Single fiber reflectance spectroscopy for pancreatic cancer detection during endoscopic ultrasound guided fine needle biopsy: a prospective cohort study

Ultrasound-Guided Quantitative Fluorescence Molecular Endoscopy for Monitoring Response in Patients with Esophageal Cancer Following Neoadjuvant Chemoradiotherapy

PURPOSE

The ability to identify residual tumor tissues in patients with locally advanced esophageal cancer following neoadjuvant chemoradiotherapy (nCRT) is essential for monitoring the treatment response. Using the fluorescent tracer bevacizumab-800CW, we evaluated whether ultrasound-guided quantitative fluorescent molecular endoscopy (US-qFME), which combines quantitative fluorescence molecular endoscopy (qFME) with ultrasound-guided needle biopsy/single-fiber fluorescence (USNB/SFF), can be used to identify residual tumor tissues in patients following nCRT.

EXPERIMENTAL DESIGN

Twenty patients received an additional endoscopy procedure the day before surgery. qFME was performed at the primary tumor site (PTS) and in healthy tissue to first establish the optimal tracer dose. USNB/SFF was then used to measure intrinsic fluorescence in the deeper PTS layers and lymph nodes (LN) suspected for metastasis. Finally, the intrinsic fluorescence and the tissue optical properties-specifically, the absorption and reduced scattering coefficients-were combined into a new parameter called omega.

RESULTS

First, a 25-mg bevacizumab-800CW dose allowed for clear differentiation between the PTS and healthy tissue, with a target-to-background ratio (TBR) of 2.98 (IQR, 1.86-3.03). Moreover, we found a clear difference between the deeper esophageal PTS layers and suspected LN compared to healthy tissues, with TBR values of 2.18 and 2.17, respectively. Finally, our new parameter, omega, further improved the ability to differentiate between the PTS and healthy tissue.

CONCLUSIONS

Combining bevacizumab-800CW with US-qFME may serve as a viable strategy for monitoring the response to nCRT in esophageal cancer and may help stratify patients regarding active surveillance versus surgery.

Evaluation of an Integrated Spectroscopy and Classification Platform for Point-of-Care Core Needle Biopsy Assessment: Performance Characteristics from Ex Vivo Renal Mass Biopsies

PURPOSE

To evaluate a transmission optical spectroscopy instrument for rapid ex vivo assessment of core needle cancer biopsies (CNBs) at the point of care.

MATERIALS AND METHODS

CNBs from surgically resected renal tumors and nontumor regions were scanned on their sampling trays with a custom spectroscopy instrument. After extracting principal spectral components, machine learning was used to train logistic regression, support vector machines, and random decision forest (RF) classifiers on 80% of randomized and stratified data. The algorithms were evaluated on the remaining 20% of the data set held out during training. Binary classification (tumor/nontumor) was performed based on a decision threshold. Multinomial classification was also performed to differentiate between the subtypes of renal cell carcinoma (RCC) and account for potential confounding effects from fat, blood, and necrotic tissue. Classifiers were compared based on sensitivity, specificity, and positive predictive value (PPV) relative to a histopathologic standard.

RESULTS

A total of 545 CNBs from 102 patients were analyzed, yielding 5,583 spectra after outlier exclusion. At the individual spectra level, the best performing algorithm was RF with sensitivities of 96% and 92% and specificities of 90% and 89%, for the binary and multiclass analyses, respectively. At the full CNB level, RF algorithm also showed the highest sensitivity and specificity (93% and 91%, respectively). For RCC subtypes, the highest sensitivity and PPV were attained for clear cell (93.5%) and chromophobe (98.2%) subtypes, respectively.

CONCLUSIONS

Ex vivo spectroscopy imaging paired with machine learning can accurately characterize renal mass CNB at the time of tissue acquisition.

Diffuse photon remission associated with the center-illuminated-area-detection geometry: Part I, an approach to the steady-state model

Diffuse photon remission associated with the center-illuminated-area-detection (CIAD) geometry has been useful for non-contact sensing and may inform single-fiber reflectance (SfR). This series of work advances model approaches that help enrich the understanding and applicability of the photon remission by CIAD. The general approach is to derive the diffuse photon remission by the area integration of the radially resolved diffuse reflectance while limiting the analysis to a medium exhibiting only the Heyney-Greenstein (HG) scattering phase function. Part I assesses the steady-state photon remission in CIAD over a reduced scattering scaled diameter of μ s ' d _{a r e a} ∈[0.5×10^-3,10³] that covers the range extensively modeled for SfR. The corresponding radially resolved diffuse reflectance is obtained by concatenating an empirical expression for the semi-ballistic region near the point-of-illumination and a formula utilizing a master-slave dual-source scheme over the semi-diffusive to a diffusive regime while being constrained by an extrapolated zero-boundary condition. The terminal algebraic photon remission is examined against Monte Carlo simulations for an absorption coefficient over [0.001,1]m m ^-1, a reduced scattering coefficient over [0.01,1000]m m ^-1, a HG scattering anisotropy factor within [0.5,0.95], and a diameter of the area of collection ranging [50,1000]µm. The algebraic model is also applied to phantom data acquired over a ∼2c m non-contact CIAD configuration and with a 200 µm SfR probe. The model approach will be extended in a subsequent work towards the time-of-flight characteristics of CIAD.