Diffusion-weighted-MRI versus PET-CT in assessment of chest wall lesions

Background Chest wall lesions comprise benign and malignant etiologies. Numerous classification systems have been proposed based on etiology, origin site, tissue composition and whether the lesion is benign or malignant. Despite that conventional radiological studies are able to provide detailed information about the tumor morphology such as size, location, and extent tissue characteristics, yet, they cannot reliably differentiate benign from malignant neoplasms. This study aimed to detect the diagnostic value of diffusion weighted MRI and PET/CT in evaluating chest wall lesions, and in differentiating benign from malignant lesions. Results The chest wall lesions were divided into either benign or malignant; 34 cases (47.9%) were diagnosed as benign, while 37 cases (52.1%) were diagnosed as malignant. The mean ADC value of malignant lesions (0.8 ± 0.3 × 10–3 mm2/s) was significantly lower than that of benign lesions (1.3 ± 0.6 × 10–3 mm2/s). This yielded statistically significant results with cut off value of 1.25 × 10–3 mm2/s for confident diagnosis and differentiation of benign from malignant lesions, with sensitivity of 91.9%, specificity of 70.6%, positive predictive value of 77.27%, negative predictive value of 88.89% and accuracy of 81.7%. The mean SUV of malignant lesions (14.2 ± 6.1) was signifi‑ cantly higher than that of benign lesions (1.5 ± 1.3). This yielded statistically significant results with cut off value of 2.45 for confident diagnosis and differentiation of benign from malignant lesions, with sensitivity of 100%, specificity of 82.4%, positive predictive value of 86.05%, negative predictive value of 100%, and accuracy of 91.5%. Conclusions Both DWI‑MRI and PET/CT can reliably differentiate benign from malignant lesions, yet, PET/CT showed higher sensitivity, specificity and accuracy.


Background
The chest wall represents the structures encircling the lungs.These structures include various tissues, Including cartilage, bone, muscle, fascia, vasculature, lymphatic vessels, fat, and skin [1].
Chest wall lesions comprise benign and malignant etiologies.Numerous classification systems have been proposed based on etiology, origin site, tissue composition and whether the lesion is benign or malignant [1][2][3].
About 50% to 80% of chest wall tumors are malignant and more than half of them are metastatic in origin [7].
Tumors that originate from the chest wall are uncommon, and unfamiliarity with them cause diagnostic challenges for radiologists.Additionally, the imaging findings of most of these neoplasms are non-specific, especially those that are locally aggressive [3].
Despite that conventional radiological studies are able to provide detailed information about the tumor morphology such as size, location, and extent tissue characteristics, yet, they cannot reliably differentiate benign from malignant neoplasms [6].
Diffusion Weighted Imaging (DWI) is a functional Magnetic Resonance Imaging (MRI) technique that has the advantage of being broadly available and non-invasive with short time of acquisition.It has the capability of studying tissue characteristics on the basis of diffusivity of water molecules within them.By calculating the apparent diffusion coefficient (ADC) value, quantitative assessment of a neoplasm is also possible, which is inversely correlated to tissue cellularity [8].
Similarly, 18F Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG PET/CT) is a non-invasive technique that provides tomographic images as well as quantitative assessment of the metabolic activity of target tissues.FDG accumulates in tissue proportional to the amount of glucose consumption, while, CT allows the visualization of morphological and anatomical structures with high spatial resolution [9,10].
The study aimed to detect the diagnostic value of diffusion weighted MRI and PET/CT in evaluating chest wall lesions, and in differentiating benign from malignant lesions.

Methods
This prospective cross-sectional study was approved by our local institutional review board.Informed written consent was obtained from all included participants or their authorized representatives.
The study was conducted over a period of 20 months (from January 2021 to September 2022).Patients were referred from the pulmonology and oncology departments and outpatient clinics to the radiology department to perform MRI of the chest with DWI, and PET/ CT for assessment of chest wall lesions.
The most common symptoms reported at presentation were dyspnea, chest pain, deformity and weight loss (Table 1).
All patients performed MRI of the chest with DWI and PET/CT.

