18F-Fluorodeoxyglucose Positron Emission Tomography Parameters can Predict Long-Term Outcome Following Trimodality Treatment for Oesophageal Cancer.

AIMS: 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18FDG-PET/CT) is routinely used for the pre-treatment staging of oesophageal or gastro-oesophageal junction cancers (EGEJC). The aim of this study was to identify objective 18FDG-PET/CT-derived parameters that can aid in predicting the patterns of recurrence and prognostication in patients with EGEJC. PATIENTS AND METHODS: EGEJC patients referred for consideration of preoperative chemoradiation therapy were identified and clinicopathological data were collected. 18FDG-PET/CT imaging data were reviewed and correlated with treatment outcomes. Maximum standardised uptake value (SUVmax), metabolic tumour volume (MTV) and total lesion glycolysis were assessed and association with recurrence-free survival (RFS), locoregional recurrence-free survival (LR-RFS), oesophageal cancer-specific survival (ECSS) and overall survival were evaluated using receiver operating characteristic curves, as well as Cox regression and Kaplan-Meier models. RESULTS: In total, 191 EGEJC patients completed trimodality treatment and 164 with 18FDG-PET/CT data were included in this analysis. At the time of analysis, 15 (9.1%), 70 (42.7%) and two (1.2%) patients were noted to have locoregional, distant and both locoregional and distant metastases, respectively. The median RFS was 30 months (9.6-50.4) and the 5-year RFS was 31.1%. The 5-year overall survival and ECSS were both noted to be 34.8%. Pre-treatment MTV25 > 28.5 cm3 (P = 0.029), MTV40 > 12.4 cm3 (P = 0.018) and MTV50 > 10.2 cm3 (P = 0.005) predicted for worse LR-RFS, ECSS and overall survival for MTV definition of voxels ≥25%, 40% and 50% of SUVmax. CONCLUSION: 18FDG-PET/CT parameters MTV and total lesion glycolysis are useful prognostic tools to predict for LR-RFS, ECSS and overall survival in EGEJC. MTV had the highest accuracy in predicting clinical outcomes. The volume cut-off points we identified for different MTV thresholds predicted outcomes with significant accuracy and may potentially be used for decision making in clinical practice.

Dosimetry study of [I-131] and [I-125]- meta-iodobenz guanidine in a simulating model for neuroblastoma metastasis.

The physical properties of I-131 may be suboptimal for the delivery of therapeutic radiation to bone marrow metastases, which are common in the natural history of neuroblastoma. In vitro and preliminary clinical studies have implied improved efficacy of I-125 relative to I-131 in certain clinical situations, although areas of uncertainty remain regarding intratumoral dosimetry. This prompted our study using human neuroblastoma multicellular spheroids as a model of metastasis. 3D dose calculations were made using voxel-based Medical Internal Radiation Dosimetry (MIRD) and dose-point-kernel (DPK) techniques. Dose distributions for I-131 and I-125 labeled mIBG were calculated for spheroids (metastases) of various sizes from 0.01 cm to 3 cm diameter, and the relative dose delivered to the tumors was compared for the same limiting dose to the bone marrow. Based on the same data, arguments were advanced based upon the principles of tumor control probability (TCP) to emphasize the potential theoretical utility of I-125 over I-131 in specific clinical situations. I-125-mIBG can deliver a higher and more uniform dose to tumors compared to I-131 mIBG without increasing the dose to the bone marrow. Depending on the tumor size and biological half-life, the relative dose to tumors of less than 1 mm diameter can increase several-fold. TCP calculations indicate that tumor control increases with increasing administered activity, and that I-125 is more effective than I-131 for tumor diameters of 0.01 cm or less. This study suggests that I-125-mIBG is dosimetrically superior to I-131-mIBG therapy for small bone marrow metastases from neuroblastoma. It is logical to consider adding I-125-mIBG to I-131-mIBG in multi-modality therapy as these two isotopes could be complementary in terms of their cumulative dosimetry.

Properties of noise in positron emission tomography images reconstructed with filtered-backprojection and row-action maximum likelihood algorithm.

