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Veluponnar D, de Boer LL, Dashtbozorg B, Jong LJS, Geldof F, Guimaraes MDS, Sterenborg HJCM, Vrancken-Peeters MJTFD, van Duijnhoven F, Ruers T. Margin assessment during breast conserving surgery using diffuse reflectance spectroscopy. J Biomed Opt 2024; 29:045006. [PMID: 38665316 PMCID: PMC11045169 DOI: 10.1117/1.jbo.29.4.045006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2024] [Revised: 04/03/2024] [Accepted: 04/08/2024] [Indexed: 04/28/2024]
Abstract
Significance During breast-conserving surgeries, it is essential to evaluate the resection margins (edges of breast specimen) to determine whether the tumor has been removed completely. In current surgical practice, there are no methods available to aid in accurate real-time margin evaluation. Aim In this study, we investigated the diagnostic accuracy of diffuse reflectance spectroscopy (DRS) combined with tissue classification models in discriminating tumorous tissue from healthy tissue up to 2 mm in depth on the actual resection margin of in vivo breast tissue. Approach We collected an extensive dataset of DRS measurements on ex vivo breast tissue and in vivo breast tissue, which we used to develop different classification models for tissue classification. Next, these models were used in vivo to evaluate the performance of DRS for tissue discrimination during breast conserving surgery. We investigated which training strategy yielded optimum results for the classification model with the highest performance. Results We achieved a Matthews correlation coefficient of 0.76, a sensitivity of 96.7% (95% CI 95.6% to 98.2%), a specificity of 90.6% (95% CI 86.3% to 97.9%) and an area under the curve of 0.98 by training the optimum model on a combination of ex vivo and in vivo DRS data. Conclusions DRS allows real-time margin assessment with a high sensitivity and specificity during breast-conserving surgeries.
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Affiliation(s)
- Dinusha Veluponnar
- Netherlands Cancer Institute, Antoni van Leeuwenhoek, Department of Surgery, Image-Guided Surgery, Amsterdam, The Netherlands
- University of Twente, Department of Nanobiophysics, Faculty of Science and Technology, Enschede, The Netherlands
| | - Lisanne L. de Boer
- Netherlands Cancer Institute, Antoni van Leeuwenhoek, Department of Surgery, Image-Guided Surgery, Amsterdam, The Netherlands
| | - Behdad Dashtbozorg
- Netherlands Cancer Institute, Antoni van Leeuwenhoek, Department of Surgery, Image-Guided Surgery, Amsterdam, The Netherlands
| | - Lynn-Jade S. Jong
- Netherlands Cancer Institute, Antoni van Leeuwenhoek, Department of Surgery, Image-Guided Surgery, Amsterdam, The Netherlands
- University of Twente, Department of Nanobiophysics, Faculty of Science and Technology, Enschede, The Netherlands
| | - Freija Geldof
- Netherlands Cancer Institute, Antoni van Leeuwenhoek, Department of Surgery, Image-Guided Surgery, Amsterdam, The Netherlands
- University of Twente, Department of Nanobiophysics, Faculty of Science and Technology, Enschede, The Netherlands
| | - Marcos Da Silva Guimaraes
- Netherlands Cancer Institute, Antoni van Leeuwenhoek, Department of Pathology, Amsterdam, The Netherlands
| | - Henricus J. C. M. Sterenborg
- Amsterdam University Medical Center, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
| | | | - Frederieke van Duijnhoven
- Netherlands Cancer Institute, Antoni van Leeuwenhoek, Department of Surgery, Image-Guided Surgery, Amsterdam, The Netherlands
| | - Theo Ruers
- Netherlands Cancer Institute, Antoni van Leeuwenhoek, Department of Surgery, Image-Guided Surgery, Amsterdam, The Netherlands
- University of Twente, Department of Nanobiophysics, Faculty of Science and Technology, Enschede, The Netherlands
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Veluponnar D, Dashtbozorg B, Jong LJS, Geldof F, Da Silva Guimaraes M, Vrancken Peeters MJTFD, van Duijnhoven F, Sterenborg HJCM, Ruers TJM, de Boer LL. Diffuse reflectance spectroscopy for accurate margin assessment in breast-conserving surgeries: importance of an optimal number of fibers. Biomed Opt Express 2023; 14:4017-4036. [PMID: 37799696 PMCID: PMC10549728 DOI: 10.1364/boe.493179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 06/05/2023] [Accepted: 06/05/2023] [Indexed: 10/07/2023]
Abstract
During breast-conserving surgeries, it remains challenging to accomplish adequate surgical margins. We investigated different numbers of fibers for fiber-optic diffuse reflectance spectroscopy to differentiate tumorous breast tissue from healthy tissue ex vivo up to 2 mm from the margin. Using a machine-learning classification model, the optimal performance was obtained using at least three emitting fibers (Matthew's correlation coefficient (MCC) of 0.73), which was significantly higher compared to the performance of using a single-emitting fiber (MCC of 0.48). The percentage of correctly classified tumor locations varied from 75% to 100% depending on the tumor percentage, the tumor-margin distance and the number of fibers.
