Palma Giuseppe, Cella Laura, Monti Serena
Institute of Nanotechnology, National Research Council, Lecce, Italy.
Institute of Biostructures and Bioimaging, National Research Council, Napoli, Italy.
Med Phys. 2023 Apr;50(4):2317-2322. doi: 10.1002/mp.16260. Epub 2023 Feb 14.
Voxel-Based (VB) analysis embraces a multifaceted ensemble of sophisticated techniques, lying at the boundary between image processing and statistical modeling, that allow for a frequentist inference of pathophysiological properties anchored to an anatomical reference. VB methods has been widely adopted in neuroimaging studies and, more recently, they are gaining momentum in radiation oncology research. However, the price for the power of VB analysis is the complexity of the underlying mathematics and algorithms.
In this paper, we present the Multi-pAradigM voxel-Based Analysis (MAMBA) toolbox, which is intended for a flexible application of VB analysis in a wide variety of scenarios in medical imaging and radiation oncology.
The MAMBA toolbox is implemented in Matlab. It provides open-source functions to compute VB statistical models of the input data, according to a great variety of regression schemes, and to derive VB maps of the observed significance level, performing a non-parametric permutation inference. The toolbox allows for including VB and global outcomes, as well as an arbitrary amount of VB and global Explanatory Variables (EVs). In addition, the Matlab Parallel Computing Toolbox is exploited to take advantage of the perfect parallelizability of most workloads.
The use of MAMBA was demonstrated by means of several realistic examples on a synthetic dataset mimicking a radiation oncology scenario.
MAMBA is an open-source toolbox, freely available for academic and non-commercial purposes. It is designed to make state-of-the-art VB analysis accessible to research scientists without the programming resources needed to build from scratch their own software solutions. At the same time, the source code is handed out for more experienced users to complement their own tools, also customizing user-defined models. MAMBA guarantees high generality and flexibility in the design of the statistical models, significantly expanding on the features of available free tools for VB analysis. The presented toolbox aims at increasing the reach of VB studies as well as the sharing of research results.
基于体素（VB）的分析包含了一系列复杂的技术，处于图像处理和统计建模的交叉领域，能够基于解剖学参考对病理生理特性进行频率推断。VB方法已在神经影像学研究中广泛应用，最近在放射肿瘤学研究中也越来越受到关注。然而，VB分析强大功能的代价是其基础数学和算法的复杂性。
在本文中，我们介绍了多范式基于体素分析（MAMBA）工具箱，旨在将VB分析灵活应用于医学成像和放射肿瘤学的各种场景。
MAMBA工具箱在Matlab中实现。它提供开源函数，根据多种回归方案计算输入数据的VB统计模型，并通过非参数置换推断得出观察到的显著性水平的VB图。该工具箱允许纳入VB和全局结果，以及任意数量的VB和全局解释变量（EV）。此外，利用Matlab并行计算工具箱来利用大多数工作负载的完美并行性。
通过在模拟放射肿瘤学场景的合成数据集上的几个实际示例展示了MAMBA的使用。
MAMBA是一个开源工具箱，可免费用于学术和非商业目的。它旨在让研究科学家能够使用先进的VB分析，而无需从头构建自己的软件解决方案所需的编程资源。同时，将源代码提供给更有经验的用户，以补充他们自己的工具，还可定制用户定义的模型。MAMBA在统计模型设计中保证了高度的通用性和灵活性，显著扩展了现有的VB分析免费工具的功能。所展示的工具箱旨在扩大VB研究的范围以及研究结果的共享。
