Evaluation of T2 values and apparent diffusion coefficient of the masseter muscle by clenching

Complexity and data mining in dental research: A network medicine perspective on interceptive orthodontics

Procedures and models of computerized data analysis are becoming researchers' and practitioners' thinking partners by transforming the reasoning underlying biomedicine. Complexity theory, Network analysis and Artificial Intelligence are already approaching this discipline, intending to provide support for patient's diagnosis, prognosis and treatments. At the same time, due to the sparsity, noisiness and time-dependency of medical data, such procedures are raising many unprecedented problems related to the mismatch between the human mind's reasoning and the outputs of computational models. Thanks to these computational, non-anthropocentric models, a patient's clinical situation can be elucidated in the orthodontic discipline, and the growth outcome can be approximated. However, to have confidence in these procedures, orthodontists should be warned of the related benefits and risks. Here we want to present how these innovative approaches can derive better patients' characterization, also offering a different point of view about patient's classification, prognosis and treatment.

Molecular imaging in masseter muscle observed by muscle function magnetic resonance imaging and 31 P-magnetic resonance spectroscopy in patients with a jaw deformity

Background

Skeletal mandibular protrusion would influence to the muscle fatigue of the masticatory muscles. Establishing a diagnostic procedures combining physiological and biochemical information is necessary for quantitative evaluation of masticatory muscle fatigue.

Objective

The transverse relaxation time (T2 time) of muscle functional magnetic resonance imaging (mfMRI), and ³¹P‐magnetic resonance spectroscopy (MRS) were used to investigate the reliability as parameters for measuring the masseter muscle in patients with skeletal mandibular prognathism.

Method

The subjects were 19 patients diagnosed as skeletal mandibular protrusions and 19 healthy subjects as a control group. Transverse relaxation time (T2 value) determined by mfMRI along with creatine phosphate (PCr) and inorganic phosphorus (Pi) determined by ³¹P‐MRS before, during, and after clenching were used for molecular imaging of muscle fatigue.

Results

The average T2 value of the patient group was significantly higher than that of the healthy control group at rest. Furthermore, the average T2 value transiently increased in both groups during experimental clenching. The PCr and Pi showed a tendency toward a transient decrease and increases, respectively. The pH in the masseter muscle showed a transient decrease in both groups prior to and following experimental clenching. The pH in the masseter muscle of the patient group was significantly lower than that in the healthy control group at rest and recovery.

Conclusion

We showed mfMRI and ³¹P‐MRS are useful for evaluating masseter fatigue during clenching, and the masseter muscle in the prognathic patients showed more severe fatigue than the healthy controls.

Diagnosis of Prostate Cancer with Noninvasive Estimation of Prostate Tissue Composition by Using Hybrid Multidimensional MR Imaging: A Feasibility Study

Purpose To evaluate whether compartmental analysis by using hybrid multidimensional magnetic resonance (MR) imaging can be used to diagnose prostate cancer and determine its aggressiveness. Materials and Methods Twenty-two patients with prostate cancer underwent preoperative 3.0-T MR imaging. Axial images were obtained with hybrid multidimensional MR imaging by using all combinations of echo times (47, 75, 100 msec) and b values of 0, 750, 1500 sec/mm², resulting in a 3 × 3 array of data associated with each voxel. Volumes of the tissue components stroma, epithelium, and lumen were calculated by fitting the hybrid data to a three-compartment signal model, with distinct, paired apparent diffusion coefficient (ADC) and T2 values associated with each compartment. Volume fractions and conventional ADC and T2 were measured for regions of interest in sites of prostatectomy-verified malignancy (n = 28) and normal tissue (n = 71). Receiver operating characteristic (ROC) analysis was used to evaluate the performance of various parameters in differentiating prostate cancer from benign tissue. Results Compared with normal tissue, prostate cancer showed significantly increased fractional volumes of epithelium (23.2% ± 7.1 vs 48.8% ± 9.2, respectively) and reduced fractional volumes of lumen (26.4% ± 14.1 vs 14.0% ± 5.2) and stroma (50.5% ± 15.7 vs 37.2% ± 9.1) by using hybrid multidimensional MR imaging. The fractional volumes of tissue components show a significantly higher Spearman correlation coefficient with Gleason score (epithelium: ρ = 0.652, P = .0001; stroma: ρ = -0.439, P = .020; lumen: ρ = -0.390, P = .040) compared with traditional T2 values (ρ = -0.292, P = .132) and ADCs (ρ = -0.315, P = .102). The area under the ROC curve for differentiation of cancer from normal prostate was highest for fractional volume of epithelium (0.991), followed by fractional volumes of lumen (0.800) and stroma (0.789). Conclusion Fractional volumes of prostatic lumen, stroma, and epithelium change significantly when cancer is present. These parameters can be measured noninvasively by using hybrid multidimensional MR imaging and have the potential to improve the diagnosis of prostate cancer and determine its aggressiveness. ^© RSNA, 2018 Online supplemental material is available for this article.

Evaluation of diffusion parameters and T2 values of the masseter muscle during jaw opening, clenching, and rest

BACKGROUND

Diffusion-weighted imaging (DWI) and diffusion-tensor imaging (DTI) can be used to evaluate changes that accompany skeletal muscle contraction.

PURPOSE

To investigate whether jaw opening or closure affect the diffusion parameters of the masseter muscles (MMs).

MATERIAL AND METHODS

Eleven healthy volunteers were evaluated. Diffusion-tensor images were acquired to obtain the primary (λ(1)), secondary (λ(2)), and tertiary eigenvalues (λ(3)). We estimated these parameters at three different locations: at the level of the mandibular notch for the superior site, the level of the mandibular foramen for the middle site, and the root apex of the mandibular molars for the inferior site.

RESULTS

Both λ(2) and λ(3) during jaw opening were significantly lower than that at rest at the superior (P = 0.006, P < 0.0001, respectively) and middle site (P = 0.004, P = 0.0001, respectively); however, the change in λ(1) was not significant. At the lower site, no parameter was significantly different at rest and during jaw opening. There was no significant difference in T2 between at rest (40.3 ± 4.4 ms) and during jaw opening (39.2 ± 2.7 ms; P = 0.12). The changes induced by jaw closure were marked at the inferior site. In the middle and inferior sites, the three eigenvalues were increased by jaw closure, and the changes in λ(1) (P = 0.0145, P = 0.0107, respectively) and λ(2) (P = 0.0003, P = 0.0001) were significant (especially λ(2)).

CONCLUSION

The eigenvalues for diffusion of the MM were sensitive to jaw position. The recruitment of muscle fibers, specific to jaw position, reflects the differences in changes in muscle diffusion parameters.