Characterization of brain tumor tissue with 1310 nm optical coherence tomography

Strenge, Paul; Lange, Birgit; Grill, Christin; Draxinger, Wolfgang; Danicke, Veit; Theisen-Kunde, Dirk; Handels, Heinz; Bonsanto, Matteo M.; Hagel, Christian; Huber, Robert; Brinkmann, Ralf

doi:10.1117/12.2578409

Cited by 5 publications

(5 citation statements)

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“…Moreover, it enables real-time 4D OCT applications, wherein increased speed can augment image quality and introduce vital functional contrast. This is particularly crucial for interactive clinical procedures or surgical navigation 31,32 .…”

Section: Abbreviationsmentioning

confidence: 99%

“…To achieve real-time, low-latency display for interactive positioning and aiming mode, we developed a specific software solution for handling OCT data. This real-time processing and visualization of OCT data are based on our custom in-house software designed for online graphical processing unit (GPU) accelerated OCT processing, referred to as "Luebeck University Real-time OCT" (LURO) navigation 31,32 . LURO enables the live display of the OCT rectoscope in Cartesian or polar coordinates.…”

Section: Optical Coherence Tomographymentioning

confidence: 99%

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High-resolution rectoscopy using MHz optical coherence tomography: a step towards real time 3D endoscopy

Schulte,

Göb,

Singh

et al. 2024

Sci Rep

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Colonoscopy and endoscopic ultrasound play pivotal roles in the assessment of rectal diseases, especially rectal cancer and inflammatory bowel diseases. Optical coherence tomography (OCT) offers a superior depth resolution, which is a critical factor for individualizing the therapeutic concept and evaluating the therapy response. We developed two distinct rectoscope prototypes, which were integrated into a 1300 nm MHz-OCT system constructed at our facility. The rapid rotation of the distal scanning probe at 40,000 revolutions per minute facilitates a 667 Hz OCT frame rate, enabling real-time endoscopic imaging of large areas. The performance of these OCT-rectoscopes was assessed in an ex vivo porcine colon and a post mortem human in-situ colon. The OCT-rectoscope consistently distinguished various layers of the intestinal wall, identified gut-associated lymphatic tissue, and visualized a rectal polyp during the imaging procedure with 3D-reconstruction in real time. Subsequent histological examination confirmed these findings. The body donor was preserved using an ethanol-glycerol-lysoformin-based technique for true-to-life tissue consistency. We could demonstrate that the novel MHZ-OCT-rectoscope effectively discriminates rectal wall layers and crucial tissue characteristics in a post mortem human colon in-situ. This real-time-3D-OCT holds promise as a valuable future diagnostic tool for assessing disease state and therapy response on-site in rectal diseases.

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Section: Abbreviationsmentioning

confidence: 99%

Section: Optical Coherence Tomographymentioning

confidence: 99%

High-resolution rectoscopy using MHz optical coherence tomography: a step towards real time 3D endoscopy

Schulte,

Göb,

Singh

et al. 2024

Sci Rep

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“…Several authors have described both qualitative (8,9) and quantitative (10) image properties that differ in healthy and diseased brain tissue. Thus, image interpretation requires high levels of viewer expertise and its accuracy has only been reported for ex vivo imaging on small patient cohorts, varying in sensitivity and specificity in the range of 90-100% and 76-96%, respectively (9)(10)(11)(12). Research on neurosurgical in vivo application, in contrast, is still mostly focused on feasibility (8,9,(13)(14)(15).…”

