Results of Abductor Pollicis Longus Suspension Ligamentoplasty for Treatment of Advanced First Carpometacarpal Arthritis

Background

Suspension ligamentoplasty using abductor pollicis longus (APL) tendon without bone tunneling, was introduced as one of the techniques for treatment of advanced first carpometacarpal (CMC) arthritis. The purpose of this study was to evaluate the radiologic and clinical results of APL suspension ligamentoplasty.

Methods

The medical records of 19 patients who underwent APL suspension ligamentoplasty for advanced first CMC arthritis between January 2008 and May 2012 were reviewed retrospectively. The study included 13 female and 6 male patients, whose mean age was 62 years (range, 43 to 82 years). For clinical evaluation, we assessed the grip and pinch power, radial and volar abduction angle, thumb adduction (modified Kapandji index), including visual analogue scale (VAS) and Disabilities of the Arm, Shoulder and Hand (DASH) scores. Radiologic evaluation was performed using simple radiographs.

Results

The mean follow-up was 36 months (range, 19 to 73.7 months). Mean power improved from 18.3 to 27 kg for grip power, from 2.8 to 3.5 kg for tip pinch, and from 4.3 to 5.4 kg for power pinch. All patients showed decreased VAS from 7.2 to 1.7. Radial abduction improved from 71° preoperatively to 82° postoperatively. The modified Kapandji index showed improvement from 6 to 7.3, and mean DASH was improved from 41 to 17.8. The height of the space decreased from 10.8 to 7.1 mm. Only one case had a complication involving temporary sensory loss of the first dorsal web space, which resolved spontaneously.

Conclusions

The APL suspension ligamentoplasty for treatment of advanced first CMC arthritis yielded satisfactory functional results.     

Hydrolytic Stability of Methacrylamide and Methacrylate in Gelatin Methacryloyl and Decoupling of Gelatin Methacrylamide from Gelatin Methacryloyl through Hydrolysis

Gelatin methacryloyl (GelMA; GM) is a promising nature‐derived photocurable material that can mimic the extracellular matrix because GelMA features tailorable mechanical properties, proteolytic degradation, and good cell adhesion. GelMA contains not only methacrylamide but also methacrylate. However, the hydrolytic stability of methacrylamide and methacrylate groups of GelMA in aqueous solutions has not been scrutinized. Here, the structural change of GelMA through hydrolysis is investigated for the first time. The structural change of hydrolyzed GelMA is quantitatively identified using colorimetric and ¹H NMR methods. The methacrylate groups decompose markedly at high pH solutions, but the methacrylamide groups remain stable. Further, pure gelatin methacrylamide is successfully decoupled from GelMA for a better understanding of GelMA structure and future use for biomedical applications.     

Development of an algorithm to automatically compress a CT image to visually lossless threshold

Background

To develop an algorithm to predict the visually lossless thresholds (VLTs) of CT images solely using the original images by exploiting the image features and DICOM header information for JPEG2000 compression and to evaluate the algorithm in comparison with pre-existing image fidelity metrics.

Methods

Five radiologists independently determined the VLT for 206 body CT images for JPEG2000 compression using QUEST procedure. The images were divided into training (n?=?103) and testing (n?=?103) sets. Using the training set, a multiple linear regression (MLR) model was constructed regarding the image features and DICOM header information as independent variables and regarding the VLTs determined with median value of the radiologists’ responses (VLT_rad) as dependent variable, after determining an optimal subset of independent variables by backward stepwise selection in a cross-validation scheme.The performance was evaluated on the testing set by measuring absolute differences and intra-class correlation (ICC) coefficient between the VLT_rad and the VLTs predicted by the model (VLT_model). The performance of the model was also compared two metrics, peak signal-to-noise ratio (PSNR) and high-dynamic range visual difference predictor (HDRVDP). The time for computing VLTs between MLR model, PSNR, and HDRVDP were compared using the repeated ANOVA with a post-hoc analysis. P?<?0.05 was considered to indicate a statistically significant difference.

Results

The means of absolute differences with the VLT_rad were 0.58 (95% CI, 0.48, 0.67), 0.73 (0.61, 0.85), and 0.68 (0.58, 0.79), for the MLR model, PSNR, and HDRVDP, respectively, showing significant difference between them (p?<?0.01). The ICC coefficients of MLR model, PSNR, and HDRVDP were 0.88 (95% CI, 0.81, 0.95), 0.85 (0.79, 0.91), and 0.84 (0.77, 0.91). The computing times for calculating VLT per image were 1.5?±?0.1 s, 3.9?±?0.3 s, and 68.2?±?1.4 s, for MLR metric, PSNR, and HDRVDP, respectively.

Conclusions

The proposed MLR model directly predicting the VLT of a given CT image showed competitive performance to those of image fidelity metrics with less computational expenses. The model would be promising to be used for adaptive compression of CT images.