Soft tissue vascular tumor-like lesions in adults: imaging and pathological analysis pitfalls per ISSVA classification

OBJECTIVES

To compare the magnetic resonance imaging (MRI) and Doppler ultrasound (DUS) findings with the pathological findings of soft tissue vascular tumors (STVTs) according to the 2018 ISSVA (International Society for the Study of Vascular Anomalies) classification to differentiate vascular tumors from vascular malformations.

METHODS

This retrospective study included patients with STVTs who underwent contrast-enhanced MRI and pathological analysis at our hospital between 2010 and 2020. The presumptive diagnosis based on the on-site imaging and histological analysis was compared with imaging and histological analysis conducted off-site utilizing the ISSVA criteria.

RESULTS

This study included 31 patients with 31 vascular tumors located in the head and neck (n = 3), trunk (n = 2), and extremities (n = 26). The off-site pathological analysis confirmed benign vascular tumors in 54.8% of cases (non-involuting congenital hemangioma: 35.5%; epithelioid hemangioma: 13%; pyogenic granuloma: 3%; and spindle cell hemangioma: 3%). Based on the off-site histological analysis, 25.8% were reclassified as having a vascular malformation whereas three had other benign lesions. Only phleboliths were associated with a vascular malformation (p = 0.03). The concordance between off-site MