Bone tumors
Soft tissue tumors
Metastases
Neurofibromatosis
Myeloma
Schwannomatosis
Lymphoma
Myxomas (Mazabraud syndrome)
Enchondromatosis (including variants)
Angiomatosis
Multiple hereditary exostoses
Lipomas (including hereditary lipomatosis)
Langerhans cell histiocytosis
Desmoid tumors
Multifocal osteomyelitis
Hyperparathyroidism with brown tumors
Initial Imaging Evaluation
Initial assessment of a suspected musculoskeletal bone or soft-tissue mass begins almost invariably with radiographic evaluation, a fundamental concept that is emphasized by the American College of Radiology Appropriateness Committee [1, 2]. The radiograph accurately predicts the biologic activity of a bone lesion, which is reflected in the appearance of the lesion’s margin and the type and extent of accompanying periosteal reaction. In addition, the pattern of associated matrix mineralization (osteoid or chondroid) may be a key to the underlying histology [3–5]. Although other imaging modalities (MR and CT) are superior to radiographs in staging, the radiograph remains the single best modality for establishing a diagnosis, for formulating a differential, and for accurately assessing the biologic activity.
Radiographs are typically considered unrewarding in the assessment of soft tissue masses; however, a recent study 281 patients showed calcification in 27%, bone involvement in 22% and fat in 11% of cases [6]. Such features may be essential in establishing an imaging diagnosis or differential. Radiographs may also be diagnostic of a palpable lesion caused by an underlying skeletal deformity (such as exuberant callus related to prior trauma) or exostosis, which may masquerade as a soft tissue mass. The soft tissue calcifications and/or ossification identified on radiographs can be suggestive, and at times highly characteristic, of a specific diagnosis, such as phleboliths within a hemangioma, the multiple intraarticular osteocartilaginous masses of synovial chondromatosis, or the peripherally more mature ossification of myositis ossificans.
Advanced Imaging Techniques
MRI has become the technique of choice for detecting and characterizing musculoskeletal masses. Its improved soft tissue contrast and multiple-image-plane capabilities have provided significant advantages for lesion conspicuity, characterization, and local staging.
MR Imaging
The protocoling of the MR imaging examination has become far more complex. The old “one size fits all” approach should be avoided as it often leads to less than optimal results. Appropriate protocoling should be based on the initial review of clinical history, physical evaluation, and initial (pre-MR) imaging, in conjunction with the patient age and lesion location, which allows a suspected diagnosis or at least a reasonable differential diagnosis. Equally important, an initial review will allow selection of the appropriate field of view (FOV), imaging planes, MR imaging sequences, and necessity for contrast material. These parameters are truly fundamental in achieving the most diagnostic imaging and deserve special emphasis.
Field of View
One of the most important parameters in tumor imaging is FOV. Although it is applicable to all cross-sectional imaging, it has received relatively little attention until recently [7]. Referring providers often order an MR study by anatomic area. MR imaging for a small mass around the hip may be ordered as a pelvis study or a lesion in the intertrochanteric region as a femur; examinations which are typically performed with a large (36–40-cm) FOV. Imaging the hip, for example, would typically be evaluated with a 20-cm FOV, allowing increased spatial resolution by as much as a factor of four, allowing markedly improved anatomic delineation of adjacent vessels, nerves, fascial planes, and other anatomic structures.
As a general guide, FOV is dictated by the size and location of the mass being studied and must be large enough to evaluate the entire lesion and allow appropriate local staging. Cases which require evaluation of an entire long bone, such as with suspected osteosarcoma, small FOV images can be supplement with limited large FOV images. Similarly, for example, when no discrete lesion is identified at initial imaging and a superficial unencapsulated lipoma is suspected, limited large FOV imaging of both sides is useful for comparison to allow confident identification of asymmetry and a definitive diagnosis.
