Development of a novel classification system for anatomical variants of the puboprostatic ligaments with expert validation

Analysis of the mandibular canal course using unsupervised machine learning algorithm

Objectives

Anatomical structure classification is necessary task in medical field, but the inevitable variability of interpretation among experts makes reliable classification difficult. This study aims to introduce cluster analysis, unsupervised machine learning method, for classification of three-dimensional (3D) mandibular canal (MC) courses, and to visualize standard MC courses derived from cluster analysis in the Korean population.

Materials and methods

A total of 429 cone-beam computed tomography images were used. Four sites in the mandible were selected for the measurement of the MC course and four parameters, two vertical and two horizontal parameters were measured per site. Cluster analysis was carried out as follows: parameter measurement, parameter normalization, cluster tendency evaluation, optimal number of clusters determination, and k-means cluster analysis. The 3D MC courses were classified into three types with statistically significant mean differences by cluster analysis.

Results

Cluster 1 showed a smooth line running towards the lingual side in the axial view and a steep slope in the sagittal view. Cluster 2 ran in an almost straight line closest to the lingual and inferior border of mandible. Cluster 3 showed the pathway with a bent buccally in the axial view and an increasing slope in the sagittal view in the posterior area. Cluster 2 showed the highest distribution (42.1%), and males were more widely distributed (57.1%) than the females (42.9%). Cluster 3 comprised similar ratio of male and female cases and accounted for 31.9% of the total distribution. Cluster 1 had the least distribution (26.0%) Distributions of the right and left sides did not show a statistically significant difference.

Conclusion

The MC courses were automatically classified as three types through cluster analysis. Cluster analysis enables the unbiased classification of the anatomical structures by reducing observer variability and can present representative standard information for each classified group.

The topography and morphometrics of the pubic ligaments

BACKGROUND

Conflicting anatomical reports and the little attention given to the pubic ligaments impede the interpretation of radiological and clinical examinations on groin pain. Morphometric data on the pubic ligaments are lacking.

METHODS

The muscular relations of the symphysis pubis were examined in layered dissection (n = 10), hemipelves (n = 60) and (un)stained plastinated body slices of body donors (n = 3). The sagittal and coronal areas, width, mean and maximum thickness of pubic ligaments were determined.

RESULTS

The adductor longus, brevis, rectus abdominis and pyramidalis muscles are attached to the anterior pubic ligament (APL). The adductor brevis and gracilis muscle are connected to the inferior pubic ligament (IPL). The IPL and superior pubic ligament (SPL) are thicker than the APL and posterior pubic ligament (PPL). The PPL is the thinnest pubic ligament. The APL has a larger sagittal area in women than in men compared to the IPL. The SPL and IPL are thicker in men compared to women.

CONCLUSION

The APL is the ligamentous anchor for the originating and inserting muscles. Investigations of the pubic ligaments might help to determine symphysis instability or severity of injury and should be included as a further criterion for surgical management.

Clinical Anatomy of the Puboprostatic Ligament for the Safe Guidance for the Prostate Surgery

OBJECTIVE

To provide the anatomy of the puboprostatic ligament and related structures to save urogenital competence after prostatectomy.

MATERIALS AND METHODS

Pelvic areas of 31 adult cadavers were dissected to figure out the shape, number, and location of the puboprostatic ligaments.

RESULTS

The puboprostatic ligament was the most important support structure between the pubic bone and prostate gland. Puboprostatic ligaments were bilaterally single (61.3%), bilaterally double (19.4%), or mixed (19.4%). Ligaments were mostly I-shaped (53.8%). If ligaments had extra attachment to or from the arcuate line, the ligaments were λ-shaped (36.3%), or Y-shaped (8.8%). In one case, the ligament had a central fusion with an irregular shape. I-shaped puboprostatic ligaments were observed more frequently in specimens with double ligaments, while λ-shaped puboprostatic ligaments were observed more frequently in the cases with single ligaments. The average distance between both puboprostatic ligaments was 8.1 mm at the pubic site and 14.2 mm at the prostate site. The distance was narrower when the specimen had double puboprostatic ligaments on both sides. The neurovascular bundle ran beneath the puboprostatic ligament. If the ligament was the λ-shaped type, the neurovascular bundle frequently pierced the lateral band of the ligament.

CONCLUSION

Puboprostatic ligaments hold and stabilize the prostate against the pubic bone. It is believed that a pelvis with bilateral, double puboprostatic ligaments would have advantages in urogenital competence. The morphologic data of the shape, multiplicity, and location of the PPLs would help to make a plan to approach the prostate.

Current Role of Active Surveillance in the Management of a Small Renal Mass

Renal cell carcinoma accounts for 3-4% of adult malignant neoplasms and over 65,000 new cases of kidney cancer were diagnosed in the USA in 2013 [1, 2]. Widespread use of abdominal imaging is leading to an increased incidence in the detection of small renal masses (SRMs) among other causes [1-4]. In light of recent literature on the role of percutaneous renal mass biopsy and retrospective data analysis, surveillance for renal masses ≤4 cm is likely to become more common especially in patients with less aggressive pathology, advanced age and multiple medical comorbidities.