Noise levels observed in positron emission tomography (PET) images complicate their geometric interpretation. Post-processing techniques aimed at noise reduction may be employed to overcome this problem. The detailed characteristics of the noise affecting PET images are, however, often not well known. Typically, it is assumed that overall the noise may be characterized as Gaussian. Other PET-imaging-related studies have been specifically aimed at the reduction of noise represented by a Poisson or mixed Poisson + Gaussian model. The effectiveness of any approach to noise reduction greatly depends on a proper quantification of the characteristics of the noise present. This work examines the statistical properties of noise in PET images acquired with a GEMINI PET/CT scanner. Noise measurements have been performed with a cylindrical phantom injected with (11)C and well mixed to provide a uniform activity distribution. Images were acquired using standard clinical protocols and reconstructed with filtered-backprojection (FBP) and row-action maximum likelihood algorithm (RAMLA). Statistical properties of the acquired data were evaluated and compared to five noise models (Poisson, normal, negative binomial, log-normal, and gamma). Histograms of the experimental data were used to calculate cumulative distribution functions and produce maximum likelihood estimates for the parameters of the model distributions. Results obtained confirm the poor representation of both RAMLA- and FBP-reconstructed PET data by the Poisson distribution. We demonstrate that the noise in RAMLA-reconstructed PET images is very well characterized by gamma distribution followed closely by normal distribution, while FBP produces comparable conformity with both normal and gamma statistics.

A conjugate of gemcitabine with bisphosphonate (Gem/BP) shows potential as a targeted bone-specific therapeutic agent in an animal model of human breast cancer bone metastases.

Bone metastases in advanced breast cancer patients remains a significant treatment challenge. Bisphosphonates are now a routine first line treatment for prevention and treatment of skeletal damage caused by malignancies and, moreover, have shown an ability to transport therapeutic drugs to the bone. Here, we describe the effect of a conjugate between the potent anticancer drug gemcitabine and a bisphosphonate molecule (Gem/BP) in an animal model of breast cancer metastases. We have previously demonstrated the targeting of this compound to bone in normal mice using an analog labeled with the radionuclide 99mTc. Using a bone metastasis model in nude mice produced by intracardiac injection of the human breast cancer cell line MDA-MB-231BO, we examined the effect of Gem/BP and gemcitabine in reducing the frequency and severity of osteolytic bone lesions. High-resolution radiographs and microPET images showed that Gem/ BP reduced the number and size of bone metastases relative to the gemcitabine-treated and the untreated control groups. Histological examination of the humeri and femurs of the control and gemcitabine groups revealed large metastatic cancer lesions in the outer and inner cortices and the medullary cavities. In contrast, Gem/BP-treated mice showed occasional small wedge-shaped metastases under the periosteum of the outer cortex and very occasionally in the medulla. These findings suggest that Gem/BP should be further evaluated for use in the treatment of bone metastases in breast cancer.

Application of machine learning methodology for PET-based definition of lung cancer.

We applied a learning methodology framework to assist in the threshold-based segmentation of non-small-cell lung cancer (NSCLC) tumours in positron-emission tomography-computed tomography (PET-CT) imaging for use in radiotherapy planning. Gated and standard free-breathing studies of two patients were independently analysed (four studies in total). Each study had a pet-ct and a treatment-planning ct image. The reference gross tumour volume (GTV) was identified by two experienced radiation oncologists who also determined reference standardized uptake value (SUV) thresholds that most closely approximated the GTV contour on each slice. A set of uptake distribution-related attributes was calculated for each PET slice. A machine learning algorithm was trained on a subset of the PET slices to cope with slice-to-slice variation in the optimal suv threshold: that is, to predict the most appropriate suv threshold from the calculated attributes for each slice. The algorithm's performance was evaluated using the remainder of the pet slices. A high degree of geometric similarity was achieved between the areas outlined by the predicted and the reference SUV thresholds (Jaccard index exceeding 0.82). No significant difference was found between the gated and the free-breathing results in the same patient. In this preliminary work, we demonstrated the potential applicability of a machine learning methodology as an auxiliary tool for radiation treatment planning in NSCLC.

A review of basic principles of fractals and their application to pharmacokinetics.

Pharmacokinetic models play a crucial role in analyzing and assessing the results of in vitro and in vivo studies. In this review, comparative analysis of pharmacokinetic models under homogeneous and heterogeneous conditions is performed, placing special focus on the role of fractal theory. The concept of fractals provides a new perspective from which processes occurring in heterogeneous, confined, or poorly mixed environments can be modeled. Following a brief theoretical overview, the applicability of fractals in characterizing anatomical structures and physiological processes as well as the transport and reaction of drugs within the body is discussed. There is significant evidence that drug absorption, distribution, metabolism, and excretion are often anomalous, that is to say their behavior deviates from classical theory, and possible reasons and appropriate models are considered.