Section: Introductionmentioning

confidence: 99%

The neurosurgical benefit of contactless in vivo optical coherence tomography regarding residual tumor detection: A clinical study

et al. 2023

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PurposeIn brain tumor surgery, it is crucial to achieve complete tumor resection while conserving adjacent noncancerous brain tissue. Several groups have demonstrated that optical coherence tomography (OCT) has the potential of identifying tumorous brain tissue. However, there is little evidence on human in vivo application of this technology, especially regarding applicability and accuracy of residual tumor detection (RTD). In this study, we execute a systematic analysis of a microscope integrated OCT-system for this purpose.Experimental designMultiple 3-dimensional in vivo OCT-scans were taken at protocol-defined sites at the resection edge in 21 brain tumor patients. The system was evaluated for its intraoperative applicability. Tissue biopsies were obtained at these locations, labeled by a neuropathologist and used as ground truth for further analysis. OCT-scans were visually assessed with a qualitative classifier, optical OCT-properties were obtained and two artificial intelligence (AI)-assisted methods were used for automated scan classification. All approaches were investigated for accuracy of RTD and compared to common techniques.ResultsVisual OCT-scan classification correlated well with histopathological findings. Classification with measured OCT image-properties achieved a balanced accuracy of 85%. A neuronal network approach for scan feature recognition achieved 82% and an auto-encoder approach 85% balanced accuracy. Overall applicability showed need for improvement.ConclusionContactless in vivo OCT scanning has shown to achieve high values of accuracy for RTD, supporting what has well been described for ex vivo OCT brain tumor scanning, complementing current intraoperative techniques and even exceeding them in accuracy, while not yet in applicability.

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“…Alternative applications in neurosurgery include the use of intraoperative 3D-ultrasound and intraoperative MR-/CTimaging, both logistically complex to operate with [8][9][10][11][12]. Further, new methods to visualize brain tumor tissue are, e.g., optical coherence tomography (OCT) or Raman histology, which are usually associated with a restructuring of the operating workflow [13][14][15][16][17]. Other studies indicate that healthy brain and tumor tissue differ from each other based on their mechanical properties, such as elasticity [18][19][20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Toward intraoperative tissue classification: exploiting signal feedback from an ultrasonic aspirator for brain tissue differentiation

Bockelmann

Schetelig²,

Kesslau³

et al. 2022

Int J CARS

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Purpose During brain tumor surgery, care must be taken to accurately differentiate between tumorous and healthy tissue, as inadvertent resection of functional brain areas can cause severe consequences. Since visual assessment can be difficult during tissue resection, neurosurgeons have to rely on the mechanical perception of tissue, which in itself is inherently challenging. A commonly used instrument for tumor resection is the ultrasonic aspirator, whose system behavior is already dependent on tissue properties. Using data recorded during tissue fragmentation, machine learning-based tissue differentiation is investigated for the first time utilizing ultrasonic aspirators. Methods Artificial tissue model with two different mechanical properties is synthesized to represent healthy and tumorous tissue. 40,000 temporal measurement points of electrical data are recorded in a laboratory environment using a CNC machine. Three different machine learning approaches are applied: a random forest (RF), a fully connected neural network (NN) and a 1D convolutional neural network (CNN). Additionally, different preprocessing steps are investigated. Results Fivefold cross-validation is conducted over the data and evaluated with the metrics F1, accuracy, positive predictive value, true positive rate and area under the receiver operating characteristic. Results show a generally good performance with a mean F1 of up to 0.900 ± 0.096 using a NN approach. Temporal information indicates low impact on classification performance, while a low-pass filter preprocessing step leads to superior results. Conclusion This work demonstrates the first steps to successfully differentiate healthy brain and tumor tissue using an ultrasonic aspirator during tissue fragmentation. Evaluation shows that both neural network-based classifiers outperform the RF. In addition, the effects of temporal dependencies are found to be reduced when adequate data preprocessing is performed. To ensure subsequent implementation in the clinic, handheld ultrasonic aspirator use needs to be investigated in the future as well as the addition of data to reflect tissue diversity during neurosurgical operations.

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Characterization of brain tumor tissue with 1310 nm optical coherence tomography

Cited by 5 publications

References 0 publications

High-resolution rectoscopy using MHz optical coherence tomography: a step towards real time 3D endoscopy

High-resolution rectoscopy using MHz optical coherence tomography: a step towards real time 3D endoscopy

The neurosurgical benefit of contactless in vivo optical coherence tomography regarding residual tumor detection: A clinical study

Toward intraoperative tissue classification: exploiting signal feedback from an ultrasonic aspirator for brain tissue differentiation

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