The ribs: anatomic and radiologic considerations

Multiple rib fractures confused with loss of lung volume on chest X-ray

A 90-year-old woman with osteoporosis and no recent injury history visited the hospital for a regular checkup. Chest X-ray showed a loss of right upper lung volume. Although we suspected pulmonary parenchymal or pleural disease, computed tomography revealed multiple rib fractures on the right side, which caused thoracic deformation.

The Development of an Automatic Rib Sequence Labeling System on Axial Computed Tomography Images with 3-Dimensional Region Growing

This paper proposes a development of automatic rib sequence labeling systems on chest computed tomography (CT) images with two suggested methods and three-dimensional (3D) region growing. In clinical practice, radiologists usually define anatomical terms of location depending on the rib’s number. Thus, with the manual process of labeling 12 pairs of ribs and counting their sequence, it is necessary to refer to the annotations every time the radiologists read chest CT. However, the process is tedious, repetitive, and time-consuming as the demand for chest CT-based medical readings has increased. To handle the task efficiently, we proposed an automatic rib sequence labeling system and implemented comparison analysis on two methods. With 50 collected chest CT images, we implemented intensity-based image processing (IIP) and a convolutional neural network (CNN) for rib segmentation on this system. Additionally, three-dimensional (3D) region growing was used to classify each rib’s label and put in a sequence label. The IIP-based method reported a 92.0% and the CNN-based method reported a 98.0% success rate, which is the rate of labeling appropriate rib sequences over whole pairs (1st to 12th) for all slices. We hope for the applicability thereof in clinical diagnostic environments by this method-efficient automatic rib sequence labeling system.

Pediatric rib pathologies: clinicoimaging scenarios and approach to diagnosis

Pathologies involving the ribs are diverse in nature, including entities specific to the pediatric population as well as shared pathologies with adults. These can be either localized within or adjacent to the rib, but may also cause rib alteration as a component of a systemic process. To better understand these disorders, we discuss several common rib pathologies in the context of their clinical presentation and pertinent imaging findings. In addition, we review the imaging modalities that may be used to evaluate the ribs. Encompassing both the clinical and imaging aspects of pediatric rib pathologies, this review aims to increase pediatric and musculoskeletal radiologists' awareness of the spectrum of disease and how to leverage a pattern-based approach.

The prevalence of 11 ribs and its potential implications in spine surgery

INTRODUCTION

Wrong level surgery is a preventable event in spine surgery. The thoracic spine given its length and anatomical landmarks remains the most challenging spine section for accurate localization during surgery. Traditionally, counting the ribs with intraoperative fluoroscopy is the preferred method. The incidence of 11 ribs instead of the conventional 12 ribs is not examined in current scientific literature, even though the incidence of 11 ribs may have a substantial impact on spinal procedures and the outcomes. This is especially relevant if patients have a potential surgical pathology of their thoracic spine. In this case series we sought to investigate the prevalence of 11 ribs in a trauma population.

METHODS

A retrospective review was conducted of patients presenting with thoracolumbar fractures at our Level I Trauma Center between 2017 and 2018. CT scans were obtained and analyzed by counting the number of ribs.

RESULTS

Out of 234 patients who were consulted for thoraco-lumbar fractures by spine specialists, 8 patients had 11 ribs which results in a prevalence of 3.4 % in this population. Within these 8 patients, 5 were male (62.5 %).

CONCLUSIONS

Spine surgeons should consider the possibility of numeric variation of ribs when evaluating thoracolumbar spine imaging. In a trauma population with spine fractures, the prevalence of 11 ribs is 3.4 %. Given the not insignificant prevalence of this variant in potentially surgical spine patients, the spine surgeon should remain vigilant of this anatomical variant.