Poster - Thurs Eve-17: Stand alone software for deforming delivered dose distributions to account for daily anatomical variations in prostate patients treated on the TomoTherapy Hi-Art II system.

The acquisition of daily megavoltage (MV)-CT images provides an invaluable tool in the delivery of adaptive radiotherapy (ART) on the TomoTherapy Hi-ART II system. Using TomoTherapy's Planned Adaptive software, delivery sinograms can be applied to pre-treatment MVCT images to generate daily delivered dose distributions, allowing for the potential comparison of planned and delivered doses. However, daily patient anatomical variations complicate the task and accurate comparison requires that daily doses be evaluated in the same references frame as the planned dose. Each anatomical point in daily MVCT images must be mapped to its corresponding point in the patient planning CT and that deformation map must be applied to the daily dose distribution. Stand alone software has been developed for the comparison of planned and delivered doses for TomoTherapy prostate patients. Software inputs are the planning CT, planning structure data, planned dose distribution, daily MVCT and delivered dose distribution. The software uses an in-house developed automatic voxel-based deformable registration algorithm designed and optimized specifically for the registration of prostate CT images to achieve anatomical correspondence between MVCT and planning images. The resultant deformation map is applied to the daily dose distribution and the software outputs the deformed daily dose distribution in the planning CT's reference frame, as well as a delivered DVH for each of the planning CT's ROI. The software allows for a number of potential research opportunities, in particular, the calculation of the cumulative dose delivered over the course of treatment for prostate patients treated on the Hi-Art II system.

Prognostic significance of serial magnetic resonance spectroscopies over the course of radiation therapy for patients with malignant glioma.

BACKGROUND: The standard treatment of high grade gliomas (HGG) involves maximal neuro-surgical debulking, followed by post-operative radiotherapy, with or without concurrent chemotherapy, depending on histologic grade. Despite this aggressive strategy, there are few long-term survivors. Proton magnetic resonance spectroscopy (MRS) is a non-invasive imaging method that can monitor metabolic changes in brain tumours. To date there is little data concerning the prognostic significance of the evolving spectral alterations during a course of radiotherapy. MATERIALS: We report herein a prospective study of patients with HGGs undergoing post-operative radiotherapy. Fourteen consecutively eligible patients with a confirmed histologic diagnosis of malignant glioma and completion of all required MRS imaging were included in this study. All patients had MRS imaging prior to radiotherapy, at week 4 of radiotherapy, and 2 months post-treatment. T1 and T2 weighted images as well as post-gadolinium multi-voxel proton MRS images were obtained. Normalized (tumour metabolite/normal brain metabolite) levels of choline, NAA, creatine, lipid and lactate were calculated. Kaplan-Meier (KM) curves of progression-free and overall survival were constructed based on the evolving patterns of metabolite changes over the course of the images. RESULTS: The mean tumour choline/NAA ratio decreased over the course of therapy, with a reduction observed between the baseline and post-radiotherapy studies (1.91 vs. 1.29, P=0.049). A similar decrease was identified with the mean normalized choline ratio, with a highly significant difference observed between the baseline and post-radiation images (1.61 vs. 0.96, P=0.001). Patients who exhibited more than 40% decrease in normalized choline between the week 4 and post-radiotherapy studies were associated with unfavourable survival (logrank test, P=0.003) and disease progression (logrank test, P=0.012). The Lactate/NAA ratio at the 4th week of radiotherapy and the change in normalized choline/creatine between baseline and week 4 of radiotherapy were also predictive of outcome suggesting the possibility of adaptive, response-based radiation treatment. Patients with two or more poor prognostic MRS indices had a significantly shorter progression-free survival compared with those with zero or one poor indices, with 15% and 68% at 1 year, respectively (logrank test, P=0.045). CONCLUSION: The evolving pattern of spectral changes over the course of radiotherapy, in particular those associated with choline-containing compounds, appears to be prognostic of tumour response and outcome. Based on our data, a decision point may exist in the mid course of radical radiotherapy, at which time consideration of the choline levels could indicate the extent of radiotherapeutic response, thus allowing for individualized treatment modification.

Monte Carlo investigation of single cell beta dosimetry for intraperitoneal radionuclide therapy.

Single event spectra for five beta-emitting radionuclides (Lu-177, Cu-67, Re-186, Re-188, Y-90) were calculated for single cells from two source geometries. The first was a surface-bound isotropically emitting point source and the second was a bath of free radioactivity in which the cell was submerged. Together these represent a targeted intraperitoneal radionuclide therapy. Monoenergetic single event spectra were calculated over an energy range of 11 keV to 2500 keV using the EGSnrc Monte Carlo system. Radionuclide single event spectra were constructed by weighting monoenergetic single event spectra according to radionuclide spectra appropriate for each source geometry. In the case of surface-bound radioactivity, these were radionuclide beta decay spectra. For the free radioactivity, a continuous slowing down approximation spectrum was used that was calculated based on the radionuclide decay spectra. The frequency mean specific energy per event increased as the energy of the beta emitter decreased. This is because, at these energies, the stopping power of the electrons decreases with increasing energy. The free radioactivity produced a higher frequency mean specific energy per event than the corresponding surface-bound value. This was primarily due to the longer mean path length through the target for this geometry. This information differentiates the radionuclides in terms of the physical process of energy deposition and could be of use in the radionuclide selection procedure for this type of therapy.

A numerical approach to non-circular birdcage RF coil optimization: verification with a fourth-order coil.

It is demonstrated that birdcage resonators, satisfying conditions of quadrature operation and radiofrequency field homogeneity, can be realized in practice on formers of non-circular cross section described by an equation of the form (x/a)n + (y/b)n = 1 where a and b are constants and n > or = 2 is an integer. Using a ladder network analogous to that of a conventional circular birdcage, optimization algorithms were employed to determine the elemental current distribution on the non-circular cylindrical surfaces. A comparison of circular, elliptical, symmetric and asymmetric fourth-order (n = 4) section birdcage current distributions is presented. A short, asymmetric fourth-order cage was constructed and tested experimentally at 3 T and compared with a conventional circular-section head coil.

The effects of circulating antigen on the pharmacokinetics and radioimmunoscintigraphic properties of 99m Tc labelled monoclonal antibodies in cancer patients.

UNLABELLED: PURPOSE. This article reports the pharmacokinetics, radiation dosimetry and radioimmunoscintigraphy (RIS) of two (99m)Tc-labelled monoclonal antibodies (MAb) used to detect cancer. METHODS: The effects of circulating antigen in female cancer patients are explored and their effects on the ability of these MAbs to effectively perform as RIS agents noted. To illustrate the effects of circulating antigen, data using MAb B43.13 (OVAREX, AltaRex Corp., Waltham, MA, USA) from a Pilot study in ovarian cancer patients are presented. The results from a Phase II study of MAb 170H.82 (Tru-Scint AD, BIOMIRA INC., Edmonton, Alberta, Canada) in patients with primary and locally recurrent breast cancer were used to portray the biodistribution patterns when no circulating antigen is present. Data from planar gamma camera images were obtained for both groups and used for pharmacokinetic and radiation dosimetry analyses. RESULTS: A pharmacokinetic analysis indicated a shorter residence time and higher clearance of (99m)Tc-MAb-B43.13 that was ascribed in part to the circulating CA 125 antigen in this group of ovarian cancer patients. CONCLUSION: These clearance patterns resulted in acceptable, though higher radiation doses to the spleen and urinary bladder wall for these patients when compared to the MAb-170H.82 group. Both MAbs were found to produce acceptable radioimmunoscintigraphic images

Approximate 3D iterative reconstruction for SPECT.

Compared with slice-by-slice approaches for SPECT reconstruction, three-dimensional iterative methods provide a more accurate physical model and an improved SPECT image. Clinical application of these methods, however, is limited primarily to their computational demands. This paper investigates the methods for approximate 3D iterative reconstruction that greatly reduce this demand by excluding from the reconstruction the smaller magnitude elements of the system matrix. A new method is described which is designed to control the resulting bias in the SPECT image for a given reduction in computation. The approximate methods were compared to fully 3D iterative reconstruction in terms of SPECT image bias and visual quality. All methods were incorporated into the ML-EM algorithm and applied to data from 3D mathematical and experimental brain phantoms. The SPECT images reconstructed by the approximate methods exhibited a positive bias throughout the image that was in general smaller with the new method (in the rage of 2%-6%). The bias was smallest in locally hot regions and largest in locally cold regions. The high quality brain phantom images demonstrated the capability of the new method in realistic imaging contexts. The time per iteration for an entire 3D brain phantom on a modern workstation using the approximate 3D method was 7.0 s.

