Use of Zernike moments to characterize dose conformity for radiotherapy treatment plans.

Dose conformity is an essential parameter used in radiotherapy and radiosurgery that measures the correspondence of the dose distribution derived from a Treatment Planning System (TPS) with the actual volume to be treated, the Planning Treatment Volume (PTV). The present work uses a method based on the expansion of dose distributions and PTVs by three-dimensional Zernike polynomials and further comparison of their moments to define a general criterion of dose conformity. To carry on this study, data coming from 20 patients comprising 80 datasets exported from the TPS, which included imaging data (PTVs) and dose distributions corresponding to different treatment modalities: three-dimensional conformal radiotherapy, intensity-modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT), were used. The expansions in Zernike polynomials were obtained up to order 6 and reconstructed dose distributions and PTVs were obtained and compared, and several definitions for a general dose conformity index were proposed. Results indicate agreement between the proposed dose conformity index and the Conformation Number CN. The proposed method allows for a systematic approach to the analysis of dose distributions with further extensions in AI applications.

Multifractal Analysis of Brain Tumor Interface in Glioblastoma.

The dynamics of tumor growth is a very complex process, generally accompanied by numerous chromosomal aberrations that determine its genetic and dynamical heterogeneity. Consequently, the tumor interface exhibits a non-regular and heterogeneous behavior often described by a single fractal dimension. A more suitable approach is to consider the tumor interface as a multifractal object that can be described by a set of generalized fractal dimensions. In the present work, detrended fluctuation and multifractal analysis are used to characterize the complexity of glioblastoma.

Morphological and Fractal Properties of Brain Tumors.

Tumor interface dynamics is a complex process determined by cell proliferation and invasion to neighboring tissues. Parameters extracted from the tumor interface fluctuations allow for the characterization of the particular growth model, which could be relevant for an appropriate diagnosis and the correspondent therapeutic strategy. Previous work, based on scaling analysis of the tumor interface, demonstrated that gliomas strictly behave as it is proposed by the Family-Vicsek ansatz, which corresponds to a proliferative-invasive growth model, while for meningiomas and acoustic schwannomas, a proliferative growth model is more suitable. In the present work, other morphological and dynamical descriptors are used as a complementary view, such as surface regularity, one-dimensional fluctuations represented as ordered series and bi-dimensional fluctuations of the tumor interface. These fluctuations were analyzed by Detrended Fluctuation Analysis to determine generalized fractal dimensions. Results indicate that tumor interface fractal dimension, local roughness exponent and surface regularity are parameters that discriminate between gliomas and meningiomas/schwannomas.

Fractals in the neurosciences, Part II: clinical applications and future perspectives.

It has been ascertained that the human brain is a complex system studied at multiple scales, from neurons and microcircuits to macronetworks. The brain is characterized by a hierarchical organization that gives rise to its highly topological and functional complexity. Over the last decades, fractal geometry has been shown as a universal tool for the analysis and quantification of the geometric complexity of natural objects, including the brain. The fractal dimension has been identified as a quantitative parameter for the evaluation of the roughness of neural structures, the estimation of time series, and the description of patterns, thus able to discriminate different states of the brain in its entire physiopathological spectrum. Fractal-based computational analyses have been applied to the neurosciences, particularly in the field of clinical neurosciences including neuroimaging and neuroradiology, neurology and neurosurgery, psychiatry and psychology, and neuro-oncology and neuropathology. After a review of the basic concepts of fractal analysis and its main applications to the basic neurosciences in part I of this series, here, we review the main applications of fractals to the clinical neurosciences for a holistic approach towards a fractal geometry model of the brain.

Fractal analysis of tumoral lesions in brain.

In this work, it is proposed a method for supervised characterization and classification of tumoral lesions in brain, based on the analysis of irregularities at the lesion contour on T2-weighted MR images. After the choice of a specific image, a segmentation procedure with a threshold selected from the histogram of intensity levels is applied to isolate the lesion, the contour is detected through the application of a gradient operator followed by a conversion to a "time series" using a chain code procedure. The correlation dimension is calculated and analyzed to discriminate between normal or malignant structures. The results found showed that it is possible to detect a differentiation between benign (cysts) and malignant (gliomas) lesions suggesting the potential of this method as a diagnostic tool.

A quasi-analytical method for relaxation rate distribution determination of T2-weighted MRI in brain.

