D and V notation in radiation therapy planning

One of the commonly used notation conventions in radiation therapy planning is the D and V notation (e.g. D90 and V120). In this short post I will explain them.

The D and V notation are conventions that are designed to designate volumes and doses that correspond to features and goals in a treatment plan (doses and volumes).

DXX designates the minimum absorbed dose received by XX% of the total volume of a structure of interest.

Example: D90 of the prostate = 65 Gy.
This means that 90% of the prostate volume receives at least 65 Gy. This is determined from the cummulative DVH (explained in this post) and can be read off the cDVH. The D90 can be visualized in a TPS by setting the minimum display dose to 65 Gy.

Note: Instead of percent of the volume DXX could be specified in absolute volume, such as cm³.

D50 of the breast volume is determined on the cDVH to be equal to 307 cGy.

VXX designates the volume that receives XX Gy.

Example: V120 of the prostate
This would be the volume of the prostate that receives 120 Gy from the current plan. This value is also determined from the cDVH. Your graphical TPS will display this as a 3D volume or an isodose contour.

Note: Instead of gray the dose in VXX could be specified as percent dose (typically normalized to DRx).

V8 (or V57%) of the breast volume is determined from the cDVH to be equal to 147.8 cm³.

The V and D notations are simply arbitrary conventions, which are easy to confuse. Hopefully this post will serve as a reference to remind you what the notations mean.

I hope this helps and let me know if you have questions or corrections.

IMAT/VMAT basics

One of the newest and most interesting external beam delivery techniques today goes by many names: intensity modulated arc therapy (IMAT), volumetric modulated arc therapy (VMAT), etc. To make things more confusing, vendors have each given this technique their own proprietary names: RapidArc (Varian), SmartArc (Philips), and VMAT^TM [didn't I already say VMAT?] (Elekta). Maybe the most general and correct name for IMAT would be cone-beam dynamic angle fluence modulated x-ray therapy (CBDAFMXT), but you might confuse that acronym with a chemotherapy drug name... In this post I'll discuss some of the basics of this arc-based form of IMRT (and just call it IMAT to keep things simple).

At its most basic IMAT is essentially conventional IMRT, but with the gantry moving in one or more rotating arcs, rather than delivering from a small number of fixed angles. This means that most of the concepts and advantages and disadvantages of IMRT apply to IMAT (detailed below). IMAT was developed (and marketed!) as a conventional linac-based alternative to helical tomotherapy and as a more conformal / lower critical structure dose and faster version of static angle IMRT.

The hierarchy of IMRT techniques.

In the figure showing the IMRT hierarchy, IMAT is on the branch of cone-beam, dynamic gantry IMRT. In order to deliver IMAT, a linac must have some of the following capabilities: gantry motion with beam on, dynamic MLC (i.e. leaf motion with beam on and gantry rotating), and variable dose rate.

Planning of IMAT is very similar to conventional IMRT. The plan is determined by inverse planning methods. The degrees of freedom are increased by considering gantry rotation speed, dose rate, number of field shapes, number of arcs, etc. For planning, arcs are usually approximated with a finite number of angles (e.g. 36). Constraints can be more tightly matched with multiple arcs at the expense of delivery time. Another important aspect in IMAT optimization is that MLC leaf speed limits the beam shape "distance" from one angle to the next, i.e. the MLC leaf positions cannot vary greatly from one angle to the next and thus beam shape "interconnectedness" must be taken in to account.

Advantages of IMAT include:

• Highly conformal target volume dose with lower dose to critical structures than IMRT or 3DCRT, as dose is spread over more angles.
• Faster delivery times and lower MU's (especially single arc IMAT) when compared with IMRT.
• Non-co-planar arcs possible.
• Comparable plans to helical tomotherapy, but performed with a conventional linac.

Disadvantages of IMAT include:

• Higher cost of hardware and software licensing relative to IMRT.
• Increased complexity of plans makes QA a poor diagnostic tool (i.e. hard to determine source of QA failures).

