Backscattering intensity measurements in optical coherence tomography as a method to identify parathyroid glands

Diseased thyroid tissue classification in OCT images using deep learning: Towards surgical decision support

Intraoperative guidance tools for thyroid surgery based on optical coherence tomography (OCT) could aid distinguish between normal and diseased tissue. However, OCT images are difficult to interpret, thus, real-time automatic analysis could support the clinical decision-making. In this study, several deep learning models were investigated for thyroid disease classification on 2D and 3D OCT data obtained from ex vivo specimens of 22 patients undergoing surgery and diagnosed with several thyroid pathologies. Additionally, two open-access datasets were used to evaluate the custom models. On the thyroid dataset, the best performance was achieved by the 3D vision transformer model with a Matthew's correlation coefficient (MCC) of 0.79 (accuracy = 0.90) for the normal-versus-abnormal classification. On the open-access datasets, the custom models achieved the best performance (MCC > 0.88, accuracy > 0.96). Results obtained for the normal-versus-abnormal classification suggest OCT, complemented with deep learning-based analysis, as a tool for real-time automatic diseased tissue identification in thyroid surgery.

Primary study of identification of parathyroid gland based on laser-induced breakdown spectroscopy

The identification and preservation of parathyroid glands (PGs) is a major issue in thyroidectomy. The PG is particularly difficult to distinguish from the surrounding tissues. Accidental damage or removal of the PG may result in temporary or permanent postoperative hypoparathyroidism and hypocalcemia. In this study, a novel method for identification of the PG was proposed based on laser-induced breakdown spectroscopy (LIBS) for the first time. LIBS spectra were collected from the smear samples of PG and non-parathyroid gland (NPG) tissues (thyroid and neck lymph node) of rabbits. The emission lines (related to K, Na, Ca, N, O, CN, C₂, etc.) observed in LIBS spectra were ranked and selected based on the important weight calculated by random forest (RF). Three machine learning algorithms were used as classifiers to distinguish PGs from NPGs. The artificial neural network classifier provided the best classification performance. The results demonstrated that LIBS can be adopted to discriminate between smear samples of PG and NPG, and it has a potential in intra-operative identification of PGs.

Optical coherence tomography for thyroid pathology: 3D analysis of tissue microstructure

To investigate the potential of optical coherence tomography (OCT) to distinguish between normal and pathologic thyroid tissue, 3D OCT images were acquired on ex vivo thyroid samples from adult subjects (n=22) diagnosed with a variety of pathologies. The follicular structure was analyzed in terms of count, size, density and sphericity. Results showed that OCT images highly agreed with the corresponding histopatology and the calculated parameters were representative of the follicular structure variation. The analysis of OCT volumes provides quantitative information that could make automatic classification possible. Thus, OCT can be beneficial for intraoperative surgical guidance or in the pathology assessment routine.

Intraoperative Near-Infrared Autofluorescence and Indocyanine Green Imaging to Identify Parathyroid Glands: A Comparison

OBJECTIVE

To investigate the feasibility of near-infrared autofluorescence (AF) and indocyanine green (ICG) fluorescence to identify parathyroid glands intraoperatively.

METHODS

Fluorescence imaging was carried out during open parathyroid and thyroid surgery. After visual identification, parathyroid glands were exposed to near-infrared (NIR) light with a wavelength between 690 and 770 nm. The camera of the Storz® NIR/ICG endoscopic system used detects NIR light as a blue signal. Therefore, parathyroid AF was expected to be displayed in the blue color channel in contrast to the surrounding tissue. Following AF imaging, a bolus of 5 mg ICG was applied intravenously. ICG fluorescence was detected using the same NIR/ICG imaging system. Well-vascularized parathyroid glands were expected to show a strong fluorescence in contrast to surrounding lymphatic and adipose tissue.

RESULTS

We investigated 78 parathyroid glands from 50 patients. 64 parathyroid glands (82%) displayed AF showing the typical bluish violet color. 63 parathyroid glands (81%) showed a strong and persistent fluorescence after application of ICG. The sensitivity of identifying a parathyroid gland by AF was 82% (64 true positive and 14 false negative results), while ICG imaging showed a sensitivity of 81% (63 true positive and 15 false negative results). The Fisher exact test revealed no significant difference between both groups at p < 0.05. Neither lymph nodes nor adipose tissue revealed substantial AF or ICG fluorescence.