Imaging Planes
MR imaging is invariably performed using a multiplanar technique. In the vast majority of locations neurovascular structures and muscles can be optimally identified and followed in the axial plane. Consequently, we generally use this as the primary imaging plane. This is augmented with long-axis images giving the best assessment of the entire lesion in “profile,” assisting in its characterization as well as its relationship to the important surrounding anatomic structures; information required for diagnosis and surgical planning. Lesions such as those of the chest wall may be problematic due to its curved nature, and images in the standard coronal or sagittal plane may be less useful than imaging perpendicular to the chest wall. To avoid confusion during image acquisition, unusual oblique planes must be clearly defined to the imaging technologist.
MR Imaging Sequences
Most musculoskeletal masses are well evaluated with T1-weighted and fat-suppressed fluid-sensitive images. We generally prefer fat-suppressed proton-density–weighted FSE images to fat-suppressed T2-weighted FSE images due to the increased signal-to-noise ratio of the former. It is important to remember that the main purpose of fat suppression in fluid-sensitive imaging is enhancement of lesion conspicuity. In reality, conspicuity is typically not an issue in tumor imaging, and non-fat-suppressed T2-weighted images may be a useful adjunct for comparison of signal intensity to that of internal controls of muscle (low), fat (intermediate), and fluid (high). This is often helpful in better assessing the nature of the mass; for example, myxoid lesions generally follow fluid signal intensity, whereas collagenous/fibrous lesions generally have low to intermediate signal intensity. As FSE imaging tends to blur the signal intensity difference between fat and water, strongly T2-weighted parameters are required in such cases for non-fat-suppressed T2-weighted sequences (TR > 4000/TE100–110).
Gradient-echo (GRE) imaging has less fluid conspicuity but is particularly useful in identifying evidence of prior intralesional hemorrhage, revealing hemosiderin deposition as a result of its greater magnetic susceptibility [8]. In addition to hemosiderin, gradient-echo imaging is useful in identifying increased susceptibility artifacts from metal and air [8].
We find short τ inversion-recovery (STIR) images especially useful in areas where fat suppression is heterogeneous. Heterogeneous fat suppression can be particularly problematic in evaluation of off-center extremity musculoskeletal masses, as well as in areas where air pockets form adjacent to curves in the extremity or torso, such as adjacent to the perineum. STIR imaging is more susceptible to degradation from patient or respiratory motion and has lower signal-to-noise ratio than spin-echo imaging; however, it can increase lesion conspicuity and is a useful adjunct [9–11].
Contrast Material
The use of contrast material for evaluation of musculoskeletal tumors is well established, and its efficacy in improving diagnostic accuracy is well documented [10, 12, 13]. Contrast material is also useful in assessment of the vascular anatomy as well as lesion vascularity [12, 14]. We find contrast material useful not only in giving greater confidence in diagnosis, but also in identifying the most suitable location of the vascularized solid elements that will provide diagnostic tissue from subsequent biopsy if required.
Contrast-enhanced imaging is especially useful in assessment of hematomas and in distinguishing the hemorrhagic component of a neoplasm from the solid elements that may not be easily distinguished on conventional imaging. Subtraction imaging is a relatively recent innovation that has received little attention in the literature [15–17]; however, we find it invaluable in such cases, since this technique eliminates the possibility of misinterpreting the T1 shortening associated with hemorrhagic change as vascular enhancement.
Patient Motion
The above MR imaging techniques are applicable for the vast majority of cases; however, the relatively long imaging acquisition times of these standard sequences limit their use in anatomic areas that are susceptible to respiratory motion [10]. Recent advances in software and imaging applications now allow a variety of techniques that can capture a complete set of images in a single breath hold [18]; techniques that not only allow rapid image acquisition but are extremely fluid sensitive. Many musculoskeletal radiologists are not familiar with these techniques, although they are routinely used by our abdominal and thoracic imaging colleagues.
