Connectivity patterns of the core resting-state networks associated with apathy in late-life depression.

BACKGROUND: Apathy is associated with reduced antidepressant response and dementia in late-life depression (LLD). However, the functional cerebral basis of apathy is understudied in LLD. We investigated the functional connectivity of 5 resting-state networks (RSN) hypothesized to underlie apathy in LLD. METHODS: Resting-state functional MRI data were collected from individuals with LLD who did not have dementia as well as healthy older adults between October 2019 and April 2022. Apathy was evaluated using the diagnostic criteria for apathy (DCA), the Apathy Evaluation Scale (AES) and the Apathy Motivation Index (AMI). Subnetworks whose connectivity was significantly associated with each apathy measure were identified via the threshold-free network-based statistics. Regions that were consistently associated with apathy across the measures were reported as robust findings. RESULTS: Our sample included 39 individuals with LLD who did not have dementia and 26 healthy older adults. Compared with healthy controls, individuals with LLD had an altered intra-RSN and inter-RNS connectivity in the default mode, the cingulo-opercular and the frontoparietal networks. All 3 apathy measurements showed associations with modified intra-RSN connectivity in these networks, except for the DCA in the cingulo-opercular network. The AMI scores showed stronger associations with the cingulo-opercular and frontoparietal networks, whereas the AES had stronger associations with the default mode network and the goal-oriented behaviour network. LIMITATIONS: The study was limited by the small number of participants without apathy according to the DCA, which may have reduced the statistical power of between-group comparisons. Additionally, the reliance on specific apathy measures may have influenced the observed overlap in brain regions. CONCLUSION: Our findings indicate that apathy in LLD is consistently associated with changes in both intra-RSN and inter-RSN connectivity of brain regions implicated in goal-oriented behaviours. These results corroborate previous findings of altered functional RSN connectivity in severe LLD.

Quantitative perfusion mapping with induced transient hypoxia using BOLD MRI.

PURPOSE: Gadolinium-based dynamic susceptibility contrast (DSC) is commonly used to characterize blood flow in patients with stroke and brain tumors. Unfortunately, gadolinium contrast administration has been associated with adverse reactions and long-term accumulation in tissues. In this work, we propose an alternative deoxygenation-based DSC (dDSC) method that uses a transient hypoxia gas paradigm to deliver a bolus of paramagnetic deoxygenated hemoglobin to the cerebral vasculature for perfusion imaging. METHODS: Through traditional DSC tracer kinetic modeling, the MR signal change induced by this hypoxic bolus can be used to generate regional perfusion maps of cerebral blood flow, cerebral blood volume, and mean transit time. This gas paradigm and blood-oxygen-level-dependent (BOLD)-MRI were performed concurrently on a cohort of 66 healthy and chronically anemic subjects (age 23.5 ± 9.7, female 64%). RESULTS: Our results showed reasonable global and regional agreement between dDSC and other flow techniques, such as phase contrast and arterial spin labeling. CONCLUSION: In this proof-of-concept study, we demonstrated the feasibility of using transient hypoxia to generate a contrast bolus that mimics the effect of gadolinium and yields reasonable perfusion estimates. Looking forward, optimization of the hypoxia boluses and measurement of the arterial-input function is necessary to improve the accuracy of dDSC. Additionally, a cross-validation study of dDSC and DSC in brain tumor and ischemic stroke subjects is warranted to evaluate the clinical diagnostic utility of this approach.

Transient Hypoxia Model Revealed Cerebrovascular Impairment in Anemia Using BOLD MRI and Near-Infrared Spectroscopy.