CONCLUSION

AF and ICG fluorescence reveal a high degree of sensitivity in identifying parathyroid glands. Further, ICG imaging facilitates the assessment of parathyroid perfusion. However, in the current setting both techniques are not suitable as screening tools to identify parathyroid glands at an early stage of the operation.

Parathyroid gland management using optical technologies during thyroidectomy or parathyroidectomy: A systematic review

New optical technologies enhancing localization or assessing viability of parathyroid glands (PG) during endocrine surgery have been reported in clinical studies. These technologies could become complementary to the surgeon's eyes and may improve surgical outcomes in thyroidectomy and parathyroidectomy. Here, we conducted a systematic review focusing on PG identification and functional assessment using optical methods to enhance surgery. A systematic literature review was performed using MEDLINE and Embase database. Two authors selected studies and extracted data; qualitative analysis was performed to summarize the characteristics of reported optical tools for thyroidectomy or parathyroidectomy. Identification and vascularisation of PG during surgery were evaluated. Clinical and biochemical outcomes were appraised when reported. Studies relating to parathyroidectomy or thyroidectomy combined with autofluorescence, fluorescent methylene blue, 5-aminolevulinic acid, indocyanine green (ICG), optical coherence tomography, laser speckle contrast imaging, dynamic optical contrast imaging and Raman spectroscopy were identified with MEDLINE and Embase. We included a total of 47 relevant articles with a total of 1615 patients enrolled. Each optical technique is described and appreciated related to its surgical purpose. Autofluorescence and ICG imaging of PG are the most widely reported optical technologies for identification and assessment of vascularisation of PG. Results are mainly based on observational studies and argue for the feasibility of both techniques in endocrine surgery but prospective randomized studies have not been performed. In vivo applications are still limited for the other methods and further investigations correlating these techniques with post-operative parathormone measurements are still needed before considering these technologies in clinical practice.

Automatic identification of parathyroid in optical coherence tomography images

BACKGROUND AND OBJECTIVE

The identification and preservation of parathyroid is a major problem in thyroid surgery. In order to solve this problem, optical coherence tomography was involved as a real-time, non-invasive high-resolution imaging technique. This study demonstrated an effective and fast method to distinguish parathyroid tissue from thyroid, lymph node, and adipose tissue in their ex vivo optical coherence tomography (OCT) images automatically.

METHODS

OCT images were obtained from parathyroid, thyroid, lymph node, and adipose tissue, respectively. A classification and an identification system based on texture features analysis and back propagation artificial neural network (BP-ANN) were established to classify the four types of tissue and identify each of the four types automatically.

RESULTS

A total of 248 OCT images were taken from 16 patients undergoing thyroidectomy. The accuracy of classification for parathyroid, thyroid, lymph node, and adipose were 99.21, 98.43, 97.65, and 98.43%, respectively.

CONCLUSION

The proposed automatic identification method is capable of distinguishing among parathyroid, thyroid, lymph, and adipose automatically and effectively. Compared with the identification results of human, it has a better accuracy and reliability. For identifying parathyroid from the other entities, it has a satisfying performance. Lasers Surg. Med. 49:305-311, 2017. © 2017 Wiley Periodicals, Inc.

[Optical coherence tomography for differentiation of parathyroid gland tissue]

BACKGROUND

Optical coherence tomography (OCT) is a high-resolution imaging technique that allows the identification of microarchitectural features in real-time.

OBJECTIVE

Can OCT be used to differentiate parathyroid tissue from other cervical tissue entities?

MATERIAL AND METHODS

All investigations were carried out during cervical operations. Initially, ex vivo images were analyzed to define morphological imaging criteria for each tissue entity. These criteria were used to evaluate a first series of ex vivo images. In a second phase the practicability of the technique was investigated in vivo and in the third phase backscattering intensity measurements were analyzed employing linear discriminant analysis (LDA).

RESULTS

In the ex vivo series parathyroid tissue could be differentiated from other tissue entities with a sensitivity and specificity of 84  % and 94  %, respectively. Parathyroid tissue was correctly identified in the in vivo series in only 69.2 %. The analysis of backscattering intensity profiles employing LDA reliably distinguished between the different tissue types.

CONCLUSION

The OCT images displayed typical characteristics for each tissue entity. Due to technical problems in handling the probe the in vivo OCT images were of much poorer quality. Backscattering intensity measurements illustrated that OCT images provide an individual profile for each tissue entity independent of the defined morphological assessment criteria. The results show that OCT is fundamentally suitable for intraoperative differentiation of tissues.