DMH-Based Plan Evaluation and Inverse Optimization in Radiotherapy

Cancer patients continue to represent a challenging disease population, which faces rather
poor prognosis with current treatment planning and delivery practices. Venues for a potential
dose escalation and/or increased healthy tissue sparing, through innovative therapeutic
approaches for those patients, are clearly needed. Current state of the art radiotherapy
treatment planning relies on the dose-volume-histogram (DVH) paradigm, where doses to
fractional (most often) or absolute volumes of anatomical structures are employed in both
optimization and plan evaluation process. It has been argued however, that the effects of
delivered dose seem to be more closely related to healthy tissue toxicity (and thereby to
clinical outcomes) when dose-mass-histograms (DMHs) are considered in treatment plan
evaluation.

The investigators propose the incorporation of mass and density information explicitly into
the cost functions of the inverse optimization process, thereby shifting from DVH to DMH
treatment planning paradigm. This novel DMH-based intensity modulated radiotherapy (IMRT)
optimization aims in minimization of radiation doses to a certain mass, rather than a volume,
of healthy tissue. The investigators' working hypothesis is that DMH- optimization will
reduce doses to healthy tissue substantially. In certain cases, with extensive, difficult to
treat disease, lower doses to healthy tissue can be used for isotoxic dose escalation, which
may result in an increase in estimated loco-regional tumor control probability.

To test the study hypothesis, the investigators will pursue the following specific aims:

- (1) Develop the theoretical and computational framework of the DMH-based IMRT
optimization. This framework will incorporate 3D and 4D IMRT as well as 3D volumetric
modulated arc (VMAT) planning for different anatomical sites.

- (2) Investigate different parametric forms for DMH-optimization functions. The ultimate
goal would be the simultaneous minimization of healthy tissue doses and/or escalation of
therapeutic doses, without violating the established dosimetric tolerances for healthy
anatomical structures.

- (3) Practical implementation and application of this novel optimization paradigm, where
virtual clinical trials for cohorts of lung, head-and-neck, and prostate cancer cases
will be performed.

Statistical significance of the DMH-optimization dosimetric improvements over standard of
care DVH-optimization will be quantified. Prospective 3D and 4D CT data collection will be
used to study the interactions between tumor time-trending changes and DMH-based optimization
results. 4D CT data will also be used to investigate and quantify the correlation between
DMH-based end points and the loss of pulmonary function during and after radiotherapy
treatment. The deliverability (with the existing radiotherapy treatment equipment) of the
investigators' 3D VMAT and 3D/4D IMRT plans will be experimentally verified, thereby paving
the road for initiation of clinical trials.

Inclusion Criteria:

- Patients must have histologically confirmed head-and-neck, lung, or prostate tumors.

- Patients who will be treated with radiation therapy or concurrent chemoradiation
therapy.

- Gross Tumor Volume (GTV) or resection cavity must be visible on CT such that it can be
delineated as a target for radiotherapy.

- Patients who are able to understand the investigational nature of this study and agree
to sign a written informed consent document.

Exclusion Criteria:

- Pregnant or nursing women will not participate. Women of reproductive potential must
be offered a pre-treatment pregnancy test and informed of the need to practice an
effective contraceptive method during the therapy.

- Patients younger than 18 years.

- Patients whose size and weight would not allow CT scanning.

- No vulnerable populations (fetuses, pregnant women, children, prisoners) will be
included in this study.