Quantitative chemometric phenotyping of three-dimensional liver organoids by Raman spectral imaging.

Confocal Raman spectral imaging (RSI) enables high-content, label-free visualization of a wide range of molecules in biological specimens without sample preparation. However, reliable quantification of the deconvoluted spectra is needed. Here we develop an integrated bioanalytical methodology, qRamanomics, to qualify RSI as a tissue phantom calibrated tool for quantitative spatial chemotyping of major classes of biomolecules. Next, we apply qRamanomics to fixed 3D liver organoids generated from stem-cell-derived or primary hepatocytes to assess specimen variation and maturity. We then demonstrate the utility of qRamanomics for identifying biomolecular response signatures from a panel of liver-altering drugs, probing drug-induced compositional changes in 3D organoids followed by in situ monitoring of drug metabolism and accumulation. Quantitative chemometric phenotyping constitutes an important step in developing quantitative label-free interrogation of 3D biological specimens.

Determining the level of cervical radiculopathy: Agreement between visual inspection of pain drawings and magnetic resonance imaging.

BACKGROUND AND AIMS: Pain drawings are commonly used in the clinical assessment of people with cervical radiculopathy. This study aimed to assess (1) the agreement of clinical interpretation of pain drawings and MRI findings in identifying the affected level of cervical radiculopathy, (2) the agreement of these predictions based on the pain drawing among four clinicians from two different professions (i.e., physiotherapy and surgery) and (3) the topographical pain distribution of people presenting with cervical radiculopathy (C4-C7). METHODS: Ninety-eight pain drawings were obtained from a baseline assessment of participants in a randomized clinical trial, in which single-level cervical radiculopathy was determined using MRI. Four experienced clinicians independently rated each pain drawing, attributing the pain distribution to a single nerve root (C4-C7). A post hoc analysis was performed to assess agreement. OUTCOME MEASURES: Percentage agreement and kappa values were used to assess the level of agreement. Topographic pain frequency maps were created for each cervical radiculopathy level as determined by MRI. RESULTS: The radiculopathy level determined from the pain drawings showed poor overall agreement with MRI (mean = 35.7%, K = -0.007 to 0.139). The inter-clinician agreement ranged from fair to moderate (K = 0.212-0.446). Topographic frequency maps revealed that pain distributions were widespread and overlapped markedly between patients presenting with different levels cervical radiculopathy. CONCLUSION: This study revealed a lack of agreement between the segmental level affected determined from the patient's pain drawing and the affected level as identified on MRI. The large overlap of pain and non-dermatomal distribution of pain reported by patients likely contributed to this result.