BACKGROUND: Obstructive sleep apnea and nocturnal oxygen desaturations, which are prevalent in sickle cell disease (SCD) and chronic anemia disorders, have been linked to risks of stroke and silent cerebral infarcts (SCI). Cerebrovascular response to intermittent desaturations has not been well studied and may identify patients at greatest risk. PURPOSE: To investigate the cerebral dynamic response to induced desaturation in SCD patients with and without SCI, chronic anemia, and healthy subjects. STUDY TYPE: Prospective. SUBJECTS: Twenty-six SCD patients (age = 21 ± 8.2, female 46.2%), including 15 subjects without SCI and nine subjects with SCI, 15 nonsickle anemic patients (age = 22 ± 5.8, female 66.7%), and 31 controls (age = 28 ± 12.3, female 77.4%). FIELD STRENGTH/SEQUENCE: 3T, gradient-echo echo-planar imaging. ASSESSMENT: A transient hypoxia challenge of five breaths of 100% nitrogen gas was performed with blood oxygen level-dependent (BOLD) MRI and near-infrared spectroscopy (NIRS) acquisitions. Hypoxia responses were characterized by desaturation depth, time-to-peak, return-to-baseline half-life, and posthypoxia recovery in the BOLD and NIRS time courses. SCI were documented by T2 fluid-attenuation inversion recovery (FLAIR). STATISTICAL TESTS: Univariate and multivariate regressions were performed between hypoxic parameters and anemia predictors. Voxelwise two-sample t-statistic maps were used to assess the regional difference in hypoxic responses between anemic and control groups. RESULTS: Compared to controls, SCD and chronically anemic patients demonstrated significantly higher desaturation depth (P < 0.01) and shorter return-to-baseline timing response (P < 0.01). Patients having SCI had shorter time-to-peak (P < 0.01), return-to-baseline (P < 0.01), and larger desaturation depth (P < 0.01) in both white matter regions at risk and normal-appearing white matter than patients without infarcts. On multivariate analysis, desaturation depth and timing varied with age, sex, blood flow, white blood cells, and cell-free hemoglobin (r2 = 0.25 for desaturation depth; r2 = 0.18 for time-to-peak; r2 = 0.37 for return-to-baseline). DATA CONCLUSION: Transient hypoxia revealed global and regional response differences between anemic and healthy subjects. SCI was associated with extensive heterogeneity of desaturation dynamics, consistent with extensive underlying microvascular remodeling.

White matter has impaired resting oxygen delivery in sickle cell patients.

Although modern medical management has lowered overt stroke occurrence in patients with sickle cell disease (SCD), progressive white matter (WM) damage remains common. It is known that cerebral blood flow (CBF) increases to compensate for anemia, but sufficiency of cerebral oxygen delivery, especially in the WM, has not been systematically investigated. Cerebral perfusion was measured by arterial spin labeling in 32 SCD patients (age range: 10-42 years old, 14 males, 7 with HbSC, 25 HbSS) and 25 age and race-matched healthy controls (age range: 15-45 years old, 10 males, 12 with HbAS, 13 HbAA); 8/24 SCD patients were receiving regular blood transfusions and 14/24 non-transfused SCD patients were taking hydroxyurea. Imaging data from control subjects were used to calculate maps for CBF and oxygen delivery in SCD patients and their T-score maps. Whole brain CBF was increased in SCD patients with a mean T-score of 0.5 and correlated with lactate dehydrogenase (r2 = 0.58, P < 0.0001). When corrected for oxygen content and arterial saturation, whole brain and gray matter (GM) oxygen delivery were normal in SCD, but WM oxygen delivery was 35% lower than in controls. Age and hematocrit were the strongest predictors for WM CBF and oxygen delivery in patients with SCD. There was spatial co-localization between regions of low oxygen delivery and WM hyperintensities on T2 FLAIR imaging. To conclude, oxygen delivery is preserved in the GM of SCD patients, but is decreased throughout the WM, particularly in areas prone to WM silent strokes.

Structural Brain Connectivity and Treatment Improvement in Mood Disorder.

Background: The treatment of depressive episodes is well established, with clearly demonstrated effectiveness of antidepressants and psychotherapies. However, more than one-third of depressed patients do not respond to treatment. Identifying the brain structural basis of treatment-resistant depression could prevent useless pharmacological prescriptions, adverse events, and lost therapeutic opportunities. Methods: Using diffusion magnetic resonance imaging, we performed structural connectivity analyses on a cohort of 154 patients with mood disorder (MD) and 77 sex- and age-matched healthy control (HC) participants. To assess illness improvement, the patients with MD went through two clinical interviews at baseline and at 6-month follow-up and were classified based on the Clinical Global Impression-Improvement score into improved or not-improved (NI). First, the threshold-free network-based statistics (NBS) was conducted to measure the differences in regional network architecture. Second, nonparametric permutations tests were performed on topological metrics based on graph theory to examine differences in connectome organization. Results: The threshold-free NBS revealed impaired connections involving regions of the basal ganglia in patients with MD compared with HC. Significant increase of local efficiency and clustering coefficient was found in the lingual gyrus, insula, and amygdala in the MD group. Compared with the NI, the improved displayed significantly reduced network integration and segregation, predominately in the default-mode regions, including the precuneus, middle temporal lobe, and rostral anterior cingulate. Conclusions: This study highlights the involvement of regions belonging to the basal ganglia, the fronto-limbic network, and the default mode network, leading to a better understanding of MD disease and its unfavorable outcome.

