No abstract

Background: Duodenal gastrinomas (DGASTs) are neuroendocrine tumors that develop in the submucosa of the duodenum and produce the hormone gastrin. Surgical resection of DGASTs is complicated by the small size of these tumors and the tendency for them to develop diffusely in the duodenum. Endoscopic mucosal resection of DGASTs is an increasingly popular method for treating this disease due to its low complication rate but suffers from poor rates of pathologically negative margins. Multiphoton microscopy can capture high-resolution images of biological tissue with contrast generated from endogenous fluorescence (autofluorescence [AF]) through two-photon excited fluorescence (2PEF). Second harmonic generation is another popular method of generating image contrast with multiphoton microscopy (MPM) and is a lightscattering phenomenon that occurs predominantly from structures such as collagen in biological samples. Some molecules that contribute to AF change in abundance from processes related to the cancer disease process (e.g., metabolic changes, oxidative stress, and angiogenesis). Study Design/Materials and Methods: MPM was used to image 12 separate patient samples of formalin-fixed and paraffin-embedded duodenal gastrinoma slides with a second-harmonic generation (SHG) channel and four 2PEF channels. The excitation and emission profiles of each 2PEF channel were tuned to capture signal dominated by distinct fluorophores with well-characterized fluorescent spectra and known connections to the physiologic changes that arise in cancerous tissue. Results: We found that there was a significant difference in the relative abundance of signal generated in the 2PEF channels for regions of DGASTs in comparison to the neighboring tissues of the duodenum. Data generated from texture feature extraction of the MPM images were used in linear discriminant analysis models to create classifiers for tumor versus all other tissue types before and after principal component analysis (PCA). PCA improved the classifier accuracy and reduced the number of features required to achieve maximum accuracy. The linear discriminant classifier after PCA distinguished between tumor and other tissue types with an accuracy of 90.6%−93.8%. Conclusions: These results suggest that multiphoton microscopy 2PEF and SHG imaging is a promising label-free method for discriminating between DGASTs and normal duodenal tissue which has implications for future applications of in vivo assessment of resection margins with endoscopic MPM.

Duodenal gastrinomas (DGASTs) are neuroendocrine tumors that develop in the submucosa of the duodenum and produce the hormone, gastrin. Surgical resection of DGASTs is complicated by the small size of these tumors and the tendency for them to develop diffusely in the duodenum. Endoscopic mucosal resection of DGASTS is an increasingly popular method for treating this disease due to its low complication rate but suffers from poor rates of pathologically negative margins. Multiphoton microscopy (MPM) is capable of capturing high-resolution images of biological tissue with contrast generated from endogenous fluorescence (autofluorescence) through two-photon excited fluorescence (2PEF). Second harmonic generation (SHG) is another popular method of generating image contrast with MPM and is a light-scattering phenomenon that occurs predominantly from structures such as collagen in biological samples. Some molecules that contribute to autofluorescence change in abundance from processes related to the cancer disease process (e.g., metabolic changes, oxidative stress, angiogenesis). MPM was used to image 12 separate patient samples of formalin-fixed and paraffinized DGAST slides with a SHG channel 4 2PEF channels, each tuned to capture fluorescence from NADH, FAD, lipofuscin, and porphyrin. We found that there was a significant difference in the relative abundance of signal generated in the 2PEF in comparison to the neighboring tissues of the duodenum. Texture extraction was used to create linear discriminant classifiers for tumor vs all other tissue classes before and after principal component analysis (PCA) of the texture feature dataset. PCA improved the classifier accuracy and reduced the number of features required to achieve maximum accuracy of the classifier. The LDA classifier after PCA distinguished between tumor and other tissue types with an accuracy of 90.6 - 93.8%. These results suggest that MPM 2PEF and SHG imaging is a promising label-free method for discriminating between DGAST tumors and normal duodenal tissue which has implications for future applications of in vivo assessment of resection margins with endoscopic MPM.

