Viability of Non-Coplanar VMAT for Liver SBRT as Compared to Coplanar VMAT and Beam Orientation Optimized 4π IMRT.

PurposeThe 4π static non-coplanar radiotherapy delivery technique has demonstrated better normal tissue sparing and dose conformity than the clinically used volumetric modulated arc therapy (VMAT). It is unclear whether this is a fundamental limitation of VMAT delivery or the coplanar nature of its typical clinical plans. The dosimetry and the limits of normal tissue toxicity constrained dose escalation of coplanar VMAT, non-coplanar VMAT and 4π radiotherapy are quantified in this study.Methods and materialsClinical stereotactic body radiation therapy plans for 20 liver patients receiving 30-60 Gy using coplanar VMAT (cVMAT) were re-planned using 3-4 partial non-coplanar arcs (nVMAT) and 4π with 20 intensity-modulated non-coplanar fields. The conformity number (CN), homogeneity index (HI), 50% dose spillage volume (R50), normal liver volume receiving >15 Gy (VL>15), dose to organs at risk (OARs), and tumor control probability (TCP) were compared for all three treatment plans. The maximum tolerable dose (MTD) yielding a normal liver normal tissue control probability (NTCP) below 1%, 5%, and 10% was calculated with the Lyman-Kutcher-Burman model for each plan, as well as the resulting survival fractions at one, two, three, and four years.ResultsCompared to cVMAT, the nVMAT and 4π plans reduced VL>15 by an average of 5 cm3 and 80 cm3, respectively. 4π reduced the 50% dose spillage volume by ~23% compared to both VMAT plans, and either significantly decreased or maintained OAR doses. The 4π MTDs and survival fractions were significantly higher than both cVMAT and nVMAT (p<0.05) for all normal liver NTCP limits used in this study.ConclusionsThe 4π technique provides significantly better OAR sparing than both cVMAT and vMAT and enables more clinically relevant dose escalation for tumor local control. Therefore, despite the current accessibility of nVMAT, it is not a viable alternative to 4π for liver SBRT

Radiation Therapy Medical Physics Review – Delivery, Interactions, Safety, Feasibility, and Head to Head Comparisons of the Leading Radiation Therapy Techniques

Radiation therapy uses high energy radiation to kill cancer cells. Radiation therapy for cancer treatment can take the form of photon therapy (using x-rays and gamma rays), or charged particle therapy including proton therapy and electron therapy. Within these categories, numerous methods of delivery have been developed. For example, a certain type of radiation can be administered by a machine outside of the body, called external-beam radiation therapy, or by a “seed” placed inside of the body near cancer cells, called internal radiation therapy or brachytherapy. Approximately half of all cancer patients receive radiation therapy, and the form of radiation treatment depends on the type of tumor, location of the tumor, available resources, and characteristics of the individual receiving treatment. In the current paper, we discuss and review the various forms of radiation therapy, the physics behind these treatments, the effectiveness of each treatment type compared with the others, the latest research on radiation therapy treatment, and future research directions. We found that proton therapy is the most promising and effective form of radiation therapy, with photon methods such as intensity modulated radiation therapy, 3D-conformal radiation therapy, image guided radiation therapy, and volumetric modulated radiation therapy also showing very good comparative performance

Intensity modulated radiation therapy and arc therapy: validation and evolution as applied to tumours of the head and neck, abdominal and pelvic regions

Intensiteitsgemoduleerde radiotherapie (IMRT) laat een betere controle over de dosisdistributie (DD) toe dan meer conventionele bestralingstechnieken. Zo is het met IMRT mogelijk om concave DDs te bereiken en om de risico-organen conformeel uit te sparen. IMRT werd in het UZG klinisch toegepast voor een hele waaier van tumorlocalisaties. De toepassing van IMRT voor de bestraling van hoofd- en halstumoren (HHT) vormt het onderwerp van het eerste deel van deze thesis. De planningsstrategie voor herbestralingen en bestraling van HHT, uitgaande van de keel en de mondholte wordt beschreven, evenals de eerste klinische resultaten hiervan. IMRT voor tumoren van de neus(bij)holten leidt tot minstens even goede lokale controle (LC) en overleving als conventionele bestralingstechnieken, en dit zonder stralingsgeïnduceerde blindheid. IMRT leidt dus tot een gunstiger toxiciteitprofiel maar heeft nog geen bewijs kunnen leveren van een gunstig effect op LC of overleving. De meeste hervallen van HHT worden gezien in het gebied dat tot een hoge dosis bestraald werd, wat erop wijst dat deze “hoge dosis” niet volstaat om alle clonogene tumorcellen uit te schakelen. We startten een studie op, om de mogelijkheid van dosisescalatie op geleide van biologische beeldvorming uit te testen. Naast de toepassing en klinische validatie van IMRT bestond het werk in het kader van deze thesis ook uit de ontwikkeling en het klinisch opstarten van intensiteitgemoduleerde arc therapie (IMAT). IMAT is een rotationele vorm van IMRT (d.w.z. de gantry draait rond tijdens de bestraling), waarbij de modulatie van de intensiteit bereikt wordt door overlappende arcs. IMAT heeft enkele duidelijke voordelen ten opzichte van IMRT in bepaalde situaties. Als het doelvolume concaaf rond een risico-orgaan ligt met een grote diameter, biedt IMAT eigenlijk een oneindig aantal bundelrichtingen aan. Een planningsstrategie voor IMAT werd ontwikkeld, en type-oplossingen voor totaal abdominale bestraling en rectumbestraling werden onderzocht en klinisch toegepast

Modeling Patient-Specific Dose-Function Response for Enhanced Characterization of Personalized Functional Damage

PURPOSE: Functional-guided radiation therapy (RT) plans have the potential to limit damage to normal tissue and reduce toxicity. Although functional imaging modalities have continued to improve, a limited understanding of the functional response to radiation and its application to personalized therapy has hindered clinical implementation. The purpose of this study was to retrospectively model the longitudinal, patient-specific dose-function response in non-small cell lung cancer patients treated with RT to better characterize the expected functional damage in future, unknown patients. METHODS AND MATERIALS: Perfusion single-photon emission computed tomography/computed tomography scans were obtained at baseline (n = 81), midtreatment (n = 74), 3 months post-treatment (n = 51), and 1 year post-treatment (n = 26) and retrospectively analyzed. Patients were treated with conventionally fractionated RT or stereotactic body RT. Normalized perfusion single-photon emission computed tomography voxel intensity was used as a surrogate for local lung function. A patient-specific logistic model was applied to each individual patient's dose-function response to characterize functional reduction at each imaging time point. Patient-specific model parameters were averaged to create a population-level logistic dose-response model. RESULTS: A significant longitudinal decrease in lung function was observed after RT by analyzing the voxelwise change in normalized perfusion intensity. Generated dose-function response models represent the expected voxelwise reduction in function, and the associated uncertainty, for an unknown patient receiving conventionally fractionated RT or stereotactic body RT. Differential treatment responses based on the functional status of the voxel at baseline suggest that initially higher functioning voxels are damaged at a higher rate than lower functioning voxels. CONCLUSIONS: This study modeled the patient-specific dose-function response in patients with non-small cell lung cancer during and after radiation treatment. The generated population-level dose-function response models were derived from individual patient assessment and have the potential to inform functional-guided treatment plans regarding the expected functional lung damage. This type of patient-specific modeling approach can be applied broadly to other functional response analyses to better capture intrapatient dependencies and characterize personalized functional damage