Quantifying Apathy in Late-Life Depression: Unraveling Neurobehavioral Links Through Daily Activity Patterns and Brain Connectivity Analysis.

BACKGROUND: Better understanding apathy in late-life depression would help improve prediction of poor prognosis of diseases such as dementia. Actimetry provides an objective and ecological measure of apathy from patients' daily motor activity. We aimed to determine whether patterns of motor activity were associated with apathy and brain connectivity in networks that underlie goal-directed behaviors. METHODS: Resting-state functional magnetic resonance imaging and diffusion magnetic resonance imaging were collected from 38 nondemented participants with late-life depression. Apathy was evaluated using the diagnostic criteria for apathy, Apathy Evaluation Scale, and Apathy Motivation Index. Functional principal components (fPCs) of motor activity were derived from actimetry recordings taken for 72 hours. Associations between fPCs and apathy were estimated by linear regression. Subnetworks whose connectivity was significantly associated with fPCs were identified via threshold-free network-based statistics. The relationship between apathy and microstructure metrics was estimated along fibers by diffusion tensor imaging and a multicompartment model called neurite orientation dispersion and density imaging via tractometry. RESULTS: We found 2 fPCs associated with apathy: mean diurnal activity, negatively associated with Apathy Evaluation Scale scores, and an early chronotype, negatively associated with Apathy Motivation Index scores. Mean diurnal activity was associated with increased connectivity in the default mode, cingulo-opercular, and frontoparietal networks, while chronotype was associated with a more heterogeneous connectivity pattern in the same networks. We did not find significant associations between microstructural metrics and fPCs. CONCLUSIONS: Our findings suggest that mean diurnal activity and chronotype could provide indirect ambulatory measures of apathy in late-life depression, associated with modified functional connectivity of brain networks that underlie goal-directed behaviors.

Brain BOLD and NIRS response to hyperoxic challenge in sickle cell disease and chronic anemias.

PURPOSE: Congenital anemias, including sickle cell anemia and thalassemia, are associated with cerebral tissue hypoxia and heightened stroke risks. Recent works in sickle cell disease mouse models have suggested that hyperoxia respiratory challenges can identify regions of the brain having chronic tissue hypoxia. Therefore, this work investigated differences in hyperoxic response and regional cerebral oxygenation between anemic and healthy subjects. METHODS: A cohort of 38 sickle cell disease subjects (age 22 ± 8 years, female 39%), 25 non-sickle anemic subjects (age 25 ± 11 years, female 52%), and 31 healthy controls (age 25 ± 10 years, female 68%) were examined. A hyperoxic gas challenge was performed with concurrent acquisition of blood oxygen level-dependent (BOLD) MRI and near-infrared spectroscopy (NIRS). In addition to hyperoxia-induced changes in BOLD and NIRS, global measurements of cerebral blood flow, oxygen delivery, and cerebral metabolic rate of oxygen were obtained and compared between the three groups. RESULTS: Regional BOLD changes were not able to identify brain regions of flow limitation in chronically anemic patients. Higher blood oxygen content and tissue oxygenation were observed during hyperoxia gas challenge. Both control and anemic groups demonstrated lower blood flow, oxygen delivery, and metabolic rate compared to baseline, but the oxygen metabolism in anemic subjects were abnormally low during hyperoxic exposure. CONCLUSION: These results indicated that hyperoxic respiratory challenge could not be used to identify chronically ischemic brain. Furthermore, the low hyperoxia-induced metabolic rate suggested potential negative effects of prolonged oxygen therapy and required further studies to evaluate the risk for hyperoxia-induced oxygen toxicity and cerebral dysfunction.

Tract-specific analysis and neurocognitive functioning in sickle cell patients without history of overt stroke.

