Alev Erdi

Many patients with non-small cell lung cancer (NSCLC) receive external beam radiation therapy as part of their treatment. Three-dimensional conformal radiation therapy (3DCRT) commonly uses computed tomography (CT) to accurately delineate the target lesion and normal tissues. Clinical studies, however, indicate that positron emission tomography (PET) has higher sensitivity than CT in detecting and staging of mediastinal metastases. Imaging with fluoro-2-deoxyglucose (FDG) PET in conjunction with CT, therefore, can improve the accuracy of lesion definition. In this pilot study, we investigated the potential benefits of incorporating PET data into the conventional treatment planning of NSCLC. Case-by-case, we prospectively analyzed planning target volume (PTV) and lung toxicity changes for a cohort of patients. We have included 11 patients in this study. They were immobilized in the treatment position and CT simulation was performed. Following CT simulation, PET scanning was performed in the treatment position using the same body cast that was produced for CT simulation and treatment. The PTV, along with the gross target volume (GTV) and normal organs, was first delineated using the CT data set. The CT and PET transmission images were then registered in the treatment planning system using either manual or automated methods, leading to consequent registration of the CT and emission images. The PTV was then modified using the registered PET emission images. The modified PTV is seen simultaneously on both CT and PET images, allowing the physician to define the PTV utilizing the information from both data sets. Dose-volume histograms (DVHs) for lesion and normal organs were generated using both CT-based and PET+CT-based treatment plans. For all patients, there was a change in PTV outline based on CT images versus CT/PET fused images. In seven out of 11 cases, we found an increase in PTV volume (average increase of 19%) to incorporate distant nodal disease. Among these patients, the highest normal-tissue complication probability (NTCP) for lung was 22% with combined PET/CT plan and 21% with CT-only plan. In other four patients PTV was decreased an average of 18%. The reduction of PTV in two of these patients was due to excluding atelectasis and trimming the target volume to avoid delivering higher radiation doses to nearby spinal cord or heart. The incorporation of PET data improves definition of the primary lesion by including positive lymph nodes into the PTV. Thus, the PET data reduces the likelihood of geographic misses and hopefully improves the chance of achieving local control.

We investigated the use of MI to register images of the pelvis and thorax regions which is a complex problem compared to the head since changes occur in soft tissue while the bony anatomy stays stable. We focused on the bony anatomy eliminating the soft tissue data by applying the MI for bone intensities. Instead of linear binning the whole spectrum of CT intensities, we bin the intensities chosen by the user as corresponding to the bone. We truncated the data spatially by choosing a region, because some bony anatomy might move from scan to scan relative to the stable parts i.e. ribs in the lung region might move with breathing or legs in the pelvis. We compare the effects of using our intensity-dependent- regional MI to the original MI for 9 pairs of CT-CT pelvis, 3 pairs of CT-CT lung and 5 pairs of CT-PET patient studies. With the original algorithm, the root-mean-square registration error can be as high 2 cm for CT-CT. The registration error with the intensity-dependent-regional...

In radionuclide therapy, absorbed dose is calculated by convolution of a three-dimensional activity matrix with a three-dimensional dose point kernel. A technique employing the fast Hartley Transform (FHT) has been developed to perform this calculation. An important part of that development was the indexing scheme for 3D data. The results of this new FHT convolution technique were compared to direct convolution. A cube was convolved with itself by these two techniques. The results differed by less than 2 percent. In an effort to show the practical applicability of 3D convolution, a three-dimensional activity matrix from a I-131-labeled 16.88 monoclonal antibody patient was convolved with beta and photon dose point kernels using direct convolution. Isodose contours were then generated from the calculated absorbed dose matrix and overlaid on a CT image of the patient

A study was performed to correlate activity quantitation derived from external imaging with surgical tumor specimens in patients who received radiolabeled monoclonal antibody. Patients were given I-131 labeled 16.88 human antibody and scanned 3-5 times by planar and/or single photon emission computed tomography imaging methods to acquire time-dependent activity data in tumor and normal tissues. A method also was developed to assess the heterogeneous activity distributions in tumor samples. Postsurgical tumor and normal tissue samples were subdivided into volume elements (voxels) of 0.5 cm x 0.5 cm x 0.05 cm thick, which were used to verify the activity quantitation computed by the conjugate view method and to appraise the heterogeneity of radiolabeled antibody uptake. Through the use of the measured voxel activities, along with the time-dependent activity curves available for the entire tumor specimen derived from imaging, the cumulated activity and absorbed dose for each voxel were uniquely determined. The calculated total absorbed dose values were color-coded as isodose curves and overlaid on a correlated computed tomographic image. In two patients, activity quantitation derived from external imaging correlated with surgical tumor resection specimens within +/- 11%. The tumor-absorbed dose heterogeneity ratio was found to be as high as 10:1, with an average tumor to whole body absorbed dose ratio of 4:1. The mapping of activity with a histologic overlay showed a good correlation among activity uptake, the presence of tumor, and antigen expression on a microscopic scale. The resultant isodose curves overlaid on correlative computed tomographic scans represent the first images obtained with actual radiolabeled antibody biodistribution data in patients.