We generally prefer the gradient version of single-shot imaging (true FISP [true fast imaging with steady-state precession], FIESTA [fast imaging employing steady-state acquisition], balanced FFE [fast field echo]), which provides high-signal-intensity flowing blood and increased signal-to-noise ratio. When used without fat-suppression, its mixed T1/T2 weighting can be confusing due to the increased signal intensity from fat, water, and flowing blood; however, its quick acquisition time makes it a valuable adjunct.
Rapid fluid-sensitive images can also be acquired using a spin-echo single-shot technique (HASTE [half-Fourier acquisition single-shot turbo spin-echo], turbo spin-echo, single-shot FSE). These sequences are motion insensitive, ideal for breath-hold imaging, and exquisitely fluid sensitive [19–21]. The most significant limitation of HASTE and similar sequences is the decreased signal-to-noise ratio, typically requiring thicker section thickness and larger-FOV imaging.
Quantitative MR Imaging Evaluation
In MR imaging, the term quantitative technique is usually applied to an imaging method in which there is a measureable outcome. Those that are most applicable to clinical practice are chemical shift and diffusion-weighted imaging, both of which allow qualitative (visual) assessment as well as a quantitative (measurable) result. Most recently, MR spectroscopy has been added to this list of available quantitative techniques; however, the inherent technical challenges have limited its widespread adoption.
Chemical Shift Imaging
Chemical shift imaging is a well-established technique based on the observation that at gradient-echo imaging, the signals from similar quantities of fat and water in a single voxel will reinforce each other when in phase and cancel each other when out of phase cancel each other out [22, 23]. This allows qualitative and quantitative (measured as percentage change in signal intensity on opposed-phase relative to in-phase images) assessment of the amount of microscopic fat in any lesion. Initially used in separating adrenal adenoma from other adrenal masses [24], this technique has proved itself useful in assessment of musculoskeletal osseous masses [25]. In a retrospective study of 50 osseous pelvic lesions Kohl et al. [25] found chemical shift imaging to be highly sensitive in identifying malignant disease and, despite its lower specificity, found its use could have eliminated the need for biopsy in more than 60% of patients with benign disease. Its application for soft tissue is more limited, but it is useful in distinguishing reactive marrow changes from tumor and microscopic fat in higher-grade liposarcoma [26].
Diffusion-weighted Imaging
Diffusion-weighted imaging has been well documented to be a useful technique in MR imaging of the brain and has more recently received greater acceptance in the musculoskeletal community [27, 28]. Diffusion-weighted imaging allows qualitative and quantitative assessment of the movement of water molecules through tissue. This technique can identify when that normal random motion is restricted, such as by an abnormally increased number and/or size of cells. This restricted motion of water is detected by application of diffusion-probing gradients of different strength (expressed as the b value) and can be visually assessed as signal intensity, with restricted diffusion showing increased signal intensity and measured as the apparent diffusion coefficient (ADC), with restricted diffusion demonstrating decreased signal on ADC maps [22].
Although qualitative assessment of diffusion-weighted imaging readily recognizes restricted diffusion and ADC values are reproducible [29], the quantitative distinction between benign and malignant based on ADC value is not yet well-defined, with variable results reported [30–33]. There is no universally applicable “one size fits all” ADC value. Razek et al. [34] recently suggested a value of 1.34 × 10−3 mm2/s as a threshold for distinguishing between benign and malignant masses. Using this value, they obtained a sensitivity, specificity, and accuracy of 94%, 88%, and 91%, respectively. A more recent study by Surov et al. [35] documented the variability of ADC value with tumor type, noting that if a value of 1.34 × 10−3 mm2/s were used in their assessment, 35.1% of their malignancies would have been incorrectly categorized. Such results underscore the influence of tumor morphology (cellularity and matrix composition) in diffusion-weighted imaging, as has been previously noted [32, 36]. Although the value of diffusion-weighted imaging in distinguishing benign from malignant lesions is as yet somewhat unsettled, it can identify restricted diffusion, which is also quite useful in identifying small pelvic lymph nodes [18].