Exclusion criteria (a) Exclusion criteria for MRI
General exclusion criteria for MRI; for example: claustrophobic patients, patients having a contraindication to MRI (cochlear implants, cerebral aneurysm clips, pacemaker, ocular metallic foreign body, etc.).(i) Qualitative assessment Chest wall diseases were analyzed for the number of lesions, site, size, shape, morphological features, tissue characterization, extent and their relation to adjacent structures.We considered lymph nodes enlarged if they were > 10 mm in short-axis diameter.We reviewed each lesion signal intensity in the different pulse sequences with comparison of their signal relative to the muscles signal in the same pulse sequence.We also qualitatively assessed the lesions on DWI and ADC maps by inspecting their signal intensity on the highb-value (b = 1000 mm 2 /s) DWI and correlating it to that on the corresponding ADC map.Associated MR imaging findings were also recorded.(ii) Quantitative assessment Measuring ADC values was done by placing the region of interest (ROI) within the center of the lesion on the ADC maps with an effort to avoid interference from the surrounding lung tissue and vascular structure.
In case of soft tissue lesions, the ROI was placed within the most restricted areas (excluding apparent cystic/necrotic areas).
To avoid the possible magnetic susceptibility artifacts, ADC values were computed far from lung-fluid interfaces and diaphragmatic areas.

Positron emission tomography/computed tomography technique (a) Patient preparation
We asked the patients to fast for six hours before the scan, and to do a renal function test.We also asked the patients to remove any metallic items, and they were given a gown to wear.We inserted an I.V. cannula in the patient's arm for 18 F FDG administration.We instructed the patients to avoid any strenuous activity after the 18 F FDG injection to avoid physiologic FDG muscle uptake, and to void before scanning.
For known diabetic patients, we measured the serum glucose before injection of 18 F FDG, and fasting levels were 70-180 ng/dl.Diabetic patients were instructed not to have their regular insulin administered within four hours of FDG administration.
In order to decrease brown fat, a warm environment was provided to the patients before injection of 18 F FDG and the patients were instructed to follow a high-fat, low-carbohydrate, protein-permitted diet prior to the examination.

(b) Dosage administration
Before the examination by 45-90 min, we injected 10-20mCi (370 MBq; approximate dose to patient, 3-5MBq/Kg) 18 F FDG.This duration is the uptake phase in which the FDG is bio-distributed and transported into the patient's cells.We asked the patients to rest in a quiet room, and to minimize their movements, including talking in order to decrease the FDG physiologic uptake into skeletal muscle, which can be confusion during scan the interpretation.

(c) Patient position
We positioned the patients in a comfortable head fixation with their arms up.

(d) Image acquisition
A low dose non enhanced CT scan was performed first, followed by a whole-body PET study, then a whole-body contrast-enhanced CT using Siemens Biography 265 Multi-slice PET/CT scanner.The duration of the study was approximately 20-30 min.The scanning started from the skull base and extended caudally to the level of the upper thighs (brain, neck, chest, abdomen and pelvis).Scanning parameters were a collimator width of 5.0 mm, pitch of 1.5, gantry rotation time of 0.8 s, and field of view of 50 cm.Reconstruction of the helical data was done at 1 mm intervals.