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Affiliation(s)
- Dinusha Veluponnar
- Department of Surgery,
Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Department of Nanobiophysics, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
| | - Behdad Dashtbozorg
- Department of Surgery,
Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Lynn-Jade S. Jong
- Department of Surgery,
Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Department of Nanobiophysics, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
| | - Freija Geldof
- Department of Surgery,
Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Department of Nanobiophysics, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
| | - Marcos Da Silva Guimaraes
- Department of Pathology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | | | - Frederieke van Duijnhoven
- Department of Surgery,
Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Henricus J. C. M. Sterenborg
- Department of Surgery,
Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, Meibergdreef 9, 1105 AZ Amsterdam, Netherlands
| | - Theo J. M. Ruers
- Department of Surgery,
Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Department of Nanobiophysics, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
| | - Lisanne L. de Boer
- Department of Surgery,
Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
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Veluponnar D, de Boer LL, Geldof F, Jong LJS, Da Silva Guimaraes M, Vrancken Peeters MJTFD, van Duijnhoven F, Ruers T, Dashtbozorg B. Toward Intraoperative Margin Assessment Using a Deep Learning-Based Approach for Automatic Tumor Segmentation in Breast Lumpectomy Ultrasound Images. Cancers (Basel) 2023; 15:cancers15061652. [PMID: 36980539 PMCID: PMC10046373 DOI: 10.3390/cancers15061652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 03/01/2023] [Accepted: 03/06/2023] [Indexed: 03/30/2023] Open
Abstract
There is an unmet clinical need for an accurate, rapid and reliable tool for margin assessment during breast-conserving surgeries. Ultrasound offers the potential for a rapid, reproducible, and non-invasive method to assess margins. However, it is challenged by certain drawbacks, including a low signal-to-noise ratio, artifacts, and the need for experience with the acquirement and interpretation of images. A possible solution might be computer-aided ultrasound evaluation. In this study, we have developed new ensemble approaches for automated breast tumor segmentation. The ensemble approaches to predict positive and close margins (distance from tumor to margin ≤ 2.0 mm) in the ultrasound images were based on 8 pre-trained deep neural networks. The best optimum ensemble approach for segmentation attained a median Dice score of 0.88 on our data set. Furthermore, utilizing the segmentation results we were able to achieve a sensitivity of 96% and a specificity of 76% for predicting a close margin when compared to histology results. The promising results demonstrate the capability of AI-based ultrasound imaging as an intraoperative surgical margin assessment tool during breast-conserving surgery.
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Affiliation(s)
- Dinusha Veluponnar
- Department of Surgery, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Department of Nanobiophysics, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
| | - Lisanne L de Boer
- Department of Surgery, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Freija Geldof
- Department of Surgery, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Lynn-Jade S Jong
- Department of Surgery, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Marcos Da Silva Guimaraes
- Department of Pathology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | | | - Frederieke van Duijnhoven
- Department of Surgery, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Theo Ruers
- Department of Surgery, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Department of Nanobiophysics, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
| | - Behdad Dashtbozorg
- Department of Surgery, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
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de Boer LL, Kho E, Van de Vijver KK, Vranken Peeters MJTFD, van Duijnhoven F, Hendriks BHW, Sterenborg HJCM, Ruers TJM. Optical tissue measurements of invasive carcinoma and ductal carcinoma in situ for surgical guidance. Breast Cancer Res 2021; 23:59. [PMID: 34022928 PMCID: PMC8141169 DOI: 10.1186/s13058-021-01436-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 05/05/2021] [Indexed: 11/10/2022] Open
Abstract
Background Although the incidence of positive resection margins in breast-conserving surgery has decreased, both incomplete resection and unnecessary large resections still occur. This is especially the case in the surgical treatment of ductal carcinoma in situ (DCIS). Diffuse reflectance spectroscopy (DRS), an optical technology based on light tissue interactions, can potentially characterize tissue during surgery thereby guiding the surgeon intraoperatively. DRS has shown to be able to discriminate pure healthy breast tissue from pure invasive carcinoma (IC) but limited research has been done on (1) the actual optical characteristics of DCIS and (2) the ability of DRS to characterize measurements that are a mixture of tissue types. Methods In this study, DRS spectra were acquired from 107 breast specimens from 107 patients with proven IC and/or DCIS (1488 measurement locations). With a generalized estimating equation model, the differences between the DRS spectra of locations with DCIS and IC and only healthy tissue were compared to see if there were significant differences between these spectra. Subsequently, different classification models were developed to be able to predict if the DRS spectrum of a measurement location represented a measurement location with “healthy” or “malignant” tissue. In the development and testing of the models, different definitions for “healthy” and “malignant” were used. This allowed varying the level of homogeneity in the train and test data. Results It was found that the optical characteristics of IC and DCIS were similar. Regarding the classification of tissue with a mixture of tissue types, it was found that using mixed measurement locations in the development of the classification models did not tremendously improve the accuracy of the classification of other measurement locations with a mixture of tissue types. The evaluated classification models were able to classify measurement locations with > 5% malignant cells with a Matthews correlation coefficient of 0.41 or 0.40. Some models showed better sensitivity whereas others had better specificity. Conclusion The results suggest that DRS has the potential to detect malignant tissue, including DCIS, in healthy breast tissue and could thus be helpful for surgical guidance. Supplementary Information The online version contains supplementary material available at 10.1186/s13058-021-01436-5.