Planar imaging quantification using 3D attenuation correction data and Monte Carlo simulated buildup factors.

A new method to correct for attenuation and the buildup of scatter in planar imaging quantification is presented. The method is based on the combined use of 3D density information provided by computed tomography to correct for attenuation and the application of Monte Carlo simulated buildup factors to correct for buildup in the projection pixels. CT and nuclear medicine images were obtained for a purpose-built nonhomogeneous phantom that models the human anatomy in the thoracic and abdominal regions. The CT transverse slices of the phantom were converted to a set of consecutive density maps. An algorithm was developed that projects the 3D information contained in the set of density maps to create opposing pairs of accurate 2D correction maps that were subsequently applied to planar images acquired from a dual-head gamma camera. A comparison of results obtained by the new method and the geometric mean approach based on published techniques is presented for some of the source arrangements used. Excellent results were obtained for various source-phantom configurations used to evaluate the method. Activity quantification of a line source at most locations in the nonhomogeneous phantom produced errors of less than 2%. Additionally, knowledge of the actual source depth is not required for accurate activity quantification. Quantification of volume sources placed in foam, Perspex and aluminium produced errors of less than 7% for the abdominal and thoracic configurations of the phantom.

Experimental and numerical investigation of the 3D SPECT photon detection kernel for non-uniform attenuating media.

Experimental tests for non-uniform attenuating media are performed to validate theoretical expressions for the photon detection kernel, obtained from a recently proposed analytical theory of photon propagation and detection for SPECT. The theoretical multi-dimensional integral expressions for the photon detection kernel, which are computed numerically, describe the probability that a photon emitted from a given source voxel will trigger detection of a photon at a particular projection pixel. The experiments were performed using a cylindrical water-filled phantom with large cylindrical air-filled inserts to simulate inhomogeneity of the medium. A point-like, a short thin cylindrical and a large cylindrical radiation source of 99Tcm were placed at various positions within the phantom. The values numerically calculated from the theoretical kernel expression are in very good agreement with the experimentally measured data. The significance of Compton-scattered photons in planar image formation is discussed and highlighted by these results. Using both experimental measurements and the calculated values obtained from the theory, the kernel's size is investigated. This is done by determining the square N x N pixel neighbourhood of the gamma camera that must be connected to a particular radiation source voxel to account for a specific fraction of all counts recorded at all camera pixels. It is shown that the kernel's size is primarily dependent upon the source position and the properties of the attenuating medium through Compton scattering events, with 3D depth-dependent collimator resolution playing an important but secondary role, at least for imaging situations involving parallel hole collimation. By considering small point-like sources within a non-uniform elliptical phantom, approximating the human thorax, it is demonstrated that on average a 12 cm x 12 cm area of the camera plane is required to collect 85% of the total count recorded. This is a significantly larger connectivity than the 3 cm x 3 cm area required if scattering contributions are ignored and only the 3D depth-dependent collimator resolution is considered.

Photon propagation and detection in single-photon emission computed tomography--an analytical approach.

An analytical theory of photon propagation and detection in single-photon emission computed tomography (SPECT) for collimated detectors is developed from first principles. The total photon detection kernel is expressed as a sum of terms due to the primary and the Compton scattered photons. The primary as well as contributions due to every order of Compton scattering are calculated separately. The model accounts for the three-dimensional depth dependence of the collimator holes as well as for nonhomogeneous attenuation. No specific assumptions about the boundary or the homogeneity of the attenuating medium are made. The energy response of the detector is also modeled by the theory. Analytical expressions are obtained for various contributions to the photon detection kernel, and the multidimensional integrals involved are calculated using standard numerical integration methods. Theoretically calculated projections and scatter fractions for the primary and the first through second scattering orders are compared with our own experimental results for a small cylindrical primary radiation source immersed at various positions in a uniform cylindrical phantom. Also, theoretically calculated scatter fractions for a small spherical (pointlike) source in a uniform elliptic phantom are compared with experimental and Monte Carlo simulation results taken from the recent literature. The results from the analytical method are essentially exact and are free from the inaccuracies inherent in the numerical simulation methods used to deal with the photon propagation and detection problem in SPECT so far. The method developed here is unique in the sense that it provides accurate theoretical predictions of results averaged over an infinite number of simulations or experiments. We believe that our theory enhances an intuitive understanding of the complex image formation process in SPECT and is an important step toward solving the inverse problem, that of reconstructing the primary radiation source distribution from the measured gamma camera projections.