(i) CT technique
The contrast-enhanced CT was performed following injection of 1-2 ml/Kg of a low-osmolarity iodinated contrast medium at a rate of 4 ml/sec by using a power injector.(ii) PET technique PET was performed following the CT study without moving the patient.About six to seven bed positions are programed in the threedimensional acquisition mode to scan the whole patient with 3-5-min acquisition at each bed position.(iii) PET/CT fusion Axial PET and CT images were taken then reconstructed into coronal and sagittal images to enhance image analysis.Corresponding "fusion" images were then generated by combining the data of the PET and CT images.
The duration of an integrated PET/CT scan was about 25 min.
(e) Image analysis The CT scans were interpreted by experienced radiologists and the PET/CT scans were separately interpreted by a consensus of two experienced nuclear medicine radiologists.A ROI of 5 to 10 mm was placed manually over the area of maximal activity on slices within the tumor and the standardized uptake value (SUV) was calculated.Pathological 18 F FDG uptake was described as accumulation of radiotracer outside the normal anatomic structures of higher intensity than background activity.
The CT and fused PET/CT images were assessed for the presence chest wall lesions, their number, site, size, shape, and relation to the surroundings.Chest wall infiltration was defined as soft tissue infiltration by the tumor and/or lytic destruction of the ribs or vertebrae.
Lymph nodes showing increased FDG uptake were characterized as positive for metastasis even if they were smaller than 1 cm in their short-axis diameter.However, lymph nodes with little or no FDG uptake were considered benign, even if they were larger than 1 cm in their short-axis diameter.

Histopathological diagnosis
The
The benign neoplastic lesions were further categorized according to tissue of origin as shown in (Table 2).
The benign non-neoplastic lesions were further categorized according to etiology (Table 3).
The primary malignant lesions were further categorized according to tissue of origin as shown in (Table 4).
Secondary malignant lesions were further categorized according to their site (Table 5).
The mean ADC value of malignant lesions (0.8 ± 0.3 × 10 -3 mm 2 /s) was significantly lower than that of benign lesions (1.3 ± 0.6 × 10 -3 mm 2 /s).This yielded statistically significant results with cut off value of 1.25 × 10 -3 mm 2 /s for confident diagnosis and differentiation of benign from malignant lesions, with sensitivity of 91.9%, specificity of 70.6%, positive predictive value of 77.27%, negative predictive value of 88.89% and accuracy of 81.7% The mean SUV of malignant lesions (14.2 ± 6.1) was significantly higher than that of benign lesions (1.5 ± 1.3).This yielded statistically significant results with cut off value of 2.45 for confident diagnosis and differentiation of benign from malignant lesions, with sensitivity of 100%, specificity of 82.4%, positive predictive value of 86.05%, negative predictive value of 100%, and accuracy of 91.5%.