IMAT delivery techniques are the obvious(?) next step following IMRT. In fact, it's hard to come up with a list of concrete disadvantages of IMAT over IMRT. (Please comment if you feel otherwise.) In our clinic it's one of the few new techniques that everyone seems to have adopted with open arms.

Further reading:

• Cedric X Yu and Grace Tang, Intensity-modulated arc therapy: principles, technologies and clinical implementation, 2011 Phys. Med. Biol. 56 R31 doi:10.1088/0031-9155/56/5/R01 (open access).
• David Shepard, Clinical Implementation of Intensity Modulated Arc Therapy, presentation, 2009, http://www.medicaldosimetry.org/meetings/2009handouts/Shepard_VMAT.pdf

The many faces of bolus: Part 2

Previously I discussed the role of bolus material in radiation therapy and some of the forms it takes. This post shows a couple of other examples.

Pink bolus molded into shape.

Super Stuff bolus, also known generically as pink bolus, is a moldable bolus material with the consistency of gelatin. The material is described by the manufacturer as a "hydophilic organic polymer" and is sold in individual powder packets. Pink bolus is supposed to have a density of 1.02 g/cm³. To use the bolus, you add the necessary amount of water, allow the material to set, i.e. coming to its gelatin-like consistency, and then knead it into the shape you want. Over time pink bolus will lose its shape and must be re-shaped. Eventually it will lose some consistency due to moisture loss and a new batch must be made. Care must also be taken to remove as many air bubbles as possible.

A packet of pink bolus powder.

Recently in our clinic we treated a patient with classic (i.e. non-HIV related) Kaposi sarcoma of the leg with photons. For this we decided to use rice grains as the bolus material. As with all bolus, the idea of using rice is to simulate tissue and modify the dose distribution as desired. In this case, increase of skin dose is desired.

Rice bolus box for treating a patient's leg/foot.

For this patient we built a polystyrene foam box and filled it with loose rice grains. It took approximately 10 kg of dry parboiled rice to fill the box with the patient's leg. The patient plus rice box was then scanned with the CT and planned as normal.

Some leftover rice (not) used as bolus material.

The open access article linked below from Ahn et al. shows some dosimetric comparisons between the use of rice as a bolus and a water bolus for irradiating extremities. I will warn you that both methods create a mess at best :)

Further reading:

• Ahn SK, Kim YB, Lee IJ, Song TS, Son DM, Jang YJ, Cho JH, Kim JH, Kim DW, Cho JH, Suh CO.   Evaluation of a Water-based Bolus Device for Radiotherapy to the Extremities in Kaposi's Sarcoma Patients.   J Korean Soc Ther Radiol Oncol. 2008 Sep;26(3):189-194.   http://dx.doi.org/10.3857/jkstro.2008.26.3.189 (Open access. In Korean with abstract and figure captions in English.)

Dose-volume histogram basics

A dose-volume histogram (DVH) is a mathematical tool to assess the appropriateness of a given radiation therapy plan. It can be used to assess whether a plan meets desired constraints for a voulme of interest, within certain limitations. DVH’s are widely used and understanding how they work is a basic skill for treatment plan assessment. In this post I’ll discuss some DVH basics.

A typical cumulative dose-volume histogram (cDVH).

A DVH is nothing more than a histogram, but it is important to understand where the data comes from and how the DVH is representing the data. Modern treatment plans are created based on 3D image sets created using CT, MRI, etc. These data sets consist of voxels (the 3D equivalent of pixels). A volume of interest, e.g. a PTV, consists of a subset of these voxels. The basic data in a DVH is generated by binning the dose values from each voxel in the volume. (Interpolation may be necessary if the bound of the volume intersects a voxel.) This binned dose frequency data comprises a differential dose-volume histogram, or dDVH, which I will discuss in more detail in a future post. The dDVH looks like a common histogram and gives you an idea of how many voxels receive a certain dose, e.g. the dDVH might show that 85% of the PTV voxels received 98% - 102% of the prescribed dose and 46% received exactly 100% of the prescribed dose.