Spectroscopy
Another quantitative method for assessment of soft-tissue tumors is proton MR spectroscopy. Unlike the previous quantitative techniques, there is no real qualitative component. In musculoskeletal spectroscopy, choline, a marker for cell membrane turnover, is measured and is recognized to be elevated in malignancies. Although spectroscopy can provide useful information, it is a technically demanding and time-consuming technique. Accordingly, it is not usually used in routine practice.
CT Imaging
While MR imaging is generally the preferred imaging method for diagnosis and staging of musculoskeletal masses; CT remains an important adjunct. It is readily available, fast, and much more patient-friendly than MR imaging.
Mineralization Characterization
As previously noted, CT is particularly useful in assessment and characterization of mineralization, especially in areas where the osseous anatomy is complex. It allows distinction of ossification from calcification and identification of characteristic patterns of mineralization. CT is also superior to radiography in detecting the zonal pattern of mineralization, essential to radiologic diagnosis of early myositis ossificans, a pattern that can be identified at CT, while radiographs remain nonspecific [37].
Dual-energy CT
This is a relatively new technology that has proved itself as a useful adjunct in evaluation of musculoskeletal masses. Using the differences in energy attenuation of soft tissue at 80 and 140 kVp, dual-energy CT allows distinction of urate crystal deposits from other soft-tissue calcifications [38]. Although it may seem that the diagnosis of chronic tophaceous gout should be obvious, such is not invariably the case. The diagnosis can be challenging, especially in those without a history of gout or hyperuricemia, and cases of gout referred to tertiary-care centers as a suspected soft-tissue sarcoma are not rare [39]. Dual-energy CT has also proved to be a useful method to evaluate metal implants by generating images acquired by monoenergetic high energy quanta, reducing metal artifact [40]. Utilization of this technique can significantly reduce metal artifact in the assessment of metal implants, improving the diagnostic value of imaging [40]. Most recently, it has shown application in the assessment of marrow edema [41, 42] and has been investigated in the distinction of marrow edema from intramedullary tumor invasion [43].
The rapid image acquisition capability of modern scanners also allows accurate assessment of lesion vascularity. In a comparison with MR angiography by Mori et al. [44], CT angiogaphy with three-dimensional reconstruction was found equivalent to MR angiography in its ability to demonstrate neurovascular involvement. CT was also superior to MR in its ability to identify cortical/ marrow involvement. Finally, CT may be the most appropriate modality for very large patients and patients with pacemakers when MRI is not feasible or contraindicated.
Diagnosis of Bone Tumors
As previously noted, the radiograph remains the most diagnostic imaging study. While more advanced imaging provides the information needed for accurate staging, diagnosis (or differential diagnosis) begins with the radiograph and is based on the morphology of the lesion, the lesion’s location and the patient’s age.
Morphology characterizes the presence and character of the lesion’s margin and periosteal reaction; features which are a function of the interaction between the lesion and the host, and are a key to biologic behavior. Morphology also includes an analysis of matrix mineralization and may be a key to the lesion histology.
The location of a lesion is a major consideration in establishing a diagnosis and structuring a differential diagnosis. There are two components to the location of an osseous lesion: the anatomic location (which bone) and the longitudinal location within the bone (epiphysis, metaphysis, metadiaphysis or diaphysis). The latter is critical in assessment of long bone lesions and is an essential principle of diagnosis pictorially presented in Fig. 1. Age is also an important consideration, with specific lesions tending to occur in specific age groups (Tables 2 and 3). For example, Langerhans cell histiocytosis localized to bone typically occurs in children and adolescents, while osseous lymphoma is most often encountered in mature adults, usually in the sixth and seventh decades. The final diagnosis, or differential, is based on the integration of the all of the above factors, taken in consideration of the prevalence of tumors within the population.
