Gait and behavior in an IL1β-mediated model of rat knee arthritis and effects of an IL1 antagonist.

Interleukin-1 beta (IL1β) is a proinflammatory cytokine that mediates arthritic pathologies. Our objectives were to evaluate pain and limb dysfunction resulting from IL1β over-expression in the rat knee and to investigate the ability of local IL1 receptor antagonist (IL1Ra) delivery to reverse-associated pathology. IL1β over-expression was induced in the right knees of 30 Wistar rats via intra-articular injection of rat fibroblasts retrovirally infected with human IL1β cDNA. A subset of animals received a 30 µl intra-articular injection of saline or human IL1Ra on day 1 after cell delivery (0.65 µg/µl hIL1Ra, n = 7 per group). Joint swelling, gait, and sensitivity were investigated over 1 week. On day 8, animals were sacrificed and joints were collected for histological evaluation. Joint inflammation and elevated levels of endogenous IL1β were observed in knees receiving IL1β-infected fibroblasts. Asymmetric gaits favoring the affected limb and heightened mechanical sensitivity (allodynia) reflected a unilateral pathology. Histopathology revealed cartilage loss on the femoral groove and condyle of affected joints. Intra-articular IL1Ra injection failed to restore gait and sensitivity to preoperative levels and did not reduce cartilage degeneration observed in histopathology. Joint swelling and degeneration subsequent to IL1β over-expression is associated limb hypersensitivity and gait compensation. Intra-articular IL1Ra delivery did not result in marked improvement for this model; this may be driven by rapid clearance of administered IL1Ra from the joint space. These results motivate work to further investigate the behavioral consequences of monoarticular arthritis and sustained release drug delivery strategies for the joint space.

Development and Testing of An Automatic Lung IMRT Planning Algorithm

Knowledge-based radiation treatment is an emerging concept in radiotherapy. It

mainly refers to the technique that can guide or automate treatment planning in

clinic by learning from prior knowledge. Dierent models are developed to realize

it, one of which is proposed by Yuan et al. at Duke for lung IMRT planning. This

model can automatically determine both beam conguration and optimization ob-

jectives with non-coplanar beams based on patient-specic anatomical information.

Although plans automatically generated by this model demonstrate equivalent or

better dosimetric quality compared to clinical approved plans, its validity and gener-

ality are limited due to the empirical assignment to a coecient called angle spread

constraint dened in the beam eciency index used for beam ranking. To eliminate

these limitations, a systematic study on this coecient is needed to acquire evidences

for its optimal value.

To achieve this purpose, eleven lung cancer patients with complex tumor shape

with non-coplanar beams adopted in clinical approved plans were retrospectively

studied in the frame of the automatic lung IMRT treatment algorithm. The primary

and boost plans used in three patients were treated as dierent cases due to the

dierent target size and shape. A total of 14 lung cases, thus, were re-planned using

the knowledge-based automatic lung IMRT planning algorithm by varying angle

spread constraint from 0 to 1 with increment of 0.2. A modied beam angle eciency

index used for navigate the beam selection was adopted. Great eorts were made to assure the quality of plans associated to every angle spread constraint as good

as possible. Important dosimetric parameters for PTV and OARs, quantitatively

re

ecting the plan quality, were extracted from the DVHs and analyzed as a function

of angle spread constraint for each case. Comparisons of these parameters between

clinical plans and model-based plans were evaluated by two-sampled Students t-tests,

and regression analysis on a composite index built on the percentage errors between

dosimetric parameters in the model-based plans and those in the clinical plans as a

function of angle spread constraint was performed.

Results show that model-based plans generally have equivalent or better quality

than clinical approved plans, qualitatively and quantitatively. All dosimetric param-

eters except those for lungs in the automatically generated plans are statistically

better or comparable to those in the clinical plans. On average, more than 15% re-

duction on conformity index and homogeneity index for PTV and V40, V60 for heart

while an 8% and 3% increase on V5, V20 for lungs, respectively, are observed. The

intra-plan comparison among model-based plans demonstrates that plan quality does

not change much with angle spread constraint larger than 0.4. Further examination

on the variation curve of the composite index as a function of angle spread constraint

shows that 0.6 is the optimal value that can result in statistically the best achievable

plans.