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Affiliation(s)
- Lisanne L de Boer
- Department of Surgery, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Postbus 90203, 1006, Amsterdam, BE, Netherlands.
| | - Esther Kho
- Department of Surgery, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Postbus 90203, 1006, Amsterdam, BE, Netherlands
| | - Koen K Van de Vijver
- Department of Pathology, Ghent University Hospital, and Cancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium
| | | | - Frederieke van Duijnhoven
- Department of Surgery, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Postbus 90203, 1006, Amsterdam, BE, Netherlands
| | - Benno H W Hendriks
- Philips Research, In-body Systems Group, Eindhoven, Netherlands.,Biomechanical Engineering Department, Delft University of Technology, Delft, The Netherlands
| | - Henricus J C M Sterenborg
- Department of Surgery, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Postbus 90203, 1006, Amsterdam, BE, Netherlands.,Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Theo J M Ruers
- Department of Surgery, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Postbus 90203, 1006, Amsterdam, BE, Netherlands.,Faculty of Science and Technology, University of Twente, Enschede, the Netherlands
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de Boer LL, Kho E, Jóźwiak K, Van de Vijver KK, Vrancken Peeters MJTFD, van Duijnhoven F, Hendriks BHW, Sterenborg HJCM, Ruers TJM. Influence of neoadjuvant chemotherapy on diffuse reflectance spectra of tissue in breast surgery specimens. J Biomed Opt 2019; 24:115004. [PMCID: PMC7003145 DOI: 10.1117/1.jbo.24.11.115004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Accepted: 11/04/2019] [Indexed: 05/28/2023]
Abstract
Diffuse reflectance spectroscopy (DRS) can discriminate different tissue types based on optical characteristics. Since this technology has the ability to detect tumor tissue, several groups have proposed to use DRS for margin assessment during breast-conserving surgery for breast cancer. Nowadays, an increasing number of patients with breast cancer are being treated by neoadjuvant chemotherapy. Limited research has been published on the influence of neoadjuvant chemotherapy on the optical characteristics of the tissue. Hence, it is unclear whether margin assessment based on DRS is feasible in this specific group of patients. We investigate whether there is an effect of neoadjuvant chemotherapy on optical measurements of breast tissue. To this end, DRS measurements were performed on 92 ex-vivo breast specimens from 92 patients, treated with neoadjuvant chemotherapy and without neoadjuvant chemotherapy. Generalized estimating equation (GEE) models were generated, comparing the measurements of patients with and without neoadjuvant chemotherapy in datasets of different tissue types using a significance level of 5%. As input for the GEE models, either the intensity at a specific wavelength or a fit parameter, derived from the spectrum, was used. In the evaluation of the intensity, no influence of neoadjuvant chemotherapy was found, since none of the wavelengths were significantly different between the measurements with and the measurements without neoadjuvant chemotherapy in any of the datasets. These results were confirmed by the analysis of the fit parameters, which showed a significant difference for the amount of collagen in only one dataset. All other fit parameters were not significant for any of the datasets. These findings may indicate that assessment of the resection margin with DRS is also feasible in the growing population of breast cancer patients who receive neoadjuvant chemotherapy. However, it is possible that we did not detect neoadjuvant chemotherapy effect in the some of the datasets due to the small number of measurements in those datasets.