The more familiar form of DVH is the cumulative dose-volume histogram, or cDVH. This DVH is calculated by summing the dDVH starting at the dose of interest, D, up to the max dose, D_max (Eq. 1).

Eq. 1

The cDVH displays the percent/number of voxels in a volume which receive at least a dose D, i.e. the cDVH of a volume irradiated perfectly uniformly to 100 cGy will show that 100% of the voxels received at least 30 cGy, 50 cGy, 80 cGy, etc, but 0% received 105 cGy. Thus for an ideal treatment plan, the cDVH’s of the target volumes will have a rectangular, step-down function appearance and the cDVH’s of critical volumes will drop immediately to zero.

In the real world treatment plans are not ideal (I know, it’s sad). Instead acceptable dose constraints are set for targets and critical structures. DVH’s can be used to determine if these constraints are mets. One caveat is that standard DVH’s do not directly provide spatial information about the dose distribution. One less than ideal method is to create sub-volumes, but creating useful/meaningful sub-volumes is a non-trivial exercise.

Top image from Vorwerk et al. Radiation Oncology 2008 3:31, doi:10.1186/1748-717X-3-31, used under CC License terms.

Compensator-based IMRT

Intensity modulated radiation therapy (IMRT) is almost always performed with the use of a multileaf collimator (MLC). This is, however, not the only way to deliver static angle IMRT. Another method is with the use of compensator blocks. In this post I will talk a little bit about this less common IMRT technique.

Brass IMRT field compensator from .decimal, Inc.

As discussed in a previous post, IMRT requires fluence modulation not possible with conventional poured / hand-cut blocks. This fluence modulation is necessary to achieve the desired target matching and critical structure sparing via inverse planning optimization. This fluence modulation is typically achieved using an MLC, which has many advantage as well as disadvantages. An alternative method, in use since at least the mid 1990's, is fluence modulation via solid compensator blocks designed for each individual field. The above image shows a sample compensator made of milled brass.

Compensator-based IMRT is purported to have several advantages over MLC-based IMRT, including:

• Being static, each field is delivered more quickly (also lower MU's).
• Fluence patterns can be closer to the ideal, i.e. not limited by leaf size, speed, or leakage.
• Potentially cheaper.
• Avoids field splitting. (Did I ever mention I hate split fields?!?)

Along with these advantages come possible drawbacks, including:

• Long fabrication times, versus automated MLC patterens.
• Therapists must change compensator for each field.
• Potential for beam hardening.
• Large size / weight to achieve low dose regions.

Compensators can be fabricated from a range of materials, including brass, Wood's metal (Cerrobend), PMMA (Plexiglas), and tungsten powder composite. Milling. molding, or stacking and bolting are possible fabrication techniques. A handful of companies sell custom fabricated IMRT compensators on demand, delivering within one or two days of order.

Do you have any experience with this technique?

Further reading:

• Chang, S., Cullip, T., Deschesne, K., Miller, E., & Rosenman, J. Compensators: An alternative IMRT delivery technique. Journal Of Applied Clinical Medical Physics, 5(3), 2004. doi:10.1120/jacmp.v5i3.1965 (open access)
• P.C. Williams, IMRT: delivery techniques and quality assurance, British Journal of Radiology (2003) 76, 766-776, doi: 10.1259/bjr/12907222 (open access?)

Medical physics journals

If you want to keep up to date on the latest developments in medical physics, journals are one of the best resources. In this post I'm going to compile a list of medical physics journals and journals with medical physics related content. I will also mention the degree of open access for each journal (that I'm aware of) and the h-index as computed by Google Scholar.