Fig. 1
Schematic diagram of the end of a long bone showing the typical sites for common primary bone tumors
Table 2
Age distribution of malignant osseous tumorsa
Tumor type | Overall incidence (%) | Incidence by decade (%) | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9+ | ||
Osteosarcoma | 29.2 | 4.6 | 46.0 | 17.2 | 8.8 | 7.6 | 6.5 | 6.7 | 2.4 | 0.3 |
Chondrosarcoma | 15.8 | 0.6 | 4.8 | 12.3 | 21.4 | 20.3 | 20.1 | 14.0 | 5.6 | 0.8 |
Myeloma | 14.4 | 0.1 | 1.2 | 5.2 | 15.7 | 29.2 | 29.2 | 15.8 | 3.4 | |
Lymphoma | 12.3 | 2.7 | 8.9 | 10.8 | 10.2 | 14.7 | 20.3 | 17.5 | 12.0 | 2.7 |
Ewing Sarcoma | 9.5 | 16.2 | 59.6 | 16.8 | 4.7 | 2.0 | 0.8 | |||
Chordoma | 6.3 | 1.1 | 4.2 | 6.2 | 13.5 | 18.5 | 24.4 | 20.5 | 9.3 | 2.2 |
Fibrosarcoma | 4.5 | 3.1 | 11.4 | 13.3 | 19.2 | 14.5 | 16.7 | 12.9 | 6.3 | 2.4 |
Chondrosarcoma, dedifferentiated | 2.1 | 1.7 | 2.5 | 6.7 | 18.3 | 32.5 | 17.5 | 16.7 | 4.2 | |
Malignant fibrous histiocytoma | 1.5 | 1.2 | 15.7 | 10.8 | 13.3 | 19.3 | 9.6 | 21.7 | 6.0 | 2.4 |
Osteosarcoma, parosteal | 1.2 | 17.4 | 39.1 | 27.5 | 10.1 | 5.8 | ||||
Chondrosarcoma, mesenchymal | 0.6 | 17.6 | 32.4 | 29.4 | 11.8 | 2.9 | 2.9 | |||
Adamantinoma | 0.6 | 2.9 | 29.4 | 44.1 | 5.9 | 5.9 | 5.9 | 5.9 |
Table 3
Age distribution of benign osseous tumorsa
Tumor type | Overall incidence (%) | Incidence by decade (%) | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9+ | ||
Osteochondroma | 34.9 | 11.8 | 47.8 | 18.5 | 10.6 | 5.4 | 3.6 | 1.4 | 0.9 | |
Giant cell tumor | 22.8 | 0.5 | 15.1 | 37.0 | 24.6 | 13.3 | 6.2 | 2.5 | 0.9 | |
Chondroma (enchondroma) | 13.4 | 10.7 | 21.8 | 17.0 | 17.0 | 17.3 | 8.1 | 6.6 | 1.2 | 0.3 |
Osteoid osteoma | 13.3 | 13.6 | 51.4 | 21.8 | 9.1 | 1.5 | 0.9 | 1.2 | 0.6 | |
Chondroblastoma | 4.8 | 2.5 | 58.8 | 14.3 | 10.9 | 4.2 | 8.4 | 0.8 | ||
Hemangioma | 4.3 | 3.7 | 9.3 | 13.9 | 15.7 | 25.9 | 16.7 | 11.1 | 3.7 | |
Osteoblastoma | 3.5 | 6.9 | 41.4 | 32.2 | 10.3 | 3.4 | 3.4 | 1.1 | 1.1 | |
Chondromyxoid fibroma | 1.8 | 11.1 | 24.4 | 31.1 | 13.3 | 8.9 | 8.9 | 2.2 |
Diagnosis of Soft Tissue Tumors
Despite the superiority of MR imaging in delineating soft-tissue tumors, it remains limited in its ability for precise diagnosis. There are instances, however, in which a specific diagnosis may be made or strongly suspected on the basis of MR features alone (Table 4). This is usually done on the basis of lesion signal intensity, pattern of growth, location and associated “signs” and findings. The MR imaging appearance of these lesions has been well reported, and is not reviewed here.
