Raman spectroscopy of stored red blood cell concentrate within sealed transfusion blood bags.

The standard practice in blood banks worldwide involves storage of red blood cells (RBCs) in plastic bags until they are needed for transfusion. During storage, the cells gradually degrade in functionality, a condition described as RBC storage lesion. Standard analytical techniques cannot assess the blood quality without breaching the sterility of the transfusion bag. In this study, we employed a commercially available spatially offset Raman spectroscopy (SORS) system using a custom designed protocol to non-invasively explore the biochemical changes in RBC concentrate of healthy donors over a storage period of approximately 42 days in standard transfusion bags, under standard storage conditions. The results reveal an increase in the oxygenation state of haemoglobin over the storage period for all donors, but different profiles for each donor. This study demonstrates the feasibility of acquiring consistent biochemical information relevant to the quality of stored blood, in situ through sealed blood transfusion bags using a commercially available instrument.

Non-invasive spectroscopy of transfusable red blood cells stored inside sealed plastic blood-bags.

After being separated from (donated) whole blood, red blood cells are suspended in specially formulated additive solutions and stored (at 4 °C) in polyvinyl chloride (PVC) blood-bags until they are needed for transfusion. With time, the prepared red cell concentrate (RCC) is known to undergo biochemical changes that lower effectiveness of the transfusion, and thus regulations are in place that limit the storage period to 42 days. At present, RCC is not subjected to analytical testing prior to transfusion. In this study, we use Spatially Offset Raman Spectroscopy (SORS) to probe, non-invasively, the biochemistry of RCC inside sealed blood-bags. The retrieved spectra compare well with conventional Raman spectra (of sampled aliquots) and are dominated by features associated with hemoglobin. In addition to the analytical demonstration that SORS can be used to retrieve RCC spectra from standard clinical blood-bags without breaking the sterility of the system, the data reveal interesting detail about the oxygenation-state of the stored cells themselves, namely that some blood-bags unexpectedly contain measurable amounts of deoxygenated hemoglobin after weeks of storage. The demonstration that chemical information can be obtained non-invasively using spectroscopy will enable new studies of RCC degeneration, and points the way to a Raman-based instrument for quality-control in a blood-bank or hospital setting.

Investigation of a 2D two-point maximum entropy regularization method for signal-to-noise ratio enhancement: application to CT polymer gel dosimetry.

This study presents a new method of image signal-to-noise ratio (SNR) enhancement by utilizing a newly developed 2D two-point maximum entropy regularization method (TPMEM). When utilized as an image filter, it is shown that 2D TPMEM offers unsurpassed flexibility in its ability to balance the complementary requirements of image smoothness and fidelity. The technique is evaluated for use in the enhancement of x-ray computed tomography (CT) images of irradiated polymer gels used in radiation dosimetry. We utilize a range of statistical parameters (e.g. root-mean square error, correlation coefficient, error histograms, Fourier data) to characterize the performance of TPMEM applied to a series of synthetic images of varying initial SNR. These images are designed to mimic a range of dose intensity patterns that would occur in x-ray CT polymer gel radiation dosimetry. Analysis is extended to a CT image of a polymer gel dosimeter irradiated with a stereotactic radiation therapy dose distribution. Results indicate that TPMEM performs strikingly well on radiation dosimetry data, significantly enhancing the SNR of noise-corrupted images (SNR enhancement factors >15 are possible) while minimally distorting the original image detail (as shown by the error histograms and Fourier data). It is also noted that application of this new TPMEM filter is not restricted exclusively to x-ray CT polymer gel dosimetry image data but can in future be extended to a wide range of radiation dosimetry data.

Accuracy and precision of manual baseline determination.

Vibrational spectra often require baseline removal before further data analysis can be performed. Manual (i.e., user) baseline determination and removal is a common technique used to perform this operation. Currently, little data exists that details the accuracy and precision that can be expected with manual baseline removal techniques. This study addresses this current lack of data. One hundred spectra of varying signal-to-noise ratio (SNR), signal-to-baseline ratio (SBR), baseline slope, and spectral congestion were constructed and baselines were subtracted by 16 volunteers who were categorized as being either experienced or inexperienced in baseline determination. In total, 285 baseline determinations were performed. The general level of accuracy and precision that can be expected for manually determined baselines from spectra of varying SNR, SBR, baseline slope, and spectral congestion is established. Furthermore, the effects of user experience on the accuracy and precision of baseline determination is estimated. The interactions between the above factors in affecting the accuracy and precision of baseline determination is highlighted. Where possible, the functional relationships between accuracy, precision, and the given spectral characteristic are detailed. The results provide users of manual baseline determination useful guidelines in establishing limits of accuracy and precision when performing manual baseline determination, as well as highlighting conditions that confound the accuracy and precision of manual baseline determination.

Revealing system dynamics through decomposition of the perturbation domain in two-dimensional correlation spectroscopy.

A technique is presented to simply and effectively decompose the perturbation domain in two-dimensional (2D) correlation maps calculated on a given set of vibrational spectra. Decomposition of the perturbation domain exposes a wealth of kinetic information complementary to the information extracted from conventional 2D correlation spectroscopy. It is shown that the technique produces "perturbation profile maps" that can be utilized in both the interpretation of the conventional 2D correlation maps and the independent kinetic analysis of the given system. Discrimination between spectral features exhibiting similar, but not identical, dynamics is facilitated by the decomposition, and spectral features exhibiting identical dynamics over the perturbation interval are quickly identified. Spectral features exhibiting similar dynamics over only a sub-range of the full perturbation are also identifiable. Interpretation of phase information illuminated in synchronous and asynchronous maps is simplified. Comparison between similar spectral features present in different samples is facilitated with the technique. The simplicity and ease of implementation of the technique make decomposition of the perturbation domain a valuable addition to the tools available in 2D correlation analysis.

Identification and interpretation of generalized two-dimensional correlation spectroscopy features through decomposition of the perturbation domain.

Generalized two-dimensional correlation spectroscopy offers great scope for revealing the behavior of relationships between components of a system under empirical study. We have developed methods that aid in the interpretation of two-dimensional correlation spectroscopy. These methods include reference patterns for two-dimensional correlation and correlation coefficient maps, their superposition and joint interpretation, and the use of delta functions to decompose them in the perturbation domain. We show how their joint use permits discrimination between similar two-dimensional correlation map features on the basis of different correlation coefficients. We also show how the decomposition of maps into the perturbation domain reflects the dynamic behavior of spectral features over the course of the perturbation and permits discrimination between otherwise highly similar two-dimensional correlation cross-peaks. These approaches simplify the interpretation of two-dimensional correlation spectroscopy maps and facilitate access to their rich information content.