Medical physics specific journals:

• Medical Physics, published by AAPM. Some article types made open access. h5-index: 45.
• Physics in Medicine and Biology, published by Institute of Physics. Open access option for authors with publishing fee. h5-index: not available.
• Journal of Applied Clinical Medical Physics, published by AAPM. Fully open access. h5-index: 15.
• Journal of Medical Physics, published by the Association of Medical Physicists of India. Fully open access. h5-index: 7.
• arXiv.org medical physics category. Fully open access. Overall for arXiv.org, h5-index: 256.
• Magnetic Resonance in Medicine, published by the International Society for Magnetic Resonance in Medicine. Paid access only. h5-index: 50.

Other journals with medical physics content:

• The Red Journal (International Journal of Radiation Oncology * Biology * Physics), published by ASTRO. Paid access only. h5-index: 68.
• The Green Journal (Radiotherapy and Oncology), published by ESTRO. Paid access only. h5-index: 48.
• Radiation Oncology, published by BioMed Central. Fully open access. h5-index: 23.
• Practical Radiation Onoclogy, published by ASTRO. Paid access only.  h5-index: N/A.
• Medical Dosimetry, published by the American Association of Medical Dosimetrists. Paid access only. h5-index: 15.

More info can be found on the state of open access and medical physics publications in my post about open access on Will Work for Science.

Any other additions to add?

Comparing dose distributions: The gamma test

In my last post I discussed dose distribution comparison with dose difference and distance-to-agreement (DTA) tests. Another widely used and closely related method for comparing dose distributions is the gamma test.

The gamma test was first introduced by Low et al. in 1998 as a single metric that combined features of both dose difference and DTA, while performing robustly in the regions where those are prone to failure. Conceptually, gamma is very similar to dose difference and DTA, but combines them into an abstract metric resembling a distance (Eq. 1). In this way both dose difference and DTA are taken into account for every point compared (rather than either-or as previously discussed).

Eq. 1

Eq. 2

In the above equations I have used somewhat different notation than Low et al. in an attempt to make things slightly clearer.

If we wish to compare two dose distributions, e.g. a measured versus a calculated distribution, we will have a dose, D_a(r_a), in the first distribution at point r_a, and a dose, D_b(r_b), at the corresponding point r_b in the second distribution. The DTA condition is fulfilled when D_a(r_a) = D_b(r_b+r), where r is an arbitrary point a distance |r| away from r_b. This condition defines an isodose contour in distribution b around point r_b. Away from this contour the DTA, d_DTA, is undefined. DTA is used with a threshold passing value, δ_DTA, e.g. 3mm. A DTA smaller than the threshold is considered passing for a simple DTA test. For gamma, δ_DTA is used to normalize the DTA value, such that a normal “passing” value would then be unity.

Dose difference is simply the difference of the two doses at the corresponding points: |D_a(r_a) = D_b(r_b)|. As with DTA, a pass/fail threshold, δ_DD, is used in the simple dose difference test, but is used to normalize the result in the gamma equation, such that the normal "passing" value would be unity.

We now have two components: normalized DTA and normalized dose difference. By squaring these values, adding, and taking the square root, we have a distance-like metric, Γ, shown in Eq. 1. Because DTA is only defined for values of r, such that D_a(r_a) = D_b(r_b+r), Γ is only defined when that condition is met (geometrically located along the DTA isodose contour).

Finally, the actual gamma index, γ, is determined by finding the minimum value of Γ by varying r. This essentially means traveling along the isodose contour and finding the point at which DTA is smallest.

The convention is for passing γ to be ≤ 1 and failing to be > 1. You will notice that a point yielding normalized DTA = 1 and normalized dose difference = 1 would now fail, since the corresponding γ would be √2.

What γ provides is a single value to evaluate, versus using separate tests and then considering both. As with DTA, γ presents challenges in efficient implementation (clearly Eq.'s 1 and 2 are not hand solvable).

Your comments (especially corrections) are appreciated.

Roy

Further reading:

• D. A. Low, W. B. Harms, S. Mutic, and J. A. Purdy, A technique for the quantitative evaluation of dose distributions, Med. Phys. 25, 656 (1998); http://dx.doi.org/10.1118/1.598248