Discussion
Chest wall tumors account for less than 5% of all thoracic neoplasms and represent a heterogeneous group of lesions that can be difficult to diagnose [11] with the new developments in MR systems, DW-MRI of the chest became an emerging functional MRI technique that makes the analysis of tissue characteristics possible on the basis of water molecules diffusivity within tissues [8,12].In addition, FDG PET/CT has been found to be more sensitive than CT or MRI in assessing treatment response and prognosis by simultaneously depicting primary lesions and distant metastases on a single scan [13].This cross section study involved 71 patients; 30 males and 41 females, with age range of 2-71 years (mean age of 44 years).
In this study, the mean ADC value of malignant lesions (0.8 ± 0.3 × 10 -3 mm 2 /s) was significantly lower than that of benign lesions (1.3 ± 0.6 × 10 -3 mm 2 /s) with cut off value of 1.25 × 10 -3 mm 2 /s for confident diagnosis and differentiation of benign from malignant lesions, with sensitivity of 91.9%, specificity of 70.6%, and accuracy of 81.7% Our results are similar to Lim et al. [14], who studied the role of DW-MRI in differentiating between benign and malignant tumors in 65 cases, and concluded that the mean ADC values for benign and malignant soft tissue tumors were 1.689 and 0.965 × 10 -3 mm 2 /s respectively with statistically significant difference between them (P value < 0.001), showing a cut off value of 1.2 × 10 -3 mm 2 /s that yielded a sensitivity of 92%, specificity of 87%, and accuracy of 90%.
Our results are however, slightly different from Lee et al. [15], who concluded that the mean ADC values for benign and malignant soft tissue tumors were 1.47 and 1.17 × 10 -3 mm 2 /s respectively, with a cut off value of 1.31 × 10 -3 mm 2 /s that yielded a sensitivity of 74%, specificity of 73%, and accuracy of 74%.
We encountered in our study 4 patients with benign lesions showing morphological, anatomical and signal characteristics of lipomas, yet, demonstrating very low ADC value (mean value of 0.43 × 10 -3 mm 2 /s), similar to those of malignant soft-tissue masses (Fig. 3).These results are consistent with those of Hassanien et al. [16], Dietrich et al. [17] and Einarsdóttir et al. [17], who stated that there is some overlap between benign and malignant soft tissue tumors such as in lipomas, giving low ADC values similar to malignant lesions (false positive).According to Hassanien et al. [16], the 5 lipomas included in their study had a mean ADC value of 0.31 × 10 -3 mm 2 /s [16][17][18].
There were 18 elastofibroma dorsi cases included in our study showing facilitated diffusion; their mean ADC value was 1.39 × 10 -3 mm 2 /s (Fig. 4).On surfing the literature, studies performed to diagnose the role of DWI on elastofibroma cases were quite limited.Tsubakimoto et al. [19], performed a study on 41 elastofibroma cases, and concluded that none of the lesions had true diffusion restriction; their mean ADC value was 1.36 × 10 -3 mm 2 /s, which is similar to our results.Our results demonstrated that vascular malformations (1 case) and lymphatic malformations (2 cases) had ADC values higher than other benign tumors with mean ADC value of 2.4 × 10 -3 mm 2 /s.These results are consistent with those of Hassanein et al. [16], who studied 3 hemangioma cases included in their research, and found that the mean ADC value of these lesions was 2.45 × 10 -3 mm 2 /s.
Concerning the inflammatory chest wall lesions included in our study, the mean ADC value of abscesses was 0.75 × 10 -3 mm 2 /s.This is coherent to Kumar et al. [23] and Douis et al. [24]; the latter mentioned that false positive cases included abscesses, as they may result in restricted diffusion with low ADC values, hence, overlapping with the ADC values for malignant soft tissue lesions [23,24] (Fig. 5).However, the typical clinical presentation of inflammatory signs such are skin redness and A single case of post-operative fluid collection (mastectomy surgical bed seroma) was included in our study with mean ADC value 2.4 × 10 -3 mm 2 /s.Ultrasound guided aspiration of this fluid collection was performed, and yielded benign nature.Our results were compatible with Aktas et al. [25], who performed a study on 42 patients to detect the role of DWI and ADC in differentiating post-operative cancer recurrence from post-operative sequalae as hematoma or seroma, and concluded that the mean ADC value of post-operative benign collections was 2.72 × 10 -3 mm 2 /s, which was significantly higher than the ADC values of tumor recurrence (1.44 × 10 -3 mm 2 /s).
Mean ADC values obtained in Ewing sarcoma cases included in our study population yielded an average of 0.65 × 10 -3 mm 2 /s, which is comparable to that reported by Saleh et al. [26], whose study included 51 pathologically proven Ewing sarcoma cases, with a mean ADC value of 0.71 ± 0.16 × 10 -3 mm 2 /s.
Note that one of the Ewing sarcoma cases in our study showed mean ADC value of 1.4 × 10 -3 mm 2 /s, which is considered higher than the average ADC for this lesion 2).Note FDG uptake in incidentally discovered right lower lung lobe nodule that was not seen in the chest MRI (Fig. 6).This may be attributed to treatment as the patient received neoadjuvant chemotherapy, therefore internal areas of breakdown were noted within the tumor resulting in high ADC values.Again, these results were comparable to Saleh et al. [26], who compared the ADC values of Ewing sarcoma pre and post therapy, and noted that there is an increase in the ADC value post treatment (1.6 ± 0.39 × 10 -3 mm 2 /s).
The mean ADC value of the 4 cases of osteosarcoma included in our study was 0.75 × 10 -3 mm 2 /s.Likewise, Yakushiji et al. [27] studied 17 cases of osteosarcoma and found that their mean ADC value was 0.84 ± 0.15 × 10 -3 mm 2 /s.