Table 4
Specific diagnoses which may be made or suspected on the basis of MR imaging
Vascular lesions: | Tumor-like lesions: |
Aneurysm and pseudoaneurysm | Abscess |
Arteriovenous hemangioma (avm) | Calcific myonecrosis |
Glomus tumor | Cystic adventitial disease |
Hemangioma | Epidermal inclusion cyst |
Hemangiomatosis (angiomatosis) | Fat necrosis |
Lymphangioma | Ganglion |
Lymphangiomatosis | Granuloma annulare |
Hematoma | |
Bone and cartilage forming lesions: | Hydroxyapatite crystal disease |
Extraskeletal chondroma | Intramuscular myxoma |
Myositis ossificans | Myonecrosis |
Panniculitis ossificans | Popliteal (synovial) cyst |
Synovial chondromatosis | Tophus |
Tumoral calcinosis | |
Fibrous lesions: | |
Elastofibroma | Peripheral nerve lesions: |
Fibroma of tendon sheath | Morton neuroma |
Fibromatosis colli | Neurofibroma |
Musculoaponeurotic fibromatosis | Schwannoma |
Superficial fibromatosis | Traumatic neuroma |
Lipomatous lesions: | Synovial lesions: |
Lipoma | Giant cell tumor of tendon sheath |
Lipoma arborescens | Nodular synovitis |
Lipoma of tendon sheath | Pigmented villonodular synovitis |
Lipomatosis | Synovial chondromatosis |
Lipomatosis of nerve | Synovial sarcoma |
Lipoblastoma | |
Lipoblastomatosis | |
Liposarcoma | |
Periosteal lipoma | |
Synovial lipoma |
DeSchepper et al. [46] performed a multivariate statistical analysis of ten imaging parameters, individually and in combination. These researchers found that malignancy was predicted with the highest sensitivity when lesions had a high signal intensity on T2-weighted images, were larger than 33 mm in diameter, and had heterogeneous signal intensity on T1-weighted images. Signs that had the greatest specificity for malignancy included tumor necrosis, bone or neurovascular involvement, and mean diameter of more than 66 mm. In a recent study of 548 patients by Gielen and colleagues [47] in which imaging and clinical data were available, an accuracy of 85% was reported in differentiating between benign and malignant lesions.
When a specific diagnosis is not possible, MR is often useful to formulate a suitably ordered differential diagnosis on the basis of imaging features, suspected biological potential and a knowledge of tumor prevalence based on the patient age and lesion anatomic location. This can be further refined by considering clinical history and radiologic features, such as pattern of growth, signal intensity and localization (subcutaneous, intramuscular, intermuscular, etc.). The most common malignant and benign lesions, by tumor location and patient age, are shown in Tables 5 and 6.
