# A Review of Image Reconstruction Algorithms for Diffuse Optical Tomography
## 5 Discussion  
The image-reconstruction algorithms reviewed in the previous sections were studied to address each technical problem. In actual clinical measurements, image reconstruction is required to consider these problems comprehensively. In particular, an improvement in the spatial resolution is essential for the diagnosis of cancers, which are important imaging targets of DOT. Studies on breast cancers using DOT and NIR spectroscopy indicated that malignant breast cancer had statistically different optical properties from normal tissues [8; 10; 12]. Malignant tumors can have a higher total hemoglobin concentration and a larger scattering coefficient than normal tissues and benign tumors. In addition to breast cancer, cancers of other organs involve abnormal vascularization. Microwessel density in tumors, which can be imaged noninvasively by diffuse optical techniques, can be an indicator of tumor grade and stage, and a prognostic indicator [157]. The progression and expansion of malignant tumors require nutrient supply and waste removal, which can be accomplished by microcirculation owing to angiogenesis and vasculogenic mimicry in tumors. Therefore, contrast with hemoglobin must be useful. However, it is difficult to distinguish cancer from benign lesions using hemoglobin as a contrast agent because the hemoglobin concentration increases in both the carrier and benign lesions [12]. One of the important characteristics useful for cancer diagnosis is tumor heterogeneity. Although the hemoglobin concentration is an important biomarker, it changes temporally and spatially in tumors. The peripheral area and invasive edge of the tumor can have more blood flow and higher hemoglobin concentrations. However, blood flow in growing tumors can decrease due to decreasing vessel density, severe structural and functional abnormalities of the vessels, and the development of necrosis [158]. Heterogeneous hypoxic regions of tumors with low blood flow, which often exist in the core of tumors and resist radiotherapy, are of interest in various medical imaging studies [159]. By imaging the heterogeneity of tumors quantitatively and qualitatively using an improved image reconstruction algorithm, DOT may be applied as expected in cancer diagnoses. Therefore, the low spatial resolution of DOT due to diffusive light propagation should be overcome by image reconstruction for clinical use, although it may not be easy for the current DOT to reconstruct the heterogeneity within a tumor a few centimeters in size. In image reconstruction, the mismatch between the forward calculation and the actual light propagation degrades image quality. Therefore, high-precision computation in the forward process is desirable. The use of RTE is a promising direction, especially for imaging cancers and abnormalities such as thyroid cancer and rheumatic arthritis, which are near the illumination positions. The error of DA increases in regions with \(\mu_{a}>0.01\) mm\({}^{-1}\) and a distance smaller than 5 mm from the illuminating position, according to studies [74; 97] comparing DA and MC simulations. DA can increase the error in the void and low scattering regions, such as the trachea in the neck and cerebral spinal fluid layer in the head, as discussed in the literature on RTE, \(P_{N}/SP_{N}\) approximations, and the MC method. However, the use of the RTE with appropriate discretization is a time-consuming and computationally expensive process. Higher-order approximations using \(P_{N}/SP_{N}\) methods [57; 58; 59; 60; 61; 62; 63; 64; 65; 66] and hybrid methods [87] can also be useful. In the application of DOT, including cancer imaging and functional brain imaging, the imaging targets associated with changes in hemoglobin concentration must be selected from a heterogeneous background consisting of multiple organs and different tissues. The effects of background heterogeneity cannot be ignored under realistic scenarios.