INTRODUCTION: Sickle cell disease (SCD) is a hereditary blood disorder in which the oxygen-carrying hemoglobin molecule in red blood cells is abnormal. SCD patients are at increased risks for strokes and neurocognitive deficit, even though neurovascular screening and treatments have lowered the rate of overt strokes. Tract-specific analysis (TSA) is a statistical method to evaluate microstructural WM damage in neurodegenerative disorders, using diffusion tensor imaging (DTI). METHODS: We utilized TSA and compared 11 major brain WM tracts between SCD patients with no history of overt stroke, anemic controls, and healthy controls. We additionally examined the relationship between the most commonly used DTI metric of WM tracts and neurocognitive performance in the SCD patients and healthy controls. RESULTS: Disruption of WM microstructure orientation-dependent metrics for the SCD patients was found in the genu of the corpus callosum (CC), cortico-spinal tract, inferior fronto-occipital fasciculus, right inferior longitudinal fasciculus, superior longitudinal fasciculus, and left uncinate fasciculus. Neurocognitive performance indicated slower processing speed and lower response inhibition skills in SCD patients compared to controls. TSA abnormalities in the CC were significantly associated with measures of processing speed, working memory, and executive functions. CONCLUSION: Decreased DTI-derived metrics were observed on six tracts in chronically anemic patients, regardless of anemia subtype, while two tracks with decreased measures were unique to SCD patients. Patients with WMHs had more significant FA abnormalities. Decreased FA values in the CC significantly correlated with all nine neurocognitive tests, suggesting a critical importance for CC in core neurocognitive processes.

White matter abnormalities in depression: A categorical and phenotypic diffusion MRI study.

Mood depressive disorder is one of the most disabling chronic diseases with a high rate of everyday life disability that affects 350 million people around the world. Recent advances in neuroimaging have reported widespread structural abnormalities, suggesting a dysfunctional frontal-limbic circuit involved in the pathophysiological mechanisms of depression. However, a variety of different white matter regions has been implicated and is sought to suffer from lack of reproducibility of such categorical-based biomarkers. These inconsistent results might be attributed to various factors: actual categorical definition of depression as well as clinical phenotype variability. In this study, we 1/ examined WM changes in a large cohort (114 patients) compared to a healthy control group and 2/ sought to identify specific WM alterations in relation to specific depressive phenotypes such as anhedonia (i.e. lack of pleasure), anxiety and psychomotor retardation -three core symptoms involved in depression. Consistent with previous studies, reduced white matter was observed in the genu of the corpus callosum extending to the inferior fasciculus and posterior thalamic radiation, confirming a frontal-limbic circuit abnormality. Our analysis also reported other patterns of increased fractional anisotropy and axial diffusivity as well as decreased apparent diffusion coefficient and radial diffusivity in the splenium of the corpus callosum and posterior limb of the internal capsule. Moreover, a positive correlation between FA and anhedonia was found in the superior longitudinal fasciculus as well as a negative correlation in the cingulum. Then, the analysis of the anxiety and diffusion metric revealed that increased anxiety was associated with greater FA values in genu and splenium of corpus callosum, anterior corona radiata and posterior thalamic radiation. Finally, the motor retardation analysis showed a correlation between increased Widlöcher depressive retardation scale scores and reduced FA in the body and genu of the corpus callosum, fornix, and superior striatum. Through this twofold approach (categorical and phenotypic), this study has underlined the need to move forward to a symptom-based research area of biomarkers, which help to understand the pathophysiology of mood depressive disorders and to stratify precise phenotypes of depression with targeted therapeutic strategies.

Graph Lasso-Based Test for Evaluating Functional Brain Connectivity in Sickle Cell Disease.

Sickle cell disease (SCD) is a vascular disorder that is often associated with recurrent ischemia-reperfusion injury, anemia, vasculopathy, and strokes. These cerebral injuries are associated with neurological dysfunction, limiting the full developing potential of the patient. However, recent large studies of SCD have demonstrated that cognitive impairment occurs even in the absence of brain abnormalities on conventional magnetic resonance imaging (MRI). These observations support an emerging consensus that brain injury in SCD is diffuse and that conventional neuroimaging often underestimates the extent of injury. In this article, we postulated that alterations in the cerebral connectivity may constitute a sensitive biomarker of SCD severity. Using functional MRI, a connectivity study analyzing the SCD patients individually was performed. First, a robust learning scheme based on graphical lasso model and Fréchet mean was used for estimating a consistent descriptor of healthy brain connectivity. Then, we tested a statistical method that provides an individual index of similarity between this healthy connectivity model and each SCD patient's connectivity matrix. Our results demonstrated that the reference connectivity model was not appropriate to model connectivity for only 4 out of 27 patients. After controlling for the gender, two separate predictors of this individual similarity index were the anemia (p = 0.02) and white matter hyperintensities (WMH) (silent stroke) (p = 0.03), so that patients with low hemoglobin level or with WMH have the least similarity to the reference connectivity model. Further studies are required to determine whether the resting-state connectivity changes reflect pathological changes or compensatory responses to chronic anemia.