The mean ADC value of the 3 malignant fibrous histiocytoma cases included in our study was 0.93 × 10 -3 mm 2 /s.Similarly, Hassanien et al. [16] study included 4 cases of the same lesion with a mean ADC value of 0.81 ± 0.15 × 10 -3 mm 2 /s.
A single case of MPNST was included in our study with an ADC value range of 0.2-0.4× 10 -3 mm 2 /s.Correspondingly, Ahlawat et al. [28] performed a study on 55 cases of peripheral nerve sheath tumor to detect the sensitivity of ADC in differentiating benign from malignant peripheral nerve sheath tumors and concluded that malignant peripheral nerve sheath tumors showed mean ADC value of 0.6 ± 0.2 × 10 -3 mm 2 /s as compared to benign nerve sheath tumors, which showed mean ADC value of 1.6 ± 0.4 × 10 -3 mm 2 /s.The mean ADC value the 2 multiple myeloma cases included in our study was 1.05 × 10 -3 mm 2 /s.This is higher than the results of Patrenain et al. [29], who performed a study on 27 multiple myeloma cases, and concluded that their mean ADC values was 0.65 × 10 -3 mm 2 /s.
The mean ADC value of the 3 lymphoma cases included in our study was 0.97 × 10 -3 mm 2 /s.This is slightly higher than the results yielded by Surov et al. [30], who performed a study on 14 cases pathologically diagnosed as lymphoma, with mean ADC value of 0.76 × 10 -3 mm 2 /s.
Most of the secondary malignant lesions encountered in our study were morphologically heterogeneous.This is attributed to several factors, such as the aggressiveness and cellularity of the primary tumor, the areas of hemorrhage and necrosis usually seen in these lesions, and whether the patient started receiving radiotherapy/chemotherapy sessions or not, which has led to a wide range of ADC values.We did our measurements from the solid most homogeneous parts of the tumor, and tried our best not to include cystic or necrotic areas.The minimum ADC value was detected in ovarian metastasis (0.4 × 10 -3 mm 2 /s), while the highest ADC value was detected in direct invasion from breast cancer (1.2 × 10 -3 mm 2 /s).The overall mean ADC value of secondary malignant chest wall lesions was 0.82 × 10 -3 mm 2 /s.Our results are more or less similar to Ahlawat et al. [31], whose study included 8 cases of secondary lesions from different sites, with a minimum ADC value of 0.6, a maximum ADC value of 1.5, and mean ADC value of 1.03 × 10 -3 mm 2 /s.Note that the average ADC value detected was still lower than that of most benign lesions, thus, allowing differentiation of benign and malignant lesions by ADC.
The mean SUV of the 18 elastofibroma cases included in our study was 1.04 (Fig. 4).This is more or less agrees with Onishi et al., 2011, who performed a study on 34 patients to study the SUV uptake in a total of 75 elastofibroma lesions, with mean SUV of 2.0 ± 0.63 [32].
All inflammatory lesions included in our study showed high FDG uptake.This was due to increased glucose utilization by the inflammatory cells, leading to increased FDG uptake in the affected region.Macrophages play a central role in the host response to injury and infection, and their energy is predominantly supplied by means of intracellular glucose metabolism, hence, causing FDG uptake and consequently false positive results.
The single case of post-operative fluid collection (mastectomy surgical bed seroma) included in our study which was pathologically proven as benign showed no FDG uptake.
Our study included 1 case of fibrous dysplasia, which showed increased FDG uptake (SUV = 6.5, which is above the cut off value) (Fig. 7).These results are conforming to Aoki et al. [33], whose results also showed increased FDG uptake in some of the fibrous dysplasia cases included in their study, exceeding the cut off value, leading to false positive result.
In this study, the mean SUV of malignant lesions (14.2 ± 6.1) was significantly higher than that of benign lesions (1.5 ± 1.3), with cut off value of 2.45, with sensitivity of 100%, specificity of 82.4%, and accuracy of 91.5%.
Our results are close to Feldman et al. [34], who performed a study on 45 patients to detect the role of FDG PET/CT in detection and analysis of musculoskeletal lesions, and concluded a sensitivity of 91.7%, specificity of 100% and accuracy of 91.7% in differentiating benign from malignant lesions.Our results are also more or less compatible with Etchebehere et al. [35] 2016, who performed a meta-analysis including 14 articles composed of 755 patients with 757 soft tissue lesions, to study the role of PET/CT in diagnosis and differentiation of benign and malignant soft tissue lesions.They concluded a sensitivity of 96%, a specificity of 77% and accuracy of 88%.
Our results are however, different from Shin et al. [36], who performed a study to detect the role of PET/CT in differentiating benign from malignant lesions.They concluded a sensitivity of 80%, specificity of 65.2% and accuracy of 73%.Our results are also different from Ioannidis et al. [37], who performed a meta-analysis including 15 studies with 441 soft-tissue lesions (227 malignant, 214 benign), to study the role of FDG PET/CT in diagnosis, differentiation and grading of soft tissue sarcomas, and Our study showed that ADC and SUV values had an inverse correlation with high SUV and low ADC values observed in malignant tumors (Fig. 8).Our results are compatible with the study conducted by Lee et al. [38], in which 57 patients performed both DW MRI and PET/CT; their results also revealed inverse correlation between the ADC value and SUV measurement, and outlined the usefulness of using ADC and SUV as an adjunct to morphological imaging to enhance the diagnosis, and as a tool for determining response to therapy.
This study has some limitations as it included only a limited number of lesions.Included lesions were histologically variable and each has variable tissue components.Hence, the need for more studies with larger populations, and larger scale randomized controlled trials are needed to validate our results.