Table 5
Distribution of common benign soft tissue tumors by anatomic location and age
Ages | Hand and wrist | No (%) | Upper extremity | No (%) | Axilla and shoulder | No (%) | Foot and ankle | No (%) | Lower extremity | No (%) |
---|---|---|---|---|---|---|---|---|---|---|
0–5 | Hemangioma | 15(15)a | Fibrous hamartoma infancy | 15(16) | Fibrous hamartoma infancy | 23(29) | Granuloma annulare | 23(30) | Granuloma annulare | 42(23) |
Granuloma annulare | 14(14) | Granuloma annulare | 15(16) | Hemangioma | 12(15) | Infantile fibromatosis | 11(14) | Hemangioma | 26(14) | |
Infantile fibromatosis | 13(13) | Hemangioma | 14(15) | Lipoblastoma | 11(14) | Hemangioma | 8(11) | Myofibromatosis | 16(9) | |
Infantile digital fibroma | 8(8) | Infantile fibromatosis | 12(13) | Fibrous hamartoma | 7(9) | Fibromatosis | 8(11) | Fibrous histiocytoma | 15(8) | |
Fibromatosis | 8(8) | Fibrous histiocytoma | 6(6) | Myofibromatosis | 6(8) | Infantile digital fibroma | 7(9) | Lipoblastoma | 13(7) | |
Aponeurotic fibroma | 7(7) | Juvenile xanthogranuloma | 6(6) | Lymphangioma | 5(6) | Lipoblastoma | 6(8) | Lymphangioma | 10(6) | |
Fibrous histiocytoma | 5(5) | Myofibromatosis | 6(6) | Nodular fasciitis | 4(5) | Lipoma | 4(5) | Juvenile xanthogranuloma | 10(6) | |
Other | 27(28) | Other | 20(21) | Other | 12(15) | Other | 9(12) | Other | 48(27) | |
6-15 | Fibrous histiocytoma | 32(14) | Fibrous histiocytoma | 41(23) | Fibrous histiocytoma | 25(34) | Fibromatosis | 35(22) | Hemangioma | 47(22) |
Hemangioma | 31(13) | Nodular fasciitis | 39(21) | Nodular fasciitis | 18(25) | Granuloma annulare | 21(13) | Fibrous histiocytoma | 34(16) | |
Aponeurotic fibroma | 25(11) | Hemangioma | 24(13) | Hemangioma | 7(10) | Hemangioma | 21(13) | Nodular fasciitis | 22(10) | |
Fibroma tendon sheath | 22(9) | Granuloma annulare | 12(7) | Granular cell tumor | 4(5) | Fibrous histiocytoma | 14(9) | Granuloma annulare | 20(9) | |
GCT tendon sheathb | 17(7) | Fibromatosis | 11(6) | Neurofibroma | 3(4) | GCT tendon sheath | 13(8) | Fibromatosis | 14(6) | |
Fibromatosis | 13(6) | Neurofibroma | 7(4) | Lymphangioma | 2(3) | Chondroma | 11(7) | Lipoma | 13(6) | |
Lipoma | 9(4) | Neurothekeoma | 6(3) | Myofibromatosis | 2(3) | Lipoma | 9(6) | Neurofibroma | 8(4) | |
Other | 86(37) | Other | 42(23) | Other | 12(16) | Other | 37(23) | Other | 58(27) | |
16–25 | GCT tendon sheath | 84(20) | Nodular fasciitis | 130(35) | Fibrous histiocytoma | 62(36) | Fibromatosis | 46(22) | Fibrous histiocytoma | 118(24) |
Fibrous histiocytoma | 57(14) | Fibrous histiocytoma | 87(23) | Nodular fasciitis | 35(20) | GCT tendon sheath | 29(14) | Nodular fasciitis | 61(13) | |
Hemangioma | 40(10) | Hemangioma | 36(10) | Fibromatosis | 16(9) | Granuloma annulare | 25(12) | Hemangioma | 55(11) | |
Fibroma tendon sheath | 40(10) | Neurofibroma | 24(6) | Lipoma | 14(8) | Fibrous histiocytoma | 24(12) | Neurofibroma | 48(10) | |
Nodular fasciitis | 26(6) | Granuloma annulare | 20(5) | Neurofibroma | 12(7) | Hemangioma | 13(6) | Fibromatosis | 38(8) | |
Granuloma annulare | 21(5) | Granular cell tumor | 17(5) | Hemangioma | 4(2) | PVNSc | 12(6) | Lipoma | 22(5) | |
Ganglion | 20(5) | Schwannoma | 11(3) | Schwannoma | 4(2) | Neurofibroma | 11(5) | Schwannoma | 20(4) | |
Other | 132(31) | Other | 51(14)
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