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Affiliation(s)
- Lisanne L. de Boer
- The Netherlands Cancer Institute, Department of Surgery, Amsterdam, The Netherlands
| | - Esther Kho
- The Netherlands Cancer Institute, Department of Surgery, Amsterdam, The Netherlands
| | - Katarzyna Jóźwiak
- The Netherlands Cancer Institute, Department of Epidemiology and Biostatistics, The Netherlands
- Institute of Biostatistics and Registry Research, Brandenburg Medical School Theodor Fontane, Neuruppin, Germany
| | - Koen K. Van de Vijver
- The Netherlands Cancer Institute, Department of Pathology, Amsterdam, The Netherlands
- Ghent University Hospital, Department of Pathology, Gent, Belgium
| | | | | | - Benno H. W. Hendriks
- Philips Research, Eindhoven, The Netherlands
- Delft University of Technology, Biomechanical Engineering Department, Delft, The Netherlands
| | - Henricus J. C. M. Sterenborg
- The Netherlands Cancer Institute, Department of Surgery, Amsterdam, The Netherlands
- Amsterdam University Medical Center, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
| | - Theo J. M. Ruers
- The Netherlands Cancer Institute, Department of Surgery, Amsterdam, The Netherlands
- University of Twente, TNW, Technical Medical Centre, Enschede, The Netherlands
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Kho E, de Boer LL, Post AL, Van de Vijver KK, Jóźwiak K, Sterenborg HJCM, Ruers TJM. Imaging depth variations in hyperspectral imaging: Development of a method to detect tumor up to the required tumor-free margin width. J Biophotonics 2019; 12:e201900086. [PMID: 31290280 DOI: 10.1002/jbio.201900086] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Revised: 05/20/2019] [Accepted: 07/09/2019] [Indexed: 06/09/2023]
Abstract
Hyperspectral imaging is a promising technique for resection margin assessment during cancer surgery. Thereby, only a specific amount of the tissue below the resection surface, the clinically defined margin width, should be assessed. Since the imaging depth of hyperspectral imaging varies with wavelength and tissue composition, this can have consequences for the clinical use of hyperspectral imaging as margin assessment technique. In this study, a method was developed that allows for hyperspectral analysis of resection margins in breast cancer. This method uses the spectral slope of the diffuse reflectance spectrum at wavelength regions where the imaging depth in tumor and healthy tissue is equal. Thereby, tumor can be discriminated from healthy breast tissue while imaging up to a similar depth as the required tumor-free margin width of 2 mm. Applying this method to hyperspectral images acquired during surgery would allow for robust margin assessment of resected specimens. In this paper, we focused on breast cancer, but the same approach can be applied to develop a method for other types of cancer.
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Affiliation(s)
- Esther Kho
- Department of Surgery, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Lisanne L de Boer
- Department of Surgery, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Anouk L Post
- Department of Surgery, Netherlands Cancer Institute, Amsterdam, the Netherlands
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Koen K Van de Vijver
- Department of Pathology, the Netherlands Cancer Institute, Amsterdam, Netherlands
- Department of Pathology, Ghent University Hospital, Ghent, Belgium
| | - Katarzyna Jóźwiak
- Department of Epidemiology and Biostatistics, the Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Henricus J C M Sterenborg
- Department of Surgery, Netherlands Cancer Institute, Amsterdam, the Netherlands
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Theo J M Ruers
- Department of Surgery, Netherlands Cancer Institute, Amsterdam, the Netherlands
- Faculty of Science and Technology, University of Twente, Enschede, Netherlands
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Kho E, Dashtbozorg B, de Boer LL, Van de Vijver KK, Sterenborg HJCM, Ruers TJM. Broadband hyperspectral imaging for breast tumor detection using spectral and spatial information. Biomed Opt Express 2019; 10:4496-4515. [PMID: 31565506 PMCID: PMC6757478 DOI: 10.1364/boe.10.004496] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 07/26/2019] [Accepted: 07/29/2019] [Indexed: 05/20/2023]
Abstract
Complete tumor removal during breast-conserving surgery remains challenging due to the lack of optimal intraoperative margin assessment techniques. Here, we use hyperspectral imaging for tumor detection in fresh breast tissue. We evaluated different wavelength ranges and two classification algorithms; a pixel-wise classification algorithm and a convolutional neural network that combines spectral and spatial information. The highest classification performance was obtained using the full wavelength range (450-1650 nm). Adding spatial information mainly improved the differentiation of tissue classes within the malignant and healthy classes. High sensitivity and specificity were accomplished, which offers potential for hyperspectral imaging as a margin assessment technique to improve surgical outcome.
