The cervical vertebral maturation method: A user's guide

The cervical vertebral maturation (CVM) method is used to determine the craniofacial skeletal maturational stage of an individual at a specific time point during the growth process. This diagnostic approach uses data derived from the second (C2), third (C3), and fourth (C4) cervical vertebrae, as visualized in a two-dimensional lateral cephalogram. Six maturational stages of those three cervical vertebrae can be determined, based on the morphology of their bodies. The first step is to evaluate the inferior border of these vertebral bodies, determining whether they are flat or concave (ie, presence of a visible notch). The second step in the analysis is to evaluate the shape of C3 and C4. These vertebral bodies change in shape in a typical sequence, progressing from trapezoidal to rectangular horizontal, to square, and to rectangular vertical. Typically, cervical stages (CSs) 1 and CS 2 are considered prepubertal, CS 3 and CS 4 circumpubertal, and CS 5 and CS 6 postpubertal. Criticism has been rendered as to the reproducibility of the CVM method. Diminished reliability may be observed at least in part due to the lack of a definitive description of the staging procedure in the literature. Based on the now nearly 20 years of experience in staging cervical vertebrae, this article was prepared as a “user's guide” that describes the CVM stages in detail in attempt to help the reader use this approach in everyday clinical practice

Interferometric cavity ring-down technique for ultra-high Q-factor microresonators

Microresonators (MRs) are key components in integrated optics. As a result, the estimation of their energy storage capacity as measured by the quality factor (Q) is crucial. However, in MR with high/ultra-high Q, the surface-wall roughness dominates the intrinsic Q and generates a coupling between counter-propagating modes. This splits the usual sharp single resonance and makes difficult the use of classical methods to assess Q. Here, we theoretically show that an interferometric excitation can be exploited in a Cavity Ring-Down (CRD) method to measure the ultimate Q of a MR. In fact, under suitable conditions, the resonant doublet merges into a single Lorentzian and the time dynamics of the MR assumes the usual behavior of a single-mode resonator unaffected by backscattering. This allows obtaining a typical exponential decay in the charging and discharging time of the MR, and thus, estimating its ultimate Q by measuring the photon lifetime.Comment: 5 pages and 2 figure

A nonsurgical approach to treatment of high-angle Class II malocclusion

Malocclusions with a hyperdivergent vertical facial pattern are often difficult to treat without a combined surgical/orthodontic approach. The aim of this article is to describe a nonsurgical approach to the treatment of a high-angle Class II malocclusion in a growing patient. Some fundamental aspects, such as correct diagnosis, treatment timing, favorable mandibular growth pattern, and patient compliance, proved to be critical to correct the severe dentoskeletal disharmony. © 2008 by The EH Angle Education and Research Foundation, Inc

Using Networks To Understand Medical Data: The Case of Class III Malocclusions

A system of elements that interact or regulate each other can be represented by a mathematical object called a network. While network analysis has been successfully applied to high-throughput biological systems, less has been done regarding their application in more applied fields of medicine; here we show an application based on standard medical diagnostic data. We apply network analysis to Class III malocclusion, one of the most difficult to understand and treat orofacial anomaly. We hypothesize that different interactions of the skeletal components can contribute to pathological disequilibrium; in order to test this hypothesis, we apply network analysis to 532 Class III young female patients. The topology of the Class III malocclusion obtained by network analysis shows a strong co-occurrence of abnormal skeletal features. The pattern of these occurrences influences the vertical and horizontal balance of disharmony in skeletal form and position. Patients with more unbalanced orthodontic phenotypes show preponderance of the pathological skeletal nodes and minor relevance of adaptive dentoalveolar equilibrating nodes. Furthermore, by applying Power Graphs analysis we identify some functional modules among orthodontic nodes. These modules correspond to groups of tightly inter-related features and presumably constitute the key regulators of plasticity and the sites of unbalance of the growing dentofacial Class III system. The data of the present study show that, in their most basic abstraction level, the orofacial characteristics can be represented as graphs using nodes to represent orthodontic characteristics, and edges to represent their various types of interactions. The applications of this mathematical model could improve the interpretation of the quantitative, patient-specific information, and help to better targeting therapy. Last but not least, the methodology we have applied in analyzing orthodontic features can be applied easily to other fields of the medical science.</p