Intrathoracic rib: rare rib anomaly, review of the literature and proposal for classification

Background: Intrathoracic ribs are very rare congenital anomalies, and often discovered incidentally on chest X-ray. Since its first description by Lutz in 1947, approximately 50 cases have been reported in the literature till date. The aim is to review the all reported intrathoracic ribs, summarize their clinical features, and propose a potential classification. Methods: All relevant literatures were searched and reviewed. The terms include intrathoracic rib, intrathoracic bifid rib, trans-thoracic rib and intrathoracic rib anomaly. We have summarized the first finding events, origination, distribution, related anomalies and imaging features of intrathoracic rib, and propose an updated classification. Results: The patients' age at initial finding was from six weeks to 79 years old. Of all, sixty percent was less than 30 years old. There was no difference in gender. Most of them were reported by authors in western countries (85.3%, 58/68), and incidental findings by radiologist and respiratory physician. The intrathoracic rib occurs more frequently on the right side, and is usually single and unilateral. According to the new classification, type I and II was account for 45.6% and 35.3%, respectively. Conclusion: Intrathoracic rib is rare findings in clinical practice. It is useful that radiologists or clinician are familiarized with the imaging appearances of these malformations. These anomalies reflect some disturbances during the embryo development, leading us to propose a potential classification that could contribute to a better understanding of this rib anomaly.

Anatomical variations and congenital anomalies of the ribs revisited by multidetector computed tomography

As they are asymptomatic or have a nonspecific, anatomical variations of the ribs are usually detected as incidental findings on imaging studies. They may be isolated changes or can be related to anomalies or clinical syndromes. Such variations are easily overlooked on conventional radiography and computed tomography if they are not actively investigated, mainly because most indications for a chest X-ray studies aim to evaluate the lung parenchyma and mediastinal structures. The objective of this pictorial essay was to use multislice computed tomography images to illustrate the imaging aspects of the main anatomical variations and congenital anomalies of the ribs.

Evaluation of a multiview architecture for automatic vertebral labeling of palliative radiotherapy simulation CT images

PURPOSE

The purpose of this work was to evaluate the performance of X-Net, a multiview deep learning architecture, to automatically label vertebral levels (S2-C1) in palliative radiotherapy simulation CT scans.

METHODS

For each patient CT scan, our automated approach 1) segmented spinal canal using a convolutional-neural network (CNN), 2) formed sagittal and coronal intensity projection pairs, 3) labeled vertebral levels with X-Net, and 4) detected irregular intervertebral spacing using an analytic methodology. The spinal canal CNN was trained via fivefold cross validation using 1,966 simulation CT scans and evaluated on 330 CT scans. After labeling vertebral levels (S2-C1) in 897 palliative radiotherapy simulation CT scans, a volume of interest surrounding the spinal canal in each patient's CT scan was converted into sagittal and coronal intensity projection image pairs. Then, intensity projection image pairs were augmented and used to train X-Net to automatically label vertebral levels using fivefold cross validation (n = 803). Prior to testing upon the final test set (n = 94), CT scans of patients with anatomical abnormalities, surgical implants, or other atypical features from the final test set were placed in an outlier group (n = 20), whereas those without these features were placed in a normative group (n = 74). The performance of X-Net, X-Net Ensemble, and another leading vertebral labeling architecture (Btrfly Net) was evaluated on both groups using identification rate, localization error, and other metrics. The performance of our approach was also evaluated on the MICCAI 2014 test dataset (n = 60). Finally, a method to detect irregular intervertebral spacing was created based on the rate of change in spacing between predicted vertebral body locations and was also evaluated using the final test set. Receiver operating characteristic analysis was used to investigate the performance of the method to detect irregular intervertebral spacing.

