The short and long term stability of the Diomed 630 PDT laser with attached fiberoptic microlens was evaluated by
means of integrating sphere, power meter and a calorimetric system. The calorimeter system was designed as a thermal
mug with absorbing media (dye and water). Both the tip of the irradiation fiber and the detection probe of a
thermocouple thermometer were positioned inside the dye solution and stirred during the measurements. The
calorimetric system yielded measurement results consistent with the other two methods, and similar long term variations
were observed by all methods. With an indicated laser power of 1 W, the detectors' readings ranged from 0.66 to 1.29
W. For short term stability study, the deviation of laser output assessed by integrating sphere, power meter and
calorimetric system were 0.3%, 0.1% and 2.8% with long term deviations of 13%, 7% and 9% respectively. This wide
variation in the laser output implies the needs to establish quality control procedures involving measurements pre and
post PDT procedures. The calorimetric system has been demonstrated to be a powerful tool for clinical laser QA and
maintenance of the calibration factor of the detectors used in this work.
We reviewed the outcome of combined photodynamic therapy (PDT) and high dose rate brachytherapy
(HDR) for patients with symptomatic obstruction from endobronchial non-small cell lung cancer. Methods: Nine
patients who received combined PDT and HDR for endobronchial cancers were identified and their charts reviewed.
The patients were eight males and one female aged 52-73 at diagnosis, initially presenting with various stages of disease:
stage IA (N=1), stage IIA (N=1), stage III (N=6), and stage IV (N=1). Intervention was with HDR (500 cGy to 5 mm
once weekly for 3 weeks) and PDT (2 mg/kg Photofrin, followed by 200 J/cm2 illumination 48 hours post infusion).
Treatment group 1 (TG-1, N=7) received HDR first; Treatment group 2 (TG-2, N=2) received PDT first. Patients were
followed by regular bronchoscopies. Results: Treatments were well tolerated, all patients completed therapy, and none
were lost to follow-up. In TG-1, local tumor control was achieved in six of seven patients for: 3 months (until death), 15
months, 2+ years (until death), 2+ years (ongoing), and 5+ years (ongoing, N=2). In TG-2, local control was achieved in
only one patient, for 84 days. Morbidities included: stenosis and/or other reversible benign local tissue reactions (N=8);
photosensitivity reaction (N=2), and self-limited pleural effusion (N=2). Conclusions: Combined HDR/PDT treatment
for endobronchial tumors is well tolerated and can achieve prolonged local control with acceptable morbidity when PDT
follows HDR and when the spacing between treatments is one month or less. This treatment regimen should be studied
in a larger patient population.
Multifocal recurrence of in-situ squamous cell cancer of the oral cavity, pharynx and vocal cord
following surgical failure can be a therapeutic dilemma. Salvage surgery or radiation may be an option but
morbidity can be significant. We evaluated the potential role of low dose Photofrin (1.2mg/Kg)
Photodynamic Therapy for this cohort of patients.
A total of 25 patients with multifocal recurrent in-situ squamous cell cancer of the oral cavity,
pharynx and vocal cord who had failed local resection, and where additional surgery or radiation therapy
would likely result in permanent morbidity, were offered Photodynamic Therapy. PDT consisted of off
label infusion of Photofrin (1.2mg/kg) followed 48 hours later by illumination at 630nm employing a light
diffuser (300J) and/or microlens (150Jcm2).
All patients completed their prescribed PDT and no patient has been lost to follow up (minimum 1
year). No photosensitivity reactions were noted. No significant morbidity was seen. All patients were able
to maintain oral nutrition. Procedure related pain was well controlled by one week of oral narcotics. At
one month post PDT all patients were biopsy negative in the treatment region and no failures within the
treatment region have been noted. No fibrosis or permanent PDT morbidity has been seen with follow up to
three years. Vocal cord and voice function were excellent.
Three patients developed new regions of in-situ disease outside the PDT fields, two underwent additional
PDT and one had laser resection.
Low dose Photofrin PDT offers excellent palliation and durable local control of recurrent in-situ
squamous cell cancers of the oral cavity, pharynx and true cords. This is a well tolerated therapy. Low
dose Photofrin appears to improve selectivity and minimize normal tissue injury. It should be tested in a
larger patient population.
Photodynamic therapy (PDT) is a technique for inducing tissue damage with light irradiation of a drug selectively retained in malignant tissue in presence of oxygen. The same mechanisms responsible for PDT efficacy can destroy the sensitizer, a process called photobleaching. In this work, the photobleaching of Photogem (a hematoporphyrin derivative used in Brazil made in Russia) was induced to study phototoxicity of the photoproducts upon a tumor (HEp-2) and non-tumor (VERO) cell line. Photogem was previously irradiated at 514nm and 630 nm (50mW/cm2) for 120 min. The sensitizer photobleaching was monitored by fluorescence and absorption properties changes and photoproducts formation evidenced by the appearance of a new absorption band around 640nm. Irradiated and non-irradiated Photogem were incubated for 18h with the cells. After drug removal, cells were irradiated with LED at 630 nm with intensities of 13, 20 and 25mW/cm2 for different times. Then, the cells were incubated for 48 hours to determine the cells viability by the MTT method. The cells in the dark were used as control. The IC50 decreases as light intensity increases, being more pronounced for tumor cells. Previously irradiated Photogem needs one-hour irradiation for both cell lines to have the same IC50 value of non-irradiated Photogem, which are irradiated for 14 min in tumor cells and 25 min in non-tumor cells. The results suggest that the photoproducts of Photogem are less cytotoxic either in the dark or in the light, decreasing with increase of intensity. These results underline the importance of dosimetry in PDT.
