Biomedical subjects

Ira J Kalet

Publications and source records attributed to Ira J Kalet.

4 recordsLinked to original sources

PubMed2005

Qualitative pharmacokinetic modeling of drugs.

We hypothesize that a representation of drug-drug interactions (DDIs) based on physiologic, pharmacokinetic (PK) and pharmacodynamic (PD) mechanisms will provide more accurate and useful information to clinicians than current approaches that simply tabulate and index pairwise interactions of drugs. This paper explores the strengths, weaknesses, and difficulties of modeling drug mechanisms and reports on our initial work designing and implementing a drug KB based on qualitative pharmacokinetic mechanisms.

Dose-Response Relationship, Drug↗

PubMed2003

A declarative implementation of the DICOM-3 network protocol.

We describe a new design for programs using the Digital Imaging and Communications in Medicine (DICOM) protocol, which we have implemented in a DICOM image storage server and a radiation treatment plan transfer facility for our locally developed radiation treatment planning system, Prism. This design is declarative, representing DICOM as a language for describing messages and sequencing of messages. The coding involved implementing an interpreter for this language. The DICOM protocol specifies messages, message formats, and sequencing. In our design, the specification translates almost directly into computer-readable declarative expressions that closely resemble the relevant tabulated DICOM specifications. The resulting programs are small, simple, and extensible, because most of the details of the DICOM protocol are not coded in the procedural control statements but are in the expressions and state table that the interpreter uses to perform all its functions. This approach provides a way to validate the consistency of a specification and the correctness of the implementation. The same method can be generalized to other such protocols. It may also be used to assist the design of new protocols.

Algorithms↗

PubMed2002

A rule-based model for local and regional tumor spread.

Prediction of microscopic spread of tumor cells is becoming critically important in the decision making process in planning radiation therapy for cancer. Until recently, radiation treatment of head and neck cancer has been conservative, treating large regions to insure eradication of disease. However, if it is known that regional spread is confined, a more focused treatment can be considered, with the payoff of reducing or eliminating morbidity due to irradiating healthy tissue in the vicinity of node groups. Knowledge about the occurrence of micrometastases comes mainly from pathology reports in connection with surgery. As the data accrue, it will be possible and necessary to represent this knowledge in a symbolic computational model. Our work reports on the feasibility of modeling this knowledge using published data.

Head and Neck Neoplasms↗

PubMed2002

Head and neck lymph node region delineation with 3-D CT image registration.

The success of radiation therapy depends critically on accurately delineating the target volume, which is the region of known or suspected disease in a patient. Methods that can compute a contour set defining a target volume on a set of patient images will contribute greatly to the success of radiation therapy and dramatically reduce the workload of radiation oncologists, who currently draw the target by hand on the images using simple computer drawing tools. The most challenging part of this process is to estimate where there is microscopic spread of disease. We are developing methods for automatically selecting and adapting standardized regions of tumor spread based on the location of lymph nodes in a standard or reference case, together with image registration techniques. The best available image registration techniques (deformable transformations computed using "mutual information" optimization) appear promising but will need to be supplemented by anatomic knowledge-based methods to achieve a clinically acceptable match.

Algorithms↗