Raman Spectroscopy and Machine Learning Enables Estimation of Articular Cartilage Structural, Compositional, and Functional Properties.

OBJECTIVE: To differentiate healthy from artificially degraded articular cartilage and estimate its structural, compositional, and functional properties using Raman spectroscopy (RS). DESIGN: Visually normal bovine patellae (n = 12) were used in this study. Osteochondral plugs (n = 60) were prepared and artificially degraded either enzymatically (via Collagenase D or Trypsin) or mechanically (via impact loading or surface abrasion) to induce mild to severe cartilage damage; additionally, control plugs were prepared (n = 12). Raman spectra were acquired from the samples before and after artificial degradation. Afterwards, reference biomechanical properties, proteoglycan (PG) content, collagen orientation, and zonal (%) thickness of the samples were measured. Machine learning models (classifiers and regressors) were then developed to discriminate healthy from degraded cartilage based on their Raman spectra and to predict the aforementioned reference properties. RESULTS: The classifiers accurately categorized healthy and degraded samples (accuracy = 86%), and successfully discerned moderate from severely degraded samples (accuracy = 90%). On the other hand, the regression models estimated cartilage biomechanical properties with reasonable error (≤ 24%), with the lowest error observed in the prediction of instantaneous modulus (12%). With zonal properties, the lowest prediction errors were observed in the deep zone, i.e., PG content (14%), collagen orientation (29%), and zonal thickness (9%). CONCLUSION: RS is capable of discriminating between healthy and damaged cartilage, and can estimate tissue properties with reasonable errors. These findings demonstrate the clinical potential of RS.

A dose-neutral image quality comparison of different CBCT and CT systems using paranasal sinus imaging protocols and phantoms.

PURPOSE: To compare the image quality produced by equivalent low-dose and default sinus imaging protocols of a conventional dental cone-beam computed tomography (CBCT) scanner, an extremity CBCT scanner and a clinical multidetector computed tomography (MDCT) scanner. METHODS: Three different phantoms were scanned using dose-neutral ultra-low-dose and low-dose sinus imaging protocols, as well as default sinus protocols of each device. Quantified parameters of image quality included modulation transfer function (MTF) to characterize the spatial response of the imaging system, contrast-to-noise ratio, low contrast visibility, image uniformity and Hounsfield unit accuracy. MTF was calculated using the line spread and edge spread functions (LSF and ESF). RESULTS: The dental CBCT had superior performance over the extremity CBCT in each studied parameter at similar dose levels. The MDCT had better contrast-to-noise ratio, low contrast visibility and image uniformity than the CBCT scanners. However, the CBCT scanners had better resolution compared to the MDCT. Accuracy of HU values for different materials was on the same level between the dental CBCT and MDCT, but substantially poorer performance was observed with the extremity CBCT. CONCLUSIONS: The studied dental CBCT scanner showed superior performance over the studied extremity CBCT scanner when using dose-neutral imaging protocols. In case a dental CBCT is not available, the given extremity CBCT is still a viable option as it provides the benefit of high resolution over a conventional MDCT.

Assessment of ejection fraction and heart perfusion using myocardial perfusion single-photon emission computed tomography in Finland and Estonia: a multicenter phantom study.

OBJECTIVES: Myocardial SPECT/CT imaging is frequently performed to assess myocardial perfusion and dynamic parameters of heart function, such as ejection fraction (EF). However, potential pitfalls exist in the imaging chain that can unfavorably affect diagnosis and treatment. We performed a national cardiac quality control study to investigate how much SPECT/CT protocols vary between different nuclear medicine units in Finland, and how this may affect the heart perfusion and EF values. METHODS: Altogether, 21 nuclear medicine units participated with 27 traditional SPECT/CT systems and two cardiac-centered IQ-SPECT systems. The reproducibility of EF and the uniformity of perfusion were studied using a commercial dynamic heart phantom. SPECT/CT acquisitions were performed and processed at each participating unit using their own clinical protocol and with a standardized protocol. The effects of acquisition protocols and analysis routines on EF estimates and uniformity of perfusion were studied. RESULTS: Considerable variation in EF estimates and in the uniformity of perfusion were observed between the units. Uniformity of perfusion was improved in some units after applying the higher count-statistic standard acquisition protocol. EF estimates varied more due to differences in analysis routines than as a result of different acquisition protocols. The results obtained with the two IQ-SPECT systems differed substantially from the traditional multipurpose cameras. CONCLUSION: On average, the EF and heart perfusion were accurately estimated by SPECT/CT, but high errors could be produced if the acquisition and analysis routines were poorly optimized. Eight of the 21 participants altered their imaging protocol after this quality control tour.