for the Boost 3D plan is shown here.

For the sum of the plans, the maximum bladder dose appears here.

Because of the varied locations of the maximum bladder dose across the two plans and the sum, and because the BED/EQD2 conversions do not scale linearly, we cannot simply perform a BED/EQD2 Conversion on the plan sum DVH to obtain accurate BED/EQD2 values. Also, the plan sum’s hot spot will not necessarily be in the exact location as the BED/EQD2 hot spot, as each plan has a different fractionation, and their respective dose voxels will scale differently.

To resolve this, ClearCheck performs an EQD2 conversion on each plan and dose separately and then sums the converted dose clouds to create the BED/EQD2 DVH, shown below. Because the two plans share the same structure set, the resultant BED/EQD2 values accurately represent the converted plan sum with respect to each plan’s geometry.

 This method converts the individual plan Eclipse DVHs directly to BED/EQD and sums the constraint values directly. For Dose, Max, Min, Mean, Median type constraints ONLY.

This method will match the usual convention of summing “worst-case scenario” doses (i.e. hottest DMax from each plan even if they are in different parts of the volume), so it is possible to verify easily. This is generally the most conservative plan, but it will likely overestimate the true total dose.

Nodes Bladder Max:

Bladder Max Dose of 4717.9 cGy is converted to 4611.4 cGy EQD2.

 

Boost Bladder Max:

Bladder Max Dose of 5232.8 cGy is converted to 5877.9 cGy EQD2.

 

In ClearCheck, we have a Conservative EQD2 Bladder Max of 4611.4 cGy EQD2 + 5877.9 cGy EQD2 = 10489.4 cGy EQD2 (note the different locations within the bladder contour from which the dose max point is derived):

Setup : The planning structure position or volume does not match, and plans are separate and sequential. The most challenging and likely most common scenario where EQD2/BED is needed (HDR treatments, previous outside treatment.)

Example: Pelvis EBRT (25 fx) + HDR Brachy Boost (5 fx)

 

Re-Binning Method

In this case, the approach is similar to situation 2a, but additional spatial uncertainty of the structures themselves along with dose spatial uncertainty needs to be accounted for. If a deformable image registration was applied, we could revert to situation 2a, as we would be able to map dose from one structure set onto another. However, standard rigid registration is often used in these scenarios. The structure location and position from the primary structure set are used, and the rigid registration is used to map the dose from the secondary structure set to the primary. In this case, organ motion or imperfect registrations introduce uncertainty. The dose voxels are converted as in Situation 2a and re-binned to a new DVH.

 

Conservative Method

Again, choosing this option converts the individual plan DVH on its respective structure set directly to BED/EQD2 and sums the constraint values directly. This applies for Dose Max, Min, Mean, Median type constraints ONLY.

This method will match the usual convention of summing “worst-case scenario” dose (i.e. hottest DMax from each plan even if they are in different parts of the body) so it can be easily verified and is generally the most conservative way to plan. Still, it is less accurate to the actual total dose.

This is the most common method clinics currently use to evaluate dose from different scans or different treatment courses, as it has the benefit of allowing them to sum dose from prior plans that may not have a DVH calculated, and a single dose is assumed from a previous treatment.

 

One Last Thing: Setting User-Defined Threshold to Ignore BED/EQD2

Within the ClearCheck Administration application, under the “Settings” tab, a checkbox allows the users to enable a range of fraction doses within which BED/EQD2 calculations will be ignored.

Conclusion

Biologically effective dose can be a powerful tool for quantitative analysis when comparing the relative value of various fractionation schemes. However, as noted in the previous post, it is based on the linear-quadratic model, which has underlying assumptions that are important to understand, such as negligible cell proliferation, patient-specific characteristics, and vascular pathology. Therefore, clinical judgment should always be used to evaluate the values and metrics provided by ClearCheck or any other software.