Clinical utility of a patient-specific algorithm for simulating intracerebral drug infusions.

Convection-enhanced delivery (CED) is a novel drug delivery technique that uses positive infusion pressure to deliver therapeutic agents directly into the interstitial spaces of the brain. Despite the promise of CED, clinical trials have demonstrated that target-tissue anatomy and patient-specific physiology play a major role in drug distribution using this technique. In this study, we retrospectively tested the ability of a software algorithm using MR diffusion tensor imaging to predict patient-specific drug distributions by CED. A tumor-targeted cytotoxin, cintredekin besudotox (interleukin 13-PE38QQR), was coinfused with iodine 123-labeled human serum albumin (123I-HSA), in patients with recurrent malignant gliomas. The spatial distribution of 123I-HSA was then compared to a drug distribution simulation provided by the software algorithm. The algorithm had a high sensitivity (71.4%) and specificity (100%) for identifying the high proportion (7 of 14) of catheter trajectories that failed to deliver drug into the desired anatomical region (p = 0.021). This usually occurred when catheter trajectories crossed deep sulci, resulting in leak of the infusate into the subarachnoid cerebrospinal fluid space. The mean concordance of the volume of distribution at the 50% isodose level between the actual 123I-HSA distribution and simulation was 65.75% (95% confidence interval [CI], 52.0%-79.5%), and the mean maximal inplane deviation was less than 8.5 mm (95% CI, 4.0-13.0 mm). The use of this simulation algorithm was considered clinically useful in 84.6% of catheters. Routine use of this algorithm, and its further developments, should improve prospective selection of catheter trajectories, and thereby improve the efficacy of drugs delivered by this promising technique.

Convection-enhanced delivery of therapeutics for brain disease, and its optimization.

Convection-enhanced delivery (CED) is the continuous injection under positive pressure of a fluid containing a therapeutic agent. This technique was proposed and introduced by researchers from the US National Institutes of Health (NIH) by the early 1990s to deliver drugs that would otherwise not cross the blood-brain barrier into the parenchyma and that would be too large to diffuse effectively over the required distances were they simply deposited into the tissue. Despite the many years that have elapsed, this technique remains experimental because of both the absence of approved drugs for intraparenchymal delivery and the difficulty of guaranteed delivery to delineated regions of the brain. During the first decade after the NIH researchers founded this analytical model of drug distribution, the results of several computer simulations that had been conducted according to more realistic assumptions were also published, revealing encouraging results. In the late 1990s, one of the authors of the present paper proposed the development of a computer model that would predict the distribution specific to a particular patient (brain) based on obtainable data from radiological images. Several key developments in imaging technology and, in particular, the relationships between image-obtained quantities and other parameters that enter models of the CED process have been required to implement this model. Note that delivery devices need further development. In the present paper we review key features of CED as well as modeling of the procedure and indulge in informed speculation on optimizing the direct delivery of therapeutic agents into brain tissue.