The use of computed tomography (CT) or magnetic resonance (MR) to overlay or register uptake patterns displayed by single-photon emission computed tomography (SPECT) with specific underlying anatomy has the potential to improve image interpretation and decrease diagnostic reading errors. The authors have developed a method that will allow the selection of a region of interest on MR or CT images that correlates with SPECT antibody images from the same patient. This method was validated first in phantom studies and subsequently was used on three patients with suspected colorectal carcinoma. Two patients were injected with the technetium-99m-labeled 88BV59 immunoglobulin G human antibody, and the third patient was injected with the iodine-131-labeled 16.88 immunoglobulin M human antibody. CT or MR scans were obtained before antibody infusion, and subsequent SPECT scans were obtained on the first or fourth day after infusion. A customized body cast with landmarks was used for each patient during the CT, MR, and SPECT scans to match slice positions for all scanning modalities. Corresponding fiducial landmarks were identified on axial images. A computer graphics program was written to match and overlay corresponding landmarks for each imaging modality. The image registration accuracy was measured by comparing fiducial marker separations (center to center) on the registered scans. This separation uncertainty was 1-2 mm for CT-MR and 3-4 mm for CT-SPECT phantom studies. For patient studies, the fiducial alignment uncertainty was 3-4 mm for axial CT-SPECT and MR-SPECT images, and 6-8 mm for sagittal CT-SPECT and MR-SPECT images. The accuracy of the anatomic alignment of the patient and image registration system was +/- 1 cm in the medial-lateral axis and +/- 2 cm in the cranial-caudal direction. This type of image analysis may resolve uncertainties with the anatomic correlation of SPECT images that otherwise may be regarded as questionable when SPECT is used alone for radioimmunodiagnosis.

A median filtered pyramidal multiresolution (MFPM) image segmentation method for detecting and delineating compact objects was applied to single-photon emission computed tomography (SPECT) images. These SPECT images were obtained by scanning spheres from 1 to 54 ml in size and from 50% to 100% contrast settings. The algorithm performed accurately for large sphere (20 and 54 ml) and high contrast (90% and 100%) cases. As the size and contrast decrease, the accuracy of the method also decreases. Comparison of the MFPM method with adaptive thresholding with edge-preserving smoothing (ATEPS) indicated superior performance of the MFPM method

ABSTRACT We investigated the use of MI to register images of the pelvis and thorax regions which is a complex problem compared to the head since changes occur in soft tissue while the bony anatomy stays stable. We focused on the bony anatomy eliminating the soft tissue data by applying the MI for bone intensities. Instead of linear binning the whole spectrum of CT intensities, we bin the intensities chosen by the user as corresponding to the bone. We truncated the data spatially by choosing a region, because some bony anatomy might move from scan to scan relative to the stable parts i.e. ribs in the lung region might move with breathing or legs in the pelvis. We compare the effects of using our intensity-dependent- regional MI to the original MI for 9 pairs of CT-CT pelvis, 3 pairs of CT-CT lung and 5 pairs of CT-PET patient studies. With the original algorithm, the root-mean-square registration error can be as high 2 cm for CT-CT. The registration error with the intensity-dependent-regional algorithm, however, was on the average 2 mm for CT-CT pelvic and 4 mm for CT-CT lung studies. Using just the bone intensities and a specific region, we have a smaller sample size, which decreased our calculation time up to 8 times to less than 15 seconds. For CT-PET studies the average registration error is reduced from 3.2 cm to 0.5 cm.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

To foster the success of clinical trials in radio-immunotherapy (RIT), one needs to determine (i) the quantity and spatial distribution of the administered radionuclide carrier in the patient over time, (ii) the absorbed dose in the tumour sites and critical organs based on this distribution and (iii) the volume of tumour mass(es) and normal organs from computerized tomography or magnetic resonance imaging and appropriately correlated with nuclear medicine imaging techniques (such as planar, single-photon emission computerized tomography or positron-emission tomography). Treatment planning for RIT has become an important tool in predicting the relative benefit of therapy based on individualized dosimetry as derived from diagnostic, pre-therapy administration of the radiolabelled antibody. This allows the investigator to pre-select those patients who have 'favorable' dosimetry characteristics (high time-averaged target: non-target ratios) so that the chances for treatment success may be more accurately quantified before placing the patient at risk for treatment-related organ toxicities. The future prospects for RIT treatment planning may yield a more accurate correlation of response and critical organ toxicity with computed absorbed dose, and the compilation of dose-volume histogram information for tumour(s) and normal organ(s) such that computing tumour control probabilities and normal tissue complication probabilities becomes possible for heterogeneous distributions of the radiolabelled antibody. Additionally, radiobiological consequences of depositing absorbed doses from exponentially decaying sources must be factored into the interpretation when trying to compute the effects of standard external beam isodose display patterns combined with those associated with RIT.

Effective radioimmunotherapy may depend on a priori knowledge of the radiation absorbed dose distribution obtained by trace imaging activities administered to a patient before treatment. A new, fast, and effective treatment planning approach is developed to deal with a heterogeneous activity distribution. Calculation of the three-dimensional absorbed dose distribution requires convolution of a cumulated activity distribution matrix with a point-source kernel; both are represented by large matrices (64 x 64 x 64). To reduce the computation time required for these calculations, an implementation of convolution using three-dimensional (3-D) fast Hartley transform (FHT) is realized. Using the 3-D FHT convolution, absorbed dose calculation time was reduced over 1000 times. With this system, fast and accurate absorbed dose calculations are possible in radioimmunotherapy. This approach was validated in simple geometries and then was used to calculate the absorbed dose distribution for a patient's tumor and a bone marrow sample.