A quasi-analytical method for the determination of relaxation rate distribution functions in T2-weighted MRI in brain is proposed. The method solves analytically the set of non linear polynomial equations on the assumption that the transversal magnetization decay in Carr-Purcell-Meiboom-Gill (CPMG) T2-weighted MR brain images can be decomposed in a finite number of exponential decays, each one corresponding to a particular tissue class. The proposed method was validated by numerical simulations and applied to the calculation of relaxation rate distribution functions of tumoral lesions in brain.

Nosologic maps of brain tumor images obtained from combination of different MRI modalities.

Tissue classification is a necessary step to obtain the spatial distribution of a pathology or nosologic map and typically it is performed by the combination of different medical image modalities, including histopathological studies. In previous work, combination of different magnetic resonance (MR) modalities such as in vivo spectroscopy, relaxometry and diffusometry have been proposed to obtain nosologic maps with appropriate spatial resolution for treatment considerations. Due to the low spatial resolution of localized in vivo spectroscopy and low longitudinal resolution in relaxation and diffusion-weighted images a partial volume problem is always present. Present work attempts to overcome this problem by careful analysis of transversal relaxation rate and apparent diffusion coefficient distributions obtained by an inverse Laplace transform algorithm (ILTA).

Brain tumor evaluation and segmentation by in vivo proton spectroscopy and relaxometry.

A new methodology has been developed for the evaluation and segmentation of brain tumors using information obtained by different magnetic resonance techniques such as in vivo proton magnetic resonance spectroscopy (1HMRS) and relaxometry. In vivo 1HMRS may be used as a preoperative technique that allows noninvasive monitoring of metabolites to identify the different tissue types present in the lesion (active tumor, necrotic tissue, edema, and normal or non-affected tissue). Spatial resolution for treatment consideration may be improved by using 1HMRS combined or fused with images obtained by relaxometry which exhibit excellent spatial resolution. Some segmentation schemes are presented and discussed. The results show that segmentation performed in this way efficiently determines the spatial localization of the tumor both qualitatively and quantitatively. It provides appropriate information for therapy planning and application of therapies such as radiosurgery or radiotherapy and future control of patient evolution.

An epitope variable-reservoir model for HIV-1 infection

Se presenta un modelo de infección por VIH-1 basado en el concepto de inmunodominancia. Además de viriones mutantes y células T-CD4, se considera también reservorios virales, entre ellos macrófagos y células dendríticas foliculares. También se considera ataque citotóxico contra los reservorios y ataque extracelular sobre los viriones, ambos coordinados por las células T-CD4. En primer lugar, se trabaja sólo con una variable viral, y se usan ciertas aproximaciones para obtener un modelo fácilmente manipulable, para el cual se encuentra un criterio de estabilidad que rige el paso de progresión a regresión de la infección. Este criterio mantiene su validez para el modelo sin uso de aproximaciones, esto es, dos epítopes que mutan al azar, cada uno de ellos con dos variantes. Los resultados sugieren: a) que el papel jugado por los reservorios en el mantenimiento de la infección es muy importante, b) que mantener el ataque de las células citotóxicas sobre los reservorios infectados facilita la labor del sistema inmune, y c) que la terapia debería orientarse preferiblemente hacia estos objetivos.

Efecto de la luz laser infrarroja pulsada sobre neoplasias malignas en ratones (Balb-c y Nih) y ratas (Sprage Dawley) / Effect of the infrared laser light played on malignant neoplasia in mices Balb-C y Nih and rats Sprague-Dawley

Esta investigación tiene por objeto determinar el efecto de la radiación láser pulsada infrarroja cercana (8:30 nm) sobre los tumores de Walker (serie I) en ratas Sprague Dawley, mieloma (serie II) y INHRR-984 (serie III) en ratones Balb-C y NIH, respectivamente. El trabajo se dividió en tres experimentales que permitieron determinar el efecto de la radiación utilizada sobre los diversos tipos de tumores. Los datos obtenidos en cada serie experimental fueron analizados utilizando el test de Student (t). Estos resultados fueron los siguientes: en la serie I la luz láser ejerce un efecto de remisión sobre el tamaño del tumor en los animales enfermos irradiados y produce una reducción transitoria del hematocrito debida quizás a su influencia sobre los factores tumorales y/o sanguíneos; en la serie II la radiación utilizada no afecta el peso de los ratones Balb-C inoculados con el tumor de células de mieloma y en la serie III se demostró que no existen diferencias estadísticamente significativas al comparar el peso ni el hematocrito promedio de los grupos estudiados. Sin embargo, en esta misma serie la sobrevivencia de los animales enfermos irradiados fue mayor que en aquellos enfermos no irradiados