Contrasting resting-state fMRI abnormalities from sickle and non-sickle anemia.

Sickle cell disease (SCD) is a chronic blood disorder that is often associated with acute and chronic cerebrovascular complications, including strokes and impaired cognition. Using functional resting state magnetic resonance images, we performed whole-brain analysis of the amplitude of low frequency fluctuations (ALFF), to detect areas of spontaneous blood oxygenation level dependent signal across brain regions. We compared the ALFF of 20 SCD patients to that observed in 19 healthy, age and ethnicity-matched, control subjects. Significant differences were found in several brain regions, including the insula, precuneus, anterior cingulate cortex and medial superior frontal gyrus. To identify the ALFF differences resulting from anemia alone, we also compared the ALFF of SCD patients to that observed in 12 patients having comparable hemoglobin levels but lacking sickle hemoglobin. Increased ALFF in the orbitofrontal cortex and the anterior and posterior cingulate cortex and decreased ALFF in the frontal pole, cerebellum and medial superior frontal gyrus persisted after accounting for the effect of anemia. The presence of white matter hyperintensities was associated with depressed frontal and medial superior frontal gyri activity in the SCD subjects. Decreased ALFF in the frontal lobe was correlated with decreased verbal fluency and cognitive flexibility. These findings may lead to a better understanding of the pathophysiology of SCD.

FUNCTIONAL CONNECTIVITY ANALYSIS FOR THALASSEMIA DISEASE BASED ON A GRAPHICAL LASSO MODEL.

Thalassemia is a congenital disorder of hemoglobin synthesis which can lead to thromboembolic events and stroke in the brain. In this work we propose to use a functional connectivity model to discriminate between control and diseased subjects. Our connectivity measure is based on functional magnetic resonance imaging, and hence common variations of the blood oxygenation level in spatially distant areas. Analyzing this connectivity could highlight abnormal neuronal activation and provide us with a descriptor (bio-marker) of the disease. To estimate the connectivity, we propose a robust learning scheme based on the graphical lasso model, whose hyperparameter is validated within a cross-validation scheme. To analyze model fit, we transfer the mean connectivity from the control group to the thalassemic patient group. Our null hypothesis is that the model learned on control subjects is perfectly adequate (in the maximum likelihood sense) to describe the patients. The results of the permutation test suggest that the some patients with thalassemia do not have the same connectivity structure as the control.

BOLD delay times using group delay in sickle cell disease.

Sickle cell disease (SCD) is an inherited blood disorder that effects red blood cells, which can lead to vasoocclusion, ischemia and infarct. This disease often results in neurological damage and strokes, leading to morbidity and mortality. Functional Magnetic Resonance Imaging (fMRI) is a non-invasive technique for measuring and mapping the brain activity. Blood Oxygenation Level-Dependent (BOLD) signals contain also information about the neurovascular coupling, vascular reactivity, oxygenation and blood propagation. Temporal relationship between BOLD fluctuations in different parts of the brain provides also a mean to investigate the blood delay information. We used the induced desaturation as a label to profile transit times through different brain areas, reflecting oxygen utilization of tissue. In this study, we aimed to compare blood flow propagation delay times between these patients and healthy subjects in areas vascularized by anterior, middle and posterior cerebral arteries. In a group comparison analysis with control subjects, BOLD changes in these areas were found to be almost simultaneous and shorter in the SCD patients, because of their increased brain blood flow. Secondly, the analysis of a patient with a stenosis on the anterior cerebral artery indicated that signal of the area vascularized by this artery lagged the MCA signal. These findings suggest that sickle cell disease causes blood propagation modifications, and that these changes could be used as a biomarker of vascular damage.

The 3D EdgeRunner Pipeline: A Novel Shape-Based Analysis for Neoplasms Characterization.

The characterization of tumors after being imaged is currently a qualitative process performed by skilled professionals. If we can aid their diagnosis by identifying quantifiable features associated with tumor classification, we may avoid invasive procedures such as biopsies and enhance efficiency. The aim of this paper is to describe the 3D EdgeRunner Pipeline which characterizes the shape of a tumor. Shape analysis is relevant as malignant tumors tend to be more lobular and benign ones tare generally more symmetrical. The method described considers the distance from each point on the edge of the tumor to the centre of a synthetically created field of view. The method then determines coordinates where the measured distances are rapidly changing (peaks) using a second derivative found by five point differentiation. The list of coordinates considered to be peaks can then be used as statistical data to compare tumors quantitatively. We have found this process effectively captures the peaks on a selection of kidney tumors.

