Fig. 1: System overview, depicting the detection of CTC candidates based on a combination of microfluidic inertial enrichment, digital holographic microscopy signature, and immunofluorescence (IF) expression. | npj Biosensing

Fig. 1: System overview, depicting the detection of CTC candidates based on a combination of microfluidic inertial enrichment, digital holographic microscopy signature, and immunofluorescence (IF) expression.

From: Circulating tumor cell detection in cancer patients using in-flow deep learning holography

Fig. 1: System overview, depicting the detection of CTC candidates based on a combination of microfluidic inertial enrichment, digital holographic microscopy signature, and immunofluorescence (IF) expression.The alternative text for this image may have been generated using AI.

Samples begin as whole blood prior to microfluidic enrichment, during which red blood cells are primarily depleted while retaining CTCs and most WBCs. Subsequently, holograms of each cell and IF signal from the field-of-view as a whole are captured during passage through a second microfluidic chip. Detections in the IF signal for emitting cells are visible as broad peaks whose time-scale is inversely proportional to the frame rate (i.e., equivalent to the time taken for a cell to passage the field-of-view). Holograms pass through a neural network to classify each cell and detect CTCs, while the IF data can be used for further filtering operations for cell enumeration.

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