Frequency domain analysis of time-resolved fluorescence measurements (TRFM) is an extremely rapid technique for medical diagnostics thanks to its unique sensitivity to a wide variety of physical and chemical features. Nevertheless, the determination of the underlying fluorescence lifetime (FLT) data of samples by their frequency response data (FRD), demands fitting algorithms. Therefore, the interpretation of the precise changes in the FLT of complex environments in term of biochemical processes is a challenge as it involves uncertainties associated with the chosen fitting algorithm. This research suggests a novel characterization procedure based on the squared distance (D2) between the FRD of the samples that avoid the inherent blurring caused by the transformation of the FRD into FLT data. The D2 approach was validated through simulated data of 6 classes with similar FLT characteristics, where the accuracy of D2 classification was about 96%. In addition, this approach was tested on experimental FRD from 43 individual samples that their preliminary physician diagnosis divided them into 4 groups: 5 healthy samples served as controls, 9 samples diagnosed with diverse types of bacteria, 16 samples diagnosed with diverse types of viruses and 13 samples were negatives to any bacterial or viral infection, although presenting related symptoms. Using the D2 analysis, the classification of 28/30 matched the physician diagnosis and the classification of 41/43 samples matched earlier report. In conclusion, this work demonstrated that the D2 model can aid in disease identification and increase the specificity and sensitivity of conventional medical procedures or TRFM-based diagnosis.
Characterizing different pathological states in the cellular level with a high throughput diagnostic tool is one of the main interests today. In previously works, we demonstrated how the frequency domain (FD) fluorescence lifetime imaging microscopy (FLIM) technique could be utilized to implement that in variety of examples. Among them was to classify between different chromosomal abnormalities in patients with b-cell chronic lymphocytic leukemia (B-CLL) and between metastatic cells and inflammation cells in the cerebral spinal fluid of patients with Medulloblastoma. This research describes the use of FD-FLIM system to differentiate between patients diagnosed without any disease (controls) that showed a normal median FLT (2.65±0.11ns) and patients diagnosed with inflammation (viruses and bacteria) that showed a prolong median FLT and a larger distribution (3.18±0.44ns in viruses and 3.28±0.45ns). The study group of this research included 43 samples divided into 4 groups: 9 samples diagnosed with different types of bacteria, 16 samples diagnosed with different types of viruses, 12 samples diagnosed with no any bacteria or virus and 5 samples diagnosed without any disease that served as controls.
Furthermore, we studied a group of patients without detection of inflammation that were sick. We found that this group was divided into two groups; one group had the same median FLT as the controls, and the other group had the same median FLT as the inflammatory patients. As a result, we believe the FD-FLIM system can suggest a faster and more accurate diagnostic technique than the methods used today. The correlations of the FLT distribution pattern with the different groups are presented.
Brain tumors are the second leading cause of cancer-related deaths in children, after leukemia. Patients with cancer in the central nervous system have a very low recovery rate. Today known imaging and cytology techniques are not always sensitive enough for an early detection of both tumor and its metastatic spread, moreover the detection is generally limited, reviewer dependent and takes a relatively long time. Medulloblastoma (MB) is the most common malignant brain tumor in children. The aim of our talk is to present the frequency domain fluorescence lifetime imaging microscopy system as a possible method for an early detection of MB and its metastatic spread in the cerebrospinal fluids within the pediatric population.