Low-frequency fluctuation amplitude analysis of resting-state fMRI in sickle cell disease.

Sickle cell disease may result in neurological damage and strokes, leading to morbidity and mortality. Currently, there are no dependable biomarkers to predict impending strokes. In this study, we analyzed neuronal processes at resting state and more particularly how this disease affects the default mode network. The amplitude of low frequency fluctuations was used to reflect areas of spontaneous BOLD signal across brain regions. We compared the activations of sickle cell disease patients to a control group using variance analysis and t-test. Significant regional differences among the two groups were observed, especially in the default mode network areas and cortical regions near large cerebral arteries. These findings suggest that sickle cell disease causes activation modifications near vessels, and these changes could be used as a biomarker of the disease.

Tract specific analysis in patients with sickle cell disease.

Sickle cell disease (SCD) is a hereditary blood disorder in which the oxygen-carrying hemoglobin molecule in red blood cells is abnormal. It affects numerous people in the world and leads to a shorter life span, pain, anemia, serious infections and neurocognitive decline. Tract-Specific Analysis (TSA) is a statistical method to evaluate white matter alterations due to neurocognitive diseases, using diffusion tensor magnetic resonance images. Here, for the first time, TSA is used to compare 11 major brain white matter (WM) tracts between SCD patients and age-matched healthy subjects. Alterations are found in the corpus callosum (CC), the cortico-spinal tract (CST), inferior fronto-occipital fasciculus (IFO), inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus (SLF), and uncinated fasciculus (UNC). Based on previous studies on the neurocognitive functions of these tracts, the significant areas found in this paper might be related to several cognitive impairments and depression, both of which are observed in SCD patients.

On feature extraction and classification in prostate cancer radiotherapy using tensor decompositions.

External beam radiotherapy is commonly prescribed for prostate cancer. Although new radiation techniques allow high doses to be delivered to the target, the surrounding healthy organs (rectum and bladder) may suffer from irradiation, which might produce undesirable side-effects. Hence, the understanding of the complex toxicity dose-volume effect relationships is crucial to adapt the treatment, thereby decreasing the risk of toxicity. In this paper, we introduce a novel method to classify patients at risk of presenting rectal bleeding based on a Deterministic Multi-way Analysis (DMA) of three-dimensional planned dose distributions across a population. After a non-rigid spatial alignment of the anatomies applied to the dose distributions, the proposed method seeks for two bases of vectors representing bleeding and non bleeding patients by using the Canonical Polyadic (CP) decomposition of two fourth order arrays of the planned doses. A patient is then classified according to its distance to the subspaces spanned by both bases. A total of 99 patients treated for prostate cancer were used to analyze and test the performance of the proposed approach, named CP-DMA, in a leave-one-out cross validation scheme. Results were compared with supervised (linear discriminant analysis, support vector machine, K-means, K-nearest neighbor) and unsupervised (recent principal component analysis-based algorithm, and multidimensional classification method) approaches based on the registered dose distribution. Moreover, CP-DMA was also compared with the Normal Tissue Complication Probability (NTCP) model. The CP-DMA method allowed rectal bleeding patients to be classified with good specificity and sensitivity values, outperforming the classical approaches.

A Novel Classification Method for Prediction of Rectal Bleeding in Prostate Cancer Radiotherapy Based on a Semi-Nonnegative ICA of 3D Planned Dose Distributions.

The understanding of dose/side-effects relationships in prostate cancer radiotherapy is crucial to define appropriate individual's constraints for the therapy planning. Most of the existing methods to predict side-effects do not fully exploit the rich spatial information conveyed by the three-dimensional planned dose distributions. We propose a new classification method for three-dimensional individuals' doses, based on a new semi-nonnegative ICA algorithm to identify patients at risk of presenting rectal bleeding from a population treated for prostate cancer. The method first determines two bases of vectors from the population data: the two bases span vector subspaces, which characterize patients with and without rectal bleeding, respectively. The classification is then achieved by calculating the distance of a given patient to the two subspaces. The results, obtained on a cohort of 87 patients (at two year follow-up) treated with radiotherapy, showed high performance in terms of sensitivity and specificity.