13 research outputs found
Current role of machine learning and radiogenomics in precision neuro-oncology
In the past few years, artificial intelligence (AI) has been increasingly used to create tools that can enhance workflow in medicine. In particular, neuro-oncology has benefited from the use of AI and especially machine learning (ML) and radiogenomics, which are subfields of AI. ML can be used to develop algorithms that dynamically learn from available medical data in order to automatically do specific tasks. On the other hand, radiogenomics can identify relationships between tumor genetics and imaging features, thus possibly giving new insights into the pathophysiology of tumors. Therefore, ML and radiogenomics could help treatment tailoring, which is crucial in personalized neuro-oncology. The aim of this review is to illustrate current and possible future applications of ML and radiomics in neuro-oncology
Quantitative Analysis of Radiation-Associated Parenchymal Lung Change
Radiation-induced lung damage (RILD) is a common consequence of thoracic radiotherapy (RT). We present here a novel classification of the parenchymal features of RILD. We developed a deep learning algorithm (DLA) to automate the delineation of 5 classes of parenchymal texture of increasing density.
200 scans were used to train and validate the network and the remaining 30 scans were used as a hold-out test set. The DLA automatically labelled the data with Dice Scores of 0.98, 0.43, 0.26, 0.47 and 0.92 for the 5 respective classes.
Qualitative evaluation showed that the automated labels were acceptable in over 80% of cases for all tissue classes, and achieved similar ratings to the manual labels. Lung registration was performed and the effect of radiation dose on each tissue class and correlation with respiratory outcomes was assessed. The change in volume of each tissue class over time generated by manual and automated segmentation was calculated. The 5 parenchymal classes showed distinct temporal patterns
We quantified the volumetric change in textures after radiotherapy and correlate these with radiotherapy dose and respiratory outcomes.
The effect of local dose on tissue class revealed a strong dose-dependent relationship
We have developed a novel classification of parenchymal changes associated with RILD that show a convincing dose relationship. The tissue classes are related to both global and local dose metrics, and have a distinct evolution over time. Although less strong, there is a relationship between the radiological texture changes we can measure and respiratory outcomes, particularly the MRC score which directly represents a patient’s functional status. We have demonstrated the potential of using our approach to analyse and understand the morphological and functional evolution of RILD in greater detail than previously possible
The Role of Arterial Spin Labelling (ASL) in Classification of Primary Adult Gliomas
Currently, the histological biopsy is the gold standard for classifying gliomas using the most recent histomolecular features. However, this process is both invasive and challenging, mainly when the lesion is in eloquent brain regions. Considering the complex interaction between the presence of the isocitrate dehydrogenase (IDH)-mutation, the upregulation of the hypoxia-induced factor (HIF), the neo-angiogenesis and the increased cellularity, perfusion MRI may be used indirectly for gliomas staging and further to predict the presence of key mutations, such as IDH. Recently, several studies have reported the subsidiary role of perfusion MRI in the prediction of gliomas histomolecular class. The three most common perfusion MRI methods are dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE) and arterial spin labelling (ASL). Both DSC and DCE use exogenous contrast agent (CA) while ASL uses magnetically labelled blood water as an inherently diffusible tracer. ASL has begun to feature more prominently in clinical settings, as this method eliminates the need for CA and facilitates quantification of absolute cerebral blood flow (CBF). As a non-invasive, CA-free test, it can also be performed repeatedly where necessary. This makes it ideal for vulnerable patients, e.g. post-treatment oncological patients, who have reduced tolerance for high rate contrast injections and those suffering from renal insufficiency. This thesis performed a systematic review and critical appraisal of the existing ASL techniques for brain perfusion estimation, followed by a further systematic review and meta-analysis of the published studies, which have quantitatively assessed the diagnostic performance of ASL for grading preoperative adult gliomas. The repeatability of absolute tumour blood flow (aTBF) and relative TBF (rTBF) ASL-derived measurements were estimated to investigate the reliability of these ASL biomarkers in the clinical routine. Finally, utilising the radiomics pipeline analysis, the added diagnostic performance of ASL compared with CA-based MRI perfusion techniques, including DSC and DCE, and diffusion-weighted imaging (DWI) was investigated for glioma class prediction according to the WHO-2016 classification
Characterization of alar ligament on 3.0T MRI: a cross-sectional study in IIUM Medical Centre, Kuantan
INTRODUCTION: The main purpose of the study is to compare the normal anatomy of alar
ligament on MRI between male and female. The specific objectives are to assess the prevalence
of alar ligament visualized on MRI, to describe its characteristics in term of its course, shape and
signal homogeneity and to find differences in alar ligament signal intensity between male and
female. This study also aims to determine the association between the heights of respondents
with alar ligament signal intensity and dimensions.
MATERIALS & METHODS: 50 healthy volunteers were studied on 3.0T MR scanner
Siemens Magnetom Spectra using 2-mm proton density, T2 and fat-suppression sequences. Alar
ligament is depicted in 3 planes and the visualization and variability of the ligament courses,
shapes and signal intensity characteristics were determined. The alar ligament dimensions were
also measured.
RESULTS: Alar ligament was best depicted in coronal plane, followed by sagittal and axial
planes. The orientations were laterally ascending in most of the subjects (60%), predominantly
oval in shaped (54%) and 67% showed inhomogenous signal. No significant difference of alar
ligament signal intensity between male and female respondents. No significant association was
found between the heights of the respondents with alar ligament signal intensity and dimensions.
CONCLUSION: Employing a 3.0T MR scanner, the alar ligament is best portrayed on coronal
plane, followed by sagittal and axial planes. However, tremendous variability of alar ligament as
depicted in our data shows that caution needs to be exercised when evaluating alar ligament,
especially during circumstances of injury
Case series of breast fillers and how things may go wrong: radiology point of view
INTRODUCTION: Breast augmentation is a procedure opted by women to overcome sagging
breast due to breastfeeding or aging as well as small breast size. Recent years have shown the
emergence of a variety of injectable materials on market as breast fillers. These injectable
breast fillers have swiftly gained popularity among women, considering the minimal
invasiveness of the procedure, nullifying the need for terrifying surgery. Little do they know
that the procedure may pose detrimental complications, while visualization of breast
parenchyma infiltrated by these fillers is also deemed substandard; posing diagnostic
challenges. We present a case series of three patients with prior history of hyaluronic acid and
collagen breast injections.
REPORT: The first patient is a 37-year-old lady who presented to casualty with worsening
shortness of breath, non-productive cough, central chest pain; associated with fever and chills
for 2-weeks duration. The second patient is a 34-year-old lady who complained of cough, fever
and haemoptysis; associated with shortness of breath for 1-week duration. CT in these cases
revealed non thrombotic wedge-shaped peripheral air-space densities.
The third patient is a 37‐year‐old female with right breast pain, swelling and redness for 2-
weeks duration. Previous collagen breast injection performed 1 year ago had impeded
sonographic visualization of the breast parenchyma. MRI breasts showed multiple non-
enhancing round and oval shaped lesions exhibiting fat intensity.
CONCLUSION: Radiologists should be familiar with the potential risks and hazards as well
as limitations of imaging posed by breast fillers such that MRI is required as problem-solving
tool