Conclusions
In conclusion, both DWI-MRI and PET/CT can reliably differentiate benign from malignant lesions, yet, PET/CT showed higher sensitivity, specificity and accuracy.So, we recommend DWI-MRI of the chest wall as a non-invasive and radiation-free imaging modality for diagnosis of primary chest wall lesions, to assess their nature and composition, hence, aiding in differentiation between benignity and malignancy.In case of malignancy, this should be followed by PET/CT, which will give an idea about the lesion nature, as well as detect other lesions elsewhere in the body within a single quick whole-body examination for better management decision.However, PET/CT is the optimal imaging modality for staging, restaging, and assessment of therapeutic response.

Fig. 2 A
Fig. 2 A scheme showing overview of the malignant chest wall lesions

Fig. 3
Fig. 3 38-year-old male patient complaining of right anterior chest wall swelling.a Axial T1, b axial T2, c axial T2 fat suppression, and d post contrast axial T1 fat suppression showing right pectoralis major intra muscular well-defined lesion eliciting signal intensity identical to fat in T1 and T2 WIs with drop of signal in fat suppressed image and no post contrast enhancement.e DWI and f ADC map showing low DWI signal intensity with corresponding low signal in ADC map.ADC value = 0.2 × 10 -3 mm 2 /s

Fig. 4
Fig. 4 67-year-old female patient with past history of uterine cancer complaining of bilateral infra-scapular fullness.MRI chest and PET/CT were performed as part of her investigation profile with incidental discovery of bilateral elastofibroma dorsi; larger on the left side.a Axial T1, b axial T2, and c post contrast axial T1 fat suppression showing bilateral sub-scapular soft tissue lesions deep to the serratus anterior and latissimus dorsi muscles exhibiting lamellar feathery pattern, and signal intensity similar to the adjacent muscles on T1 and T2 WIs with patchy enhancement.Mild right and minimal left pleural effusions were also noted.d DWI and e ADC map showing low DWI signal intensity with corresponding low signal in ADC map.ADC value = 1.1 × 10 -3 mm 2 /s.f Axial CT, g axial fused PET-CT, and h axial PET image showing FDG activity within bilateral elastofibroma (SUV = 1.2).Note FDG uptake in incidentally discovered right lower lung lobe nodule that was not seen in the chest MRI