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Affiliation(s)
- Esther Kho
- Department of Surgery, Netherlands Cancer Institute, Plesmanlaan 121, 1066CX Amsterdam, Netherlands
| | - Behdad Dashtbozorg
- Department of Surgery, Netherlands Cancer Institute, Plesmanlaan 121, 1066CX Amsterdam, Netherlands
- Department of Biomedical Engineering, Eindhoven University of Technology, 5600MB Eindhoven, Netherlands
| | - Lisanne L. de Boer
- Department of Surgery, Netherlands Cancer Institute, Plesmanlaan 121, 1066CX Amsterdam, Netherlands
| | - Koen K. Van de Vijver
- Department of Pathology, Netherlands Cancer Institute, Plesmanlaan 121, 1066CX Amsterdam, Netherlands
- Department of Pathology, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Gent, Belgium
| | - Henricus J. C. M. Sterenborg
- Department of Surgery, Netherlands Cancer Institute, Plesmanlaan 121, 1066CX Amsterdam, Netherlands
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, Meibergdreef 9, 1105AZ Amsterdam, Netherlands
| | - Theo J. M. Ruers
- Department of Surgery, Netherlands Cancer Institute, Plesmanlaan 121, 1066CX Amsterdam, Netherlands
- Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522NB Enschede, Netherlands
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de Boer LL, Kho E, Nijkamp J, Van de Vijver KK, Sterenborg HJCM, ter Beek LC, Ruers TJM. Method for coregistration of optical measurements of breast tissue with histopathology: the importance of accounting for tissue deformations. J Biomed Opt 2019; 24:1-12. [PMID: 31347338 PMCID: PMC6995961 DOI: 10.1117/1.jbo.24.7.075002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Accepted: 07/09/2019] [Indexed: 05/24/2023]
Abstract
For the validation of optical diagnostic technologies, experimental results need to be benchmarked against the gold standard. Currently, the gold standard for tissue characterization is assessment of hematoxylin and eosin (H&E)-stained sections by a pathologist. When processing tissue into H&E sections, the shape of the tissue deforms with respect to the initial shape when it was optically measured. We demonstrate the importance of accounting for these tissue deformations when correlating optical measurement with routinely acquired histopathology. We propose a method to register the tissue in the H&E sections to the optical measurements, which corrects for these tissue deformations. We compare the registered H&E sections to H&E sections that were registered with an algorithm that does not account for tissue deformations by evaluating both the shape and the composition of the tissue and using microcomputer tomography data as an independent measure. The proposed method, which did account for tissue deformations, was more accurate than the method that did not account for tissue deformations. These results emphasize the need for a registration method that accounts for tissue deformations, such as the method presented in this study, which can aid in validating optical techniques for clinical use.
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Affiliation(s)
- Lisanne L. de Boer
- The Netherlands Cancer Institute, Department of Surgery, Amsterdam, The Netherlands
| | - Esther Kho
- The Netherlands Cancer Institute, Department of Surgery, Amsterdam, The Netherlands
| | - Jasper Nijkamp
- The Netherlands Cancer Institute, Department of Surgery, Amsterdam, The Netherlands
| | - Koen K. Van de Vijver
- The Netherlands Cancer Institute, Department of Pathology, Amsterdam, The Netherlands
- Ghent University Hospital, Department of Pathology, Gent, Belgium
| | - Henricus J. C. M. Sterenborg
- The Netherlands Cancer Institute, Department of Surgery, Amsterdam, The Netherlands
- Amsterdam University Medical Center, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
| | - Leon C. ter Beek
- The Netherlands Cancer Institute, Department of Medical Physics, Amsterdam, The Netherlands
| | - Theo J. M. Ruers
- The Netherlands Cancer Institute, Department of Surgery, Amsterdam, The Netherlands
- University of Twente, Faculty of Science and Technology, Enschede, The Netherlands
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9
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Kho E, de Boer LL, Van de Vijver KK, van Duijnhoven F, Vrancken Peeters MJT, Sterenborg HJ, Ruers TJ. Hyperspectral Imaging for Resection Margin Assessment during Cancer Surgery. Clin Cancer Res 2019; 25:3572-3580. [DOI: 10.1158/1078-0432.ccr-18-2089] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2018] [Revised: 10/24/2018] [Accepted: 03/12/2019] [Indexed: 11/16/2022]
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de Boer LL, Bydlon TM, van Duijnhoven F, Vranken Peeters MJTFD, Loo CE, Winter-Warnars GAO, Sanders J, Sterenborg HJCM, Hendriks BHW, Ruers TJM. Towards the use of diffuse reflectance spectroscopy for real-time in vivo detection of breast cancer during surgery. J Transl Med 2018; 16:367. [PMID: 30567584 PMCID: PMC6299954 DOI: 10.1186/s12967-018-1747-5] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Accepted: 12/13/2018] [Indexed: 12/31/2022] Open
Abstract
