ANALYSIS OF PET STUDIES PET Basics Course 2006 Turku PET Centre Vesa Oikonen

Analysis of PET studies 1.Instructions in quality system 2.Retrieving data for analysis 3.Steps of analysis 4.Quantification in PET analysis 5.Models 6.Analysis tools in intranet and WWW 7.Imaging, modelling and IT in intranet

Quality documents: SOP, MET, DAN MET: analysis methods in general terms DAN: more detailed data analysis instructions

Quality data analysis Check when starting new study project: –the current analysis method –most recent software releases –never follow old ”recipes”! Even SOP and MET can be outdated!

Quality data analysis Follow a certain analysis chain (SOP, MET, DAN) If new software version is released during the study, recalculate all (or nothing) Record what documents you follow and software versions you use in electronic format Document all exceptions Record final versions of documents and analysis results in database (PETO)

PETO Requesting and scheduling studies Retrieving data for analysis Recording documentation Storing final analysis results

PETO

Steps of analysis Results Parametric Image + Blood Data Model calculations Drawing ROI SPM Dynamic PET Image Regional TACs + MRI + Blood Data Drawing ROI

Collection of data and the specific method of analysis depends on the studied question Sometimes the visual inspection of single image (static imaging) is sufficient, e.g. in tumour detection Detailed analysis requires dynamic imaging, often blood sampling, and elaborate modelling The more advanced statistical methods require parametric images

Static image One scan Resulting image planes (example):

Dynamic image Femoral region [ 15 O]O 2 bolus Example of TACs

TACs tell us about the tissue TAC = time-activity (concentration) curve TAC of tracer concentration in arterial blood TAC of concentration in tissue measured by PET scanner Tissue characteristics: Perfusion Endothelial permeability Vascular volume fraction Transport across cell membranes Specific binding to receptors Non-specific binding Enzyme activity

Parametric image Dynamic information is converted to functional information with dedicated software –Not a series of scans (smaller file size) –image voxel value = the value of the studied physiological parameter (perfusion, glucose consumption, receptor density) More sophisticated analyses possible –requires careful evaluation of alternative models before choosing the right model

Regions of interest = ROI Anatomical regions –detection requires MRI –drawn into the MR image by hand –also automatic software are developed Aim: calculate the average of the studied physiological parameter in a specific anatomical region E. g. quantification of dopamine receptor densities in frontal cortex of brain

PET is a quantitative tool Radioactivity concentration (tissue or plasma) can be easily converted to drug concentration: drug concentration = Drug concentration is used to measure tissue function in vivo: perfusion, glucose consumption, receptor density, enzyme activity, etc.

Calibration Tissue and reference radioactivity must be comparable PET, well counter for plasma samples, and dose calibrator are all cross-calibrated Calibration is done by PET physicist

Physical decay In PET, drugs are labelled with positron emitting isotopes with very short half-lives During the PET study, isotope label is decaying substantially, compared to the drug; specific radioactivity is decreasing To correct this, all measured radioactivity are corrected to the time of injection

How to study the characteristics of tissue? Alternatives for model calculation: –Compartment models –Spectral analysis –Ratio –MTGA (Logan or Gjedde-Patlak plot) –FUR –SUV Comparison table

Arterial FDG Venous FDG Interstitial FDG Intracellular FDG Intracellular FDG-6-P

Compartmental model for [ 18 F]FDG in muscle

Multiple-time graphical analysis (MTGA) Independent of compartments Data is transformed to a linear plot Macro-parameter estimated directly as the slope of linear phase of plot Reversible models: Logan analysis (DV, DVR) Irreversible models: Gjedde-Patlak analysis (K i )

Logan analysis with plasma input Distribution volume = Slope of the Logan plot Distribution volume ratio = Ratio of slopes of the ROI and reference region Logan J. Graphical analysis of PET data applied to reversible and irreversible tracers. Nucl Med Biol 2000;27:

Gjedde-Patlak analysis with plasma input Net influx rate Ki = Slope of the Patlak plot Unit of Ki = ml plasma * min -1 * ml tissue -1 Patlak CS, Blasberg RG. Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. Generalizations. J Cereb Blood Flow Metab 1985;5:

Standardized uptake value SUV Simple, semi-quantitative measure (g/ml) Regional radioactivity concentration (kBq/ml) normalized by injected dose (GBq) and subject weight (kg) Average SUV in entire body = body density Blood sampling not needed Example: measuring amino acid methionine uptake in tumour studies

Using analysis software Can be used on any PC with Windows XP in hospital network and/or PET intranet Downloadable in WWW Analysis instructions in WWW P:\bin\windows

Requesting software New software Feature requests Bug reports Project follow-up Software documents a/ or ask IT or modelling group members

Imaging and modelling method development and validation Instrumentation Image processing Modelling Project follow-up Documentation or ask imaging group members