RESULTS

The spinal canal architecture yielded centroid coordinates spanning S2-C1 with submillimeter accuracy (mean ± standard deviation, 0.399 ± 0.299 mm; n = 330 patients) and was robust in the localization of spinal canal centroid to surgical implants and widespread metastases. Cross-validation testing of X-Net for vertebral labeling revealed that the deep learning model performance (F1 score, precision, and sensitivity) improved with CT scan length. The X-Net, X-Net Ensemble, and Btrfly Net mean identification rates and localization errors were 92.4% and 2.3 mm, 94.2% and 2.2 mm, and 90.5% and 3.4 mm, respectively, in the final test set and 96.7% and 2.2 mm, 96.9% and 2.0 mm, and 94.8% and 3.3 mm, respectively, within the normative group of the final test set. The X-Net Ensemble yielded the highest percentage of patients (94%) having all vertebral bodies identified correctly in the final test set when the three most inferior and superior vertebral bodies were excluded from the CT scan. The method used to detect labeling failures had 67% sensitivity and 95% specificity when combined with the X-Net Ensemble and flagged five of six patients with atypical vertebral counts (additional thoracic (T13), additional lumbar (L6) or only four lumbar vertebrae). Mean identification rate on the MICCAI 2014 dataset using an X-Net Ensemble was increased from 86.8% to 91.3% through the use of transfer learning and obtained state-of-the-art results for various regions of the spine.

CONCLUSIONS

We trained X-Net, our unique convolutional neural network, to automatically label vertebral levels from S2 to C1 on palliative radiotherapy CT images and found that an ensemble of X-Net models had high vertebral body identification rate (94.2%) and small localization errors (2.2 ± 1.8 mm). In addition, our transfer learning approach achieved state-of-the-art results on a well-known benchmark dataset with high identification rate (91.3%) and low localization error (3.3 mm ± 2.7 mm). When we pre-screened radiotherapy CT images for the presence of hardware, surgical implants, or other anatomic abnormalities prior to the use of X-Net, it labeled the spine correctly in more than 97% of patients and 94% of patients when scans were not prescreened. Automatically generated labels are robust to widespread vertebral metastases and surgical implants and our method to detect labeling failures based on neighborhood intervertebral spacing can reliably identify patients with an additional lumbar or thoracic vertebral body.

Pediatric Thoracic Anatomic Variants: What Radiologists Need to Know

Anatomic variants are common incidental findings in pediatric chest imaging and can be mistaken for true underlying pathology, sometimes resulting in unnecessary additional imaging evaluation or invasive procedures. Clear understanding of the imaging characteristics and clinical significance of anatomic thoracic variants is important for accurate diagnosis and avoidance of unnecessary intervention. This article provides an up-to-date review of anatomic variants in the pediatric chest to increase knowledge and aide in timely, correct diagnosis.

External rib structure can be predicted using mathematical models: An anatomical study with application to understanding fractures and intercostal muscle function

As ribs adapt to stress like all bones, and the chest behaves as a pressure vessel, the effect of stress on the ribs can be determined by measuring rib height and thickness. Rib height and thickness (depth) were measured using CT scans of seven rib cages from anonymized cadavers. A Finite Element Analysis (FEA) model of a rib cage was constructed using a validated approach and used to calculate intramuscular forces as the vectors of both circumferential and axial chest wall forces at right angles to the ribs. Nonlinear quadratic models were used to relate rib height and rib thickness to rib level, and intercostal muscle force to vector stress. Intercostal muscle force was also related to vector stress using Pearson correlation. For comparison, rib height and thickness were measured on CT scans of children. Rib height increased with rib level, increasing by 13% between the 3rd and 7th rib levels, where the 7th/8th rib was the widest part or "equator" of the rib cage, P < 0.001 (t-test). Rib thickness showed a statistically significant 23% increase between the 3rd and 7th ribs, P = 0.004 (t-test). Intercostal muscle force was significantly related to vector stress, Pearson correlation r = 0.944, P = 0.005. The three nonlinear quadratic models developed all had statistically significant parameter estimates with P < 0.03. External rib morphology, in particular rib height and thickness, can be predicted using statistical mathematical models. Rib height is significantly related to the calculated intercostal muscle force, showing that environmental factors affect external rib morphology.