Pancreatic neuroendocrine tumors (PNETs) are a rare but increasingly more prevalent cancer with heterogeneous clinical and pathological presentation. Surgery is the preferred treatment for all hormone-expressing PNETs and any PNET greater than 2 cm, but difficulties arise when tumors are multifocal, metastatic, or small in size due to lack of effective surgical localization. Existing techniques such as intraoperative ultrasound provide poor contrast and resolution, resulting in low sensitivity for such tumors. Somatostatin receptor type 2 (SSTR2) is commonly overexpressed in PNETs and presents an avenue for targeted tumor localization. SSTR2 is often used for pre-operative imaging and therapeutic treatment, with recent studies demonstrating that somatostatin receptor imaging (SRI) can be applied in radioguided surgery to aid in removal of metastatic lymph nodes and achieving negative surgical margins. However not all PNETs express SSTR2, indicating labeled SRI could benefit from using a supplemental label-free technique such as multiphoton microscopy (MPM), which has proven useful in improving the accuracy of diagnosing more common exocrine pancreatic cancers. Our work tests the suitability of combined SRI and MPM for localizing PNETs by imaging and comparing samples of PNETs and normal pancreatic tissue. Specimens were labeled with a novel SSTR2-targeted contrast agent and imaged using fluorescence microscopy, and subsequently imaged using MPM to collect four autofluorescent channels and second harmonic generation. Our results show that a combination of both SRI and MPM provides enhanced contrast and sensitivity for localizing diseased tissue, suggesting that this approach could be a valuable clinical tool for surgical localization and treatment of PNETs.

Gastrointestinal cancers continue to account for a disproportionately large percentage of annual cancer deaths in the United States. Advancements in miniature imaging technology combined with a need for precise and thorough tumor detection in gastrointestinal cancer screenings fuel the demand for new, small-scale, and low-cost methods of localization and margin identification with improved accuracy. Here, we report the development of a miniaturized, chip-on-tip, multispectral, fluorescence imaging probe designed for compatibility with a gastroscope working channel with the aim of detecting cancerous lesions in point-of-care endoscopy of the gastrointestinal lumen. Preclinical testing has confirmed fluorescence sensitivity and supports that this miniature probe can locate structures of interest via detection of fluorescence emission from exogenous contrast agents. This work demonstrates the design and preliminary performance evaluation of a miniaturized, single-use, chip-on-tip fluorescence imaging system, capable of detecting multiplexed fluorophores, and devised for deployment via the accessory channel of a standard gastroscope.

No abstract

Gastrinomas are gastrin-producing neuroendocrine tumors (NETs) located in the gastroenteropancreatic system. Gastrinomas are often small, multifocal, and found at late stages. Their unpredictable behavior and metastatic potential make it extremely challenging to develop therapeutic strategies. Surgery is the only potentially curative treatment for gastrinoma, but current tumor localization techniques such as intraoperative ultrasound and manual palpitation have poor sensitivity for small tumors, resulting in higher rates of recurrence and metastasis. Therefore, there is a strong clinical need for developing advanced intraoperative imaging technologies for tumor localization in treating gastrinoma. Polarized light imaging (PLI) is a promising method for label-free tissue characterization due to its sensitivity to micro and nanoscale structures, which are often influenced with the onset of cancer, but no works have yet investigated the application of PLI for gastrinoma localization.To assess the suitability of PLI for gastrinoma localization, we imaged 11 formalin-fixed paraffin embedded (FFPE) specimens of gastrinoma using a five-wavelength Mueller Matrix Polarization Microscope. The Lu-Chipman decomposition was applied to spatial maps of the sixteen Mueller matrix parameters. Values for depolarization, diattenuation, and retardance were compared for regions of interest corresponding to tumor and adjacent tissues. There was significant difference between the average depolarization of the Brunner's gland and tumors when imaged with light at 442, 543, and 632nm (p<0.05), and the average diattenuation values of the two at 405nm (p<0.05), suggesting that these properties could be used for label-free localization. These results motivate further study of the use of PLI for NET localization. Future steps include broadening the sample pool to other NETs and validating results in fresh tissue studies.

No abstract