We have performed an experiment to investigate the degradation of the photosensitizer Photogem in solution. The investigation was carried out at 630 nm diode laser for different intensities. The light degradation considered was from light that could cause modification of the solution fluorescence spectra under excitation of 535 nm. Knowing the degradation rate as a function of intensity, one can infer the rate of degradation during PDT application and its process efficiency loss.
KEYWORDS: Principal component analysis, Skin, Monte Carlo methods, Reflectivity, Imaging systems, In vivo imaging, Data modeling, Melanoma, Algorithm development, Tissue optics
Early detection of malignant melanoma is critical to improve the survival rates of patients with this aggressive malignancy. We constructed an imaging system employing two liquid-crystal tunable filters to acquire in vivo spectral images of dysplastic lesions from patients at 31 wavelengths from 500 to 950nm. These reflectance images were analyzed in search of optical signatures for quantitative characterization of dysplastic nevi and malignant melanoma. A principal component analysis (PCA) algorithm was developed to examine the spectral imaging data in the component space and an index of spreading of clustering pixels (SCP) was defined to measure the degree of clustering in the distribution of image pixel scores in a component space. We found that SCP of differential polarimetric images correlate strongly with the degree of dysplasia for 4 lesions. However, many questions remain unanswered on the relations between PCA results and the spatial and spectral characteristics of the image data because of limited spectral image data from the patients. To fully improve our understanding on the multivariate analysis of spectral imaging data, we have developed a parallel Monte Carlo code to efficiently generate reflectance images from given distribution of optical parameters in a skin lesion phantom. With this tool, we have investigated numerically the dependence of score distribution and SCP in the component sub-spaces on lesion size and position. These numerical results provide a foundation for our future study to identify optical signature of dysplastic lesion and melanoma in the skin.
The response of a digital computed radiography system to the megavoltage therapeutic radiation beams was invested. A narrow slit of radiation beam was used to test the line spread function of the system. The effects of various facts such as cassette, beam energy, radiation dose, scanning orientation and timing on the line spread function were investigated. The calibration curves were established to calibrate the image intensity to the megavoltage radiation dose. The calibration curves were applied to measure the beam profiles of the radiation fields with various wedges.
A prototype high definition multi-leaf collimator system (HDI) has been developed and installed on the linear accelerator for use in conformal radiotherapy. The HDI technique utilizes the dynamic shift of the 3D-target volume to feather the multi-leaf collimator defined field edges. During each feathering, the leaf positions are adjusted according to the updated target image projected into the MLC plane. The purpose of this study is to demonstrate that this device can improve spatial resolution of a conformal radiation therapy treatment. The results of this study indicate that the HDI technique can be a useful tool for treating small, or highly irregular shaped targets, and for sparing adjacent critical structures for certain cases.
The aim of this work is to increase the precision of the computations involved in brain tumor stereotactic radiosurgery. It is proposed to apply the newest algorithm of contour segmentation to the contours of the MR/CT slices. It is shown that this algorithm improves significantly the accuracy and speed of the classical contour segmentation algorithms and produces a one-to-one transformation between the Euclidean space and the discrete pixel space. For the distance computations involved in dose distribution computation a subpixel precision is obtained. The segmentation algorithm computes the exact equation of the discrete lines forming a pixel contour of an object (the skull, a tumor, etc.). Since it actually computes the equation of the lines forming the contour and not an approximated line like most algorithms, the algorithm is reversible. From the segmented contour the pixel contour can be exactly reconstructed without loss or displacement of any pixel. The segmentation algorithm is quick since it works in linear time. The present application involves the computation of dose distribution for stereotactic radiosurgery. The intersection between the ray and the skull, the sinus cavities and the tumor can be computed with subpixel accuracy. This obviously improves the dose distribution computation. There are many other applications for this algorithm, for example segmentation, slice reconstruction or simply better rendering of anatomical information, etc. The advantage of this segmentation algorithm over classical approaches lies not only in the results presented here, but also in the fact that a 3D extension should be available soon. This strongly suggests the building of a real 3D planning system, simplifies the inverse planning problem and increases the precision of the computations involved in stereotactic radiosurgery.