Abnormal rib count in scoliosis surgery: impact on the reporting of spinal fusion levels

PURPOSE

Variation in rib numbering has been noted in adolescent idiopathic scoliosis (AIS), but its effect on the reporting of fusion levels has not been studied. We hypothesized that vertebral numbering variations can lead to differing documentation of fusion levels.

METHODS

We examined the radiographs of 161 surgical AIS patients and 179 control patients without scoliosis. For AIS patients, the operative report of fusion levels was compared to conventional vertebral labeling from the first thoracic level and proceeding caudal. We defined normal counts as 12 thoracic (rib-bearing) and five lumbar (non-rib-bearing) vertebrae. We compared our counts with data from 181 anatomic specimens.

RESULTS

Among AIS patients, 22 (14 %) had an abnormal number of ribs and 29 (18 %) had either abnormal rib or lumbar count. In 12/29 (41 %) patients, the operative report differed from conventional labeling by one level, versus 3/132 (2 %) patients with normal numbering (p < 0.001). However, there were no cases seen of wrong fusion levels based on curve pattern. Among controls, 11 % had abnormal rib count (p = 0.41) compared to the rate in AIS. Anatomic specimen data did not differ in abnormal rib count (p = 1.0) or thoracolumbar pattern (p = 0.59).

CONCLUSIONS

The rate of numerical variations in the thoracolumbar vertebrae of AIS patients is equivalent to that in the general population. When variations in rib count are present, differences in numbering levels can occur. In the treatment of scoliosis, no wrong fusion levels were noted. However, for both scoliosis patients and the general population, we suggest adherence to conventional labeling to enhance clarity.

Additional circular intercostal space created by bifurcation of the left 3rd rib and its costal cartilage: a case report

INTRODUCTION

In the thorax there are normally 11 pairs of intercostal spaces: the spaces between adjacent ribs. The intercostal spaces contain intercostal muscles, intercostal nerves and vessels.

CASE PRESENTATION

During a routine dissection for undergraduate medical students, we observed a variation involving the left 3rd rib and 3rd costal cartilage in the cadaver of a man of Indian ethnicity aged about 65 years. The left 3rd rib and its costal cartilage were bifurcated at their costochondral junction enclosing a small circular additional intercostal space. Muscle tissue covered by deep fascia was present in this circular intercostal space. The muscle in the circular intercostal space received its nerve supply from a branch of the 2nd intercostal nerve.

CONCLUSIONS

Knowledge of such variations is helpful to surgeons operating on the anterior thoracic wall involving ribs and intercostal spaces. Knowing the possibility of the presence of an additional space between normal intercostal spaces can guide a surgeon through to a successful surgery.

Correlative anatomy for the sternum and ribs, costovertebral angle, chest wall muscles and intercostal spaces, thoracic outlet

The structures of the chest wall and thoracic outlet are complex. A working knowledge of their anatomy and of its variations is essential to any thoracic surgeon working in the area. Correlating imaging with anatomy is just as important if one wants to recognize surgical indications, and potential operating difficulties. In the past, conventional radiographic examination was the norm but interpretation was often difficult and incomplete. Currently, CT and MRI are the best available imaging tools, and most times they have complementary roles in the evaluation of chest wall anatomy.

Counting ribs on CT by assessing costal attachments to the proximal xiphoid: is this method accurate?

OBJECTIVES

To evaluate the usefulness of the method of counting ribs by assessing anatomic variations of the attachments of costal cartilages to the proximal xiphoid.

MATERIALS AND METHODS

From January to September 2005, 224 subjects (136 men, 88 women, age 13 to 89 years, mean age 55 years) underwent computed tomography examination of the chest. Axial images of the chest were obtained on a 16-slice multidetector computed tomography. Counting ribs was performed by using the medial clavicle as an anatomic landmark to identify the first costal cartilage. We analyzed variety and incidence of the attachment patterns of costal cartilages to the proximal xiphoid.