Background Breast cancer surgeons struggle with differentiating healthy tissue from cancer at the resection margin during surgery. We report on the feasibility of using diffuse reflectance spectroscopy (DRS) for real-time in vivo tissue characterization. Methods Evaluating feasibility of the technology requires a setting in which measurements, imaging and pathology have the best possible correlation. For this purpose an optical biopsy needle was used that had integrated optical fibers at the tip of the needle. This approach enabled the best possible correlation between optical measurement volume and tissue histology. With this optical biopsy needle we acquired real-time DRS data of normal tissue and tumor tissue in 27 patients that underwent an ultrasound guided breast biopsy procedure. Five additional patients were measured in continuous mode in which we obtained DRS measurements along the entire biopsy needle trajectory. We developed and compared three different support vector machine based classification models to classify the DRS measurements. Results With DRS malignant tissue could be discriminated from healthy tissue. The classification model that was based on eight selected wavelengths had the highest accuracy and Matthews Correlation Coefficient (MCC) of 0.93 and 0.87, respectively. In three patients that were measured in continuous mode and had malignant tissue in their biopsy specimen, a clear transition was seen in the classified DRS measurements going from healthy tissue to tumor tissue. This transition was not seen in the other two continuously measured patients that had benign tissue in their biopsy specimen. Conclusions It was concluded that DRS is feasible for integration in a surgical tool that could assist the breast surgeon in detecting positive resection margins during breast surgery. Trail registration NIH US National Library of Medicine–clinicaltrails.gov, NCT01730365. Registered: 10/04/2012 https://clinicaltrials.gov/ct2/show/study/NCT01730365
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Affiliation(s)
- Lisanne L de Boer
- Department of Surgery, the Netherlands Cancer Institute-Antoni van Leeuwenhoek, Plesmanlaan 121, Postbus 90203, 1066 CX, Amsterdam, The Netherlands.
| | - Torre M Bydlon
- In-body Systems, Philips Research, High Tech, Campus 34, 5656 AE, Eindhoven, The Netherlands
| | - Frederieke van Duijnhoven
- Department of Surgery, the Netherlands Cancer Institute-Antoni van Leeuwenhoek, Plesmanlaan 121, Postbus 90203, 1066 CX, Amsterdam, The Netherlands
| | - Marie-Jeanne T F D Vranken Peeters
- Department of Surgery, the Netherlands Cancer Institute-Antoni van Leeuwenhoek, Plesmanlaan 121, Postbus 90203, 1066 CX, Amsterdam, The Netherlands
| | - Claudette E Loo
- Department of Radiology, the Netherlands Cancer Institute-Antoni van Leeuwenhoek, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Gonneke A O Winter-Warnars
- Department of Radiology, the Netherlands Cancer Institute-Antoni van Leeuwenhoek, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Joyce Sanders
- Department of Pathology, the Netherlands Cancer Institute-Antoni van Leeuwenhoek, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Henricus J C M Sterenborg
- Department of Surgery, the Netherlands Cancer Institute-Antoni van Leeuwenhoek, Plesmanlaan 121, Postbus 90203, 1066 CX, Amsterdam, The Netherlands.,Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Benno H W Hendriks
- In-body Systems, Philips Research, High Tech, Campus 34, 5656 AE, Eindhoven, The Netherlands.,Biomechanical Engineering, Delft University of Technology, Mekelweg 5, 2628 CD, Delft, The Netherlands
| | - Theo J M Ruers
- Department of Surgery, the Netherlands Cancer Institute-Antoni van Leeuwenhoek, Plesmanlaan 121, Postbus 90203, 1066 CX, Amsterdam, The Netherlands.,Technical Medical Centre, University of Twente, Drienerlolaan 5, 7522 NB, Enschede, The Netherlands
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de Boer LL, Hendriks BHW, van Duijnhoven F, Peeters-Baas MJTFDV, Van de Vijver K, Loo CE, Jóźwiak K, Sterenborg HJCM, Ruers TJM. Using DRS during breast conserving surgery: identifying robust optical parameters and influence of inter-patient variation. Biomed Opt Express 2016; 7:5188-5200. [PMID: 28018735 PMCID: PMC5175562 DOI: 10.1364/boe.7.005188] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2016] [Revised: 11/11/2016] [Accepted: 11/13/2016] [Indexed: 05/12/2023]
Abstract
Successful breast conserving surgery consists of complete removal of the tumor while sparing healthy surrounding tissue. Despite currently available imaging and margin assessment tools, recognizing tumor tissue at a resection margin during surgery is challenging. Diffuse reflectance spectroscopy (DRS), which uses light for tissue characterization, can potentially guide surgeons to prevent tumor positive margins. However, inter-patient variation and changes in tissue physiology occurring during the resection might hamper this light-based technology. Here we investigate how inter-patient variation and tissue status (in vivo vs ex vivo) affect the performance of the DRS optical parameters. In vivo and ex vivo measurements of 45 breast cancer patients were obtained and quantified with an analytical model to acquire the optical parameters. The optical parameter representing the ratio between fat and water provided the best discrimination between normal and tumor tissue, with an area under the receiver operating characteristic curve of 0.94. There was no substantial influence of other patient factors such as menopausal status on optical measurements. Contrary to expectations, normalization of the optical parameters did not improve the discriminative power. Furthermore, measurements taken in vivo were not significantly different from the measurements taken ex vivo. These findings indicate that DRS is a robust technology for the detection of tumor tissue during breast conserving surgery.