KEYWORDS: Positron emission tomography, Magnetic resonance imaging, Image segmentation, 3D modeling, Tomography, Information fusion, Data modeling, Medical imaging, Heart, Fuzzy logic
A new methodology is proposed for the delineation of anatomical or physiological target regions utilizing a rich set of multimodality imagery. The proposed technique is unique in that it allows the integration of anatomical cues from transmission tomography (MRI/CT) with more fuzzy, physiological information derived from emission tomography (PET/SPECT). This approach allows for the delineation of regions of homogeneous tracer uptake constrained by the boundaries of anatomical structures, and vice versa. An extension of deformable model segmentation techniques is presented which integrates both region and edge information from registered scans in a competitive manner. The proposed technique has been implemented for two-dimensional deformable models. Results are presented for the cases of unimodal MRI in which region and edge information is integrated, and for a multimodal case employing a registered MRI and PET scan.
Biomedical image data, such as obtained from CT or MR imaging modalities, tend to occupy a large amount of storage space. At the cost of losing or distorting salient features, lossy compression techniques can be used to reduce significantly the amount of data storage space. The main aim of this article is to present a novel method for optimal enhancement and restoration of images recovered from data stored using lossy compression techniques. A statistical model of the deformations undergone by the salient features within the original image, when it is stored using lossy compression techniques and then recovered, is generated. This statistical model generates a discrete lattice space. The algorithm presented here designs a set of filters over the statistical lattice space. Due to the statistical nature of the lattice the designed filters are optimal and the best possible recovery of the salient features in the original image is achieved. Results comparing the performance of the presented method to that achieved by median filters are presented. Robustness of the algorithm is tested by applying filters generated using a set of images of one subject, to images of different subjects and images stored using different compression ratios.
KEYWORDS: Visualization, Computing systems, Medical imaging, 3D displays, Surgery, Reliability, 3D image processing, 3D modeling, Cancer, Biomedical optics
In this paper, we present a new approach to the generation and manipulation of oblique slices of MR/CT or any voxel space images. We consider the result of the voxel space as if it would be cut by a scalpel, simulating the action of a surgeon. With the intervention of a new definition of discrete 3D voxel plane, we show that this can be done in a highly efficient way and that there are very few computations to do. It is shown that the supercover of the continuous oblique plane is a 6-connected discrete plane that has many very interesting properties that can be usefully exploited. For instance, geometrical considerations avoid much of the intersection computations and once one oblique slice is generated, all the other parallel oblique slices can be generated with few further computations. These results are applied to improve the existing algorithms and provide some ideas for new ones. It should also improve the handling possibilities of oblique slices, indeed, almost all that can be done on a sagittal or axial slice can then also be done on oblique slices. An extension to 4D oblique slices is possible.
This paper proposes an approach to advance the utility of physical modeling techniques for medical applications by correlating finite element based models with the mechanical anatomy characteristic of a clinical patient. A methodology is presented to model the patient-specific mechanical response of brain tissue in vivo. The resultant model is parameterized in terms of clinical CT and MRI imaging sequences acquired for each patient. Applications of the proposed technique to the areas of brain tumor growth modeling and predicting tissue shifts during stereotactic neurosurgery, are described. Results are presented for an implementation of our approach to the problem of predictive brain tumor modeling.
In the present work, distinct structures appearing in biomedical images are modeled as fractals. Within an image, the relevant structures are associated to a fractal dimension. Changes in the dimension values, as a function of time, reflect alterations of structural properties. Accurate and robust estimation of this dimension, leads to a precise characterization of changes undergone by the structure. The Continuous Pyramidal Alternating Sequential Filter method is proposed as a robust and accurate fractal dimension estimator. A study on bedrest data of human subjects was conducted. Bedrest is an accepted model for the study of osteoporosis. Here the spine is modeled as a fractal structure. Fractal model were also applied towards analysis of breast cancer and brain tumors. Results from these different studies confirm that fractals can suitably model a variety of biological structures. These studies also suggest that fractal models can be effectively utilized to detect temporal changes undergone by the structures.
Radiation therapy is a treatment modality which seeks to deliver radiation energy to a localized site within a patient, in order to destroy a malignant tumor. The nature of radio-therapy results in dual, conflicting treatment goals: (1) the ability to deliver sufficient energy to a site so as to destroy the growth and, (2) sufficient localization of the energy to minimize the damage of surrounding, healthy tissue. One of the most important aspects of radiation dose treatment planning is the accurate localization of tumor masses. In order for a course of radiation therapy to be successful, the treatment volume must encompass the entire malignant process. Accordingly, the treatment volume must include the primary tumor of interest, as well as the direct and indirect course of the cancer's metastasis. Clinical results have demonstrated that a patient's tolerance to a given dose of radiation decreases as the volume exposed is increased. Therefore, improvements in tumor localization will provide the maximum amount of tissue sparing to the patient while encompassing the necessary target volume. An improved methodology is presented for the localization of tumors. This approach focuses on the integration of MRI and CT imaging data towards the generation of a mathematically optimal, tumor boundary. The solution to this problem is formulated within a framework integrating concepts from the fields of deformable modeling, fuzzy logic, and data fusion. Fuzzy edges derived from CT and MR are combined to form an integrated edge map, which subsequently guides the `growth' of a deformable tumor model. The fusion algorithm yields tumor contours which may be employed directly in the radiation therapy treatment planning process. Results are presented for the case of a phantom data set, with a simulated-implanted tumor, as well as for an actual patient.
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