Biomedical Engineering Reference
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drug trials that changes in glycolytic rate precede effects on the tumor volume. For example, in
patients suffering from gastrointestinal stromal tumors treated with imatinib glucose utilization was
signii cantly reduced within 24 h after treatment onset, while there was no effect on tumor volume
for several months, indicating that glucose utilization rate predicts therapy response.
A common technique to assess tumor angiogenesis is the so-called dynamic contrast-enhanced
(DCE) MRI methods, which exploits the fact that newly formed immature vessels are characterized
by increased vascular permeability. DCE-MRI measures the leakage of low molecular weight
contrast agents such as GdDTPA (Magnevist ® ) or GdDOTA (Dotarem ® ) into the extracellular
space. This method is currently evaluated as biomarker for evaluating the efi cacy of antiangiogenic
therapy. Inhibition of VEGF receptor signaling should be rel ected by decreased vascular permeability
and potentially also reduced tumor blood volume, as demonstrated for the VEGF tyrosine kinase
inhibitor vatalanib for several tumor models in mice. Drug effects could be detected within 48 h
following onset of treatment. Clinical studies in patients with liver metastases yielded corresponding
results indicating that, in fact, vascular permeability measures may serve as a biomarker of efi cacy.
The method has been used for translational studies with a number of compounds.
Currently used imaging biomarkers are based on structural (e.g., response evaluation criteria
for solid tumors [RECIST] for tumors, infarct volume for stroke, and lesion load for MS) or
physiological and metabolic readouts (e.g., DCE-MRI and glucose utilization rates for tumors). A
next generation of (molecular) imaging approaches will provide specii c mechanistic information
tightly linked to the therapeutic pharmacological principle; a term coined in this regard is thera-
nostics, the merger of therapeutic and diagnostics.
7.4 DOES IMAGING ADD VALUE TO THE DRUG DISCOVERY PROCESS?
What is the added value of using resource-intense imaging methods in DDD? The obvious expec-
tation is that the use of noninvasive analytical techniques facilitates the translation of the thera-
peutic concept from preclinical to clinical development and thus might contribute to shortening
of DDD times. Convincing as a concept, there is little evidence today that the use of imaging
has greatly impacted development. This is likely to change in the future as all major stakehold-
ers have recognized the importance of speeding up DDD as outline in the FDA Critical Path
Initiative. Biomarkers and eventually surrogate markers will allow assessing treatment efi cacy
and safety aspects signii cantly earlier than classical clinical endpoint measures. Noninvasive
imaging will be a key enabling technology in that context as illustrated in the previous section.
It is important to realize that the purpose of translational imaging applications in DDD are not
large-scale multicenter phase III trials, which pose high demands on standardization of imaging
protocols and potentially would be very expensive. Translation imaging studies serve the purpose
of establishing pharmacological proof-of-concept in a selected patient population in a small, well-
controlled clinical study—critical information for decision makers before entering large-scale
clinical evaluation.
Apart from these translational aspects imaging readouts have turned out to provide essential
information to the drug developer. The possibility to derive morphological, physiological, met-
abolic, cellular, and molecular information in a noninvasive manner from an intact organism is
highly relevant, in particular when studying chronic degenerative diseases that require longitudinal
evaluation. It is therefore not surprising that the majority of imaging applications refers to disease
phenotyping; in view of the increasing number of genetically engineered mouse lines available, this
application will certainly become even more important. The information gathered during disease
phenotyping should be used to stratify treatment groups: prior to therapy administration, patients
or animals can be classii ed into “homogenous” treatment groups, which should translate into data
with better statistical relevance.
Imaging is inherently quantitative although translation from primary imaging parameters to
biomedical information is not straightforward and constitutes a major challenge for the imaging
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