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Affiliation(s)
- Lisanne L. de Boer
- Netherlands Cancer Institute – Antoni van Leeuwenhoek, Amsterdam The Netherlands
| | - Benno H. W. Hendriks
- Philips Research, Eindhoven, The Netherlands
- Biomechanical Engineering Department, Delft University of Technology, Delft, The Netherlands
| | | | | | - Koen Van de Vijver
- Netherlands Cancer Institute – Antoni van Leeuwenhoek, Amsterdam The Netherlands
| | - Claudette E. Loo
- Netherlands Cancer Institute – Antoni van Leeuwenhoek, Amsterdam The Netherlands
| | - Katarzyna Jóźwiak
- Netherlands Cancer Institute – Antoni van Leeuwenhoek, Amsterdam The Netherlands
| | - Henricus J. C. M. Sterenborg
- Netherlands Cancer Institute – Antoni van Leeuwenhoek, Amsterdam The Netherlands
- Academic Medical Center, Department of Biomedical Engineering and Physics, Meibergdreef 9, 1105AZ, Amsterdam, Netherlands
| | - Theo J. M. Ruers
- Netherlands Cancer Institute – Antoni van Leeuwenhoek, Amsterdam The Netherlands
- MIRA Institute, University Twente, The Netherlands
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12
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Obdeijn MC, Horeman T, de Boer LL, van Baalen SJ, Liverneaux P, Tuijthof GJM. Navigation forces during wrist arthroscopy: assessment of expert levels. Knee Surg Sports Traumatol Arthrosc 2016; 24:3684-3692. [PMID: 25448136 DOI: 10.1007/s00167-014-3450-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2014] [Accepted: 11/17/2014] [Indexed: 10/24/2022]
Abstract
PURPOSE To facilitate effective and efficient training in skills laboratory, objective metrics can be used. Forces exerted on the tissues can be a measure of safe tissue manipulation. To provide feedback during training, expert threshold levels need to be determined. The purpose of this study was to define the magnitude and the direction of navigation forces used during arthroscopic inspection of the wrist. METHODS We developed a set-up to mount a cadaver wrist to a 3D force platform that allowed measurement of the forces exerted on the wrist. Six experts in wrist arthroscopy performed two tasks: (1) Introduction of the camera and visualization of the hook. (2) Navigation through the wrist with visualization of five anatomic structures. The magnitude (Fabs) and direction of force were recorded, with the direction defined as α being the angle in the vertical plane and β being the angle in the horizontal plane. The 10th-90th percentile of the data were used to set threshold levels for training. RESULTS The results show distinct force patterns for each of the anatomic landmarks. Median Fabs of the navigation task is 3.8 N (1.8-7.3), α is 3.60 (-54-44) and β is 260 (0-72). CONCLUSION Unique expert data on navigation forces during wrist arthroscopy were determined. The defined maximum allowable navigation force of 7.3 N (90th percentile) can be used in providing feedback on performance during skills training. The clinical value is that this study contributes to objective assessment of skills levels.