RESULT

Out of the 224 patients, the last costal attachments to the proximal xiphoid were the sixth costal cartilages bilaterally for 2 (0.9%) subjects, one 6th and one 7th for 4 (1.8%) subjects, bilateral seventh for 191 (85.3%) subjects, one 7th and one 8th for 15 (6.7%) subjects, and bilateral eighth for 12 (5.4%) subjects.

CONCLUSIONS

The method of counting ribs from the proximal xiphoid is inaccurate because the sixth, seventh, and eighth costal cartilages may each attach to the proximal xiphoid.

Segmentation of the posterior ribs in chest radiographs using iterated contextual pixel classification

The task of segmenting the posterior ribs within the lung fields of standard posteroanterior chest radiographs is considered. To this end, an iterative, pixel-based, supervised, statistical classification method is used, which is called iterated contextual pixel classification (ICPC). Starting from an initial rib segmentation obtained from pixel classification, ICPC updates it by reclassifying every pixel, based on the original features and, additionally, class label information of pixels in the neighborhood of the pixel to be reclassified. The method is evaluated on 30 radiographs taken from the JSRT (Japanese Society of Radiological Technology) database. All posterior ribs within the lung fields in these images have been traced manually by two observers. The first observer's segmentations are set as the gold standard; ICPC is trained using these segmentations. In a sixfold cross-validation experiment, ICPC achieves a classification accuracy of 0.86 +/- 0.06, as compared to 0.94 +/- 0.02 for the second human observer.

The tenth rib line as a new landmark of the lumbar vertebral level during spinal block

The purpose of this study was to assess whether the tenth rib line (an imaginary line that joins the lowest points of the rib cage on the flanks) could be used as a marker of the lumbar vertebral level. Simple X-rays (n = 100) were taken with radiopaque markers attached on the lowest points of the rib cage and the uppermost points of the iliac crests on both flanks. The spinous process or interspinous space that the tenth rib or Tuffier's lines crossed was identified and recorded, respectively, in the neutral and fully flexed positions. With lumbar flexion, the tenth rib line (median (25th to 75th percentiles)) moved upward (L(2) (L(1-2) - L(2)) vs. L(1-2) (L(1-2) - L(1-2)); p < 0.01), but Tuffier's line moved downward (L(4-5) (L(4) - L(4-5)) vs. L(4-5) (L(4) - L(5)); p < 0.01). Because the ease of palpating the tenth rib line and its distribution patterns are comparable to those of the Tuffier's line, the tenth rib line may be useful as a new landmark of the lumbar vertebral level as well as a safeguard to prevent spinal puncture from being mistakenly performed at a dangerously high level.

How far is the sternal angle from the mid-right atrium?

BACKGROUND

The central venous pressure (CVP) is commonly estimated at the bedside by measuring the height of the jugular venous pressure (JVP) relative to the sternal angle. Determining the CVP from this measure requires that the distance from the sternal angle to the level of the mid-right atrium be known. Classical clinical teaching quotes this distance as 5 cm, invariable between patients, and invariable with changes in the elevation of the patient's head. The validity of these JVP characteristics has been questioned.

OBJECTIVES

To measure the distance from the sternal angle to the level of the mid-right atrium (SA-RA) and determine if the SA-RA distance varies with patient position.

METHODS

Cross-sectional study conducted at a single-center teaching hospital on ambulatory patients undergoing computed tomography of the chest.

RESULTS

One hundred sixty patients were included. The median SA-RA distance with the patient lying supine was 5.4 cm (interquartile range, 4.7 to 6.1). Using geometric calculations to estimate the SA-RA distance when the patient's torso was elevated above the supine position, the median SA-RA distance was calculated to be 8 cm, 9.7 cm, and 9.8 cm at 30, 45, and 60 degrees elevation respectively. The SA-RA distance varied extensively between patients and was independently associated with smoking, age, and antero-posterior chest diameter.

CONCLUSIONS

The distance from the sternal angle to the level of the mid-right atrium varies considerably between individuals and with patient position. When using the JVP to calculate the CVP, physicians need to consider specific patient factors and the patient's position.