Fig. 5
Fig. 5 37-year-old diabetic male patient complaining of anterior chest wall swelling with overlying skin redness.a Axial T1, b axial T2, and c post contrast axial T1 fat suppression showing pre-sternal well-defined subcutaneous lesion eliciting low T1 and high T2 WIs signal intensity with marginal post contrast enhancement.d DWI and e ADC map showing diffusion restriction in the form of high diffusion signal and low ADC.ADC value = 0.8 × 10-3 mm 2 /s.f Sagittal T2, and g Sagittal post contrast T1 fat suppression showing involvement of the underlying bone with no intra-thoracic extension

Fig. 6
Fig. 6 19-year-old male with pathologically proven right chest wall Ewing sarcoma following neoadjuvant chemotherapy.a Axial T1, b axial T2, and e post axial T1 fat suppression, showing right posterior chest wall pleural-based ill-defined mass lesion eliciting heterogeneous mixed low/ intermediate T1 and high/intermediate T2 signal intensities with faint heterogeneous post contrast enhancement.c DWI and d ADC map showing low DWI signal intensity with corresponding high signal in ADC map.ADC value = 1.4 × 10 -3 mm 2 /s

Fig. 7
Fig. 7 40-year-old male patient complaining of right chest wall pain and hard swelling.a Axial CT, b axial fused PET-CT, and c axial PET image showing diffuse medullary expansion of several right ribs along the course of the rib with intact cortex and intense FDG uptake corresponding to the affected ribs (SUV = 8).Note the affection of a left rib too.CT-guided biopsy revealed fibrous dysplasia

Fig. 8
Fig. 8 69-year-old male patient with history of treated differentiated thyroid cancer coming for follow up.MRI chest and PET/CT were performed as part of his investigation profile.a Axial T1, b axial T2, and c post contrast axial T1 fat suppression showing anterior mediastinum/retro-sternal lobulated soft tissue lesion reaching the anterior aspect of the ascending aorta and extending to encircle the right sterno-clavicular joint with periarticular soft tissue sheets.It elicits isointense T1 and heterogeneous iso to low T2 signal intensity with heterogeneous post contrast enhancement.d DWI and e ADC map showing diffusion restriction in the form of high diffusion signal and low ADC.ADC value = 0.56 × 10 -3 mm 2 /s.Note metallic susceptibility artifacts from sternotomy wires suture.f Axial CT, g axial fused PET-CT, and h axial PET image showing retrosternal FDG uptake with erosion of the adjacent sternum and right sterno-clavicular joint (SUV = 13.2).CT-guided biopsy revealed nodal metastasis

Symptoms Number of patients Percentage (%)
The presenting symptoms numbers and percentages in our study Contrast-enhanced MRI was recommended in 51 patients (72.9%).A venous catheter was placed in a peripheral vein (ante-cubital vein in most cases) attached to automatic injector through a long connecting tube to allow easy injection without changing the patient position.The injected dose was 0.1 mmol gadolinium-DTPA/kg.Patients were instructed to fast for six hours, and to perform a renal function test prior to the scan.
The mode of acquisition of the biopsy was determined according to accessibility of the lesions.The rest of cases (35.2%) were diagnosed based on clinical data and typical radiological features.

Table 2
Classification of benign neoplastic lesions according to tissue of origin

Table 3
Classification of benign non-neoplastic lesions according to etiology

Table 4
Classification of primary malignant lesions according to tissue of origin PNET = Primitive neuroectodermal tumors, UPS = Undifferentiated pleomorphic sarcoma, MPNST = Malignant peripheral nerve sheath tumor

Table 5
Classification of secondary malignant lesions according to their site