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Affiliation(s)
- Miryam C Obdeijn
- Department of Plastic, Reconstructive and Hand Surgery, Academic Medical Center, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, Netherlands.
| | - Tim Horeman
- Department of Biomechanical Engineering, Delft University of Technology, Delft, Netherlands
| | - Lisanne L de Boer
- Department of Technical Medicine, MIRA Institute for Biomedical Technology and Technical Medicine Enschede, University of Twente, Enschede, Netherlands
| | - Sophie J van Baalen
- Department of Technical Medicine, MIRA Institute for Biomedical Technology and Technical Medicine Enschede, University of Twente, Enschede, Netherlands
| | - Philippe Liverneaux
- Department of Hand Surgery, Strasbourg University Hospitals, Illkirch, France
| | - Gabrielle J M Tuijthof
- Department of Biomechanical Engineering, Delft University of Technology, Delft, Netherlands.,Department of Orthopedic Surgery, Orthopedic Research Center Amsterdam, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands
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13
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Spliethoff JW, de Boer LL, Meier MAJ, Prevoo W, de Jong J, Kuhlmann K, Bydlon TM, Sterenborg HJCM, Hendriks BHW, Ruers TJM. In vivo characterization of colorectal metastases in human liver using diffuse reflectance spectroscopy: toward guidance in oncological procedures. J Biomed Opt 2016; 21:97004. [PMID: 27637008 PMCID: PMC8357329 DOI: 10.1117/1.jbo.21.9.097004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2016] [Accepted: 08/30/2016] [Indexed: 05/15/2023]
Abstract
There is a strong need to develop clinical instruments that can perform rapid tissue assessment at the tip of smart clinical instruments for a variety of oncological applications. This study presents the first in vivo real-time tissue characterization during 24 liver biopsy procedures using diffuse reflectance (DR) spectroscopy at the tip of a core biopsy needle with integrated optical fibers. DR measurements were performed along each needle path, followed by biopsy of the target lesion using the same needle. Interventional imaging was coregistered with the DR spectra. Pathology results were compared with the DR spectroscopy data at the final measurement position. Bile was the primary discriminator between normal liver tissue and tumor tissue. Relative differences in bile content matched with the tissue diagnosis based on histopathological analysis in all 24 clinical cases. Continuous DR measurements during needle insertion in three patients showed that the method can also be applied for biopsy guidance or tumor recognition during surgery. This study provides an important validation step for DR spectroscopy-based tissue characterization in the liver. Given the feasibility of the outlined approach, it is also conceivable to make integrated fiber-optic tools for other clinical procedures that rely on accurate instrument positioning.
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Affiliation(s)
- Jarich W. Spliethoff
- Netherlands Cancer Institute, Department of Surgery, Plesmanlaan 121, 1066CX Amsterdam, The Netherlands
- Address all correspondence to: Jarich W. Spliethoff, E-mail:
| | - Lisanne L. de Boer
- Netherlands Cancer Institute, Department of Surgery, Plesmanlaan 121, 1066CX Amsterdam, The Netherlands
| | - Mark A. J. Meier
- Netherlands Cancer Institute, Department of Radiology, Plesmanlaan 121, 1066CX Amsterdam, The Netherlands
| | - Warner Prevoo
- Netherlands Cancer Institute, Department of Radiology, Plesmanlaan 121, 1066CX Amsterdam, The Netherlands
| | - Jeroen de Jong
- Netherlands Cancer Institute, Department of Pathology, Plesmanlaan 121, 1066CX Amsterdam, The Netherlands
| | - Koert Kuhlmann
- Netherlands Cancer Institute, Department of Surgery, Plesmanlaan 121, 1066CX Amsterdam, The Netherlands
| | - Torre M. Bydlon
- Philips Research, Department In-body Systems, High Tech Campus 34, 5656AE Eindhoven, The Netherlands
| | - Henricus J. C. M. Sterenborg
- Academic Medical Center, Department of Biomedical Engineering and Physics, Meibergdreef 9, 1105AZ Amsterdam, The Netherlands
| | - Benno H. W. Hendriks
- Philips Research, Department In-body Systems, High Tech Campus 34, 5656AE Eindhoven, The Netherlands
| | - Theo J. M. Ruers
- Netherlands Cancer Institute, Department of Surgery, Plesmanlaan 121, 1066CX Amsterdam, The Netherlands
- University of Twente, MIRA Institute, Drienerlolaan 5, Zuidhorst ZH116, 7522 NB Enschede, The Netherlands
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Spliethoff JW, de Boer LL, Meier MA, Prevoo W, de Jong J, Bydlon TM, Sterenborg HJ, Burgers JA, Hendriks BH, Ruers TJ. Spectral sensing for tissue diagnosis during lung biopsy procedures: The importance of an adequate internal reference and real-time feedback. Lung Cancer 2016; 98:62-68. [DOI: 10.1016/j.lungcan.2016.05.019] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2016] [Revised: 05/17/2016] [Accepted: 05/25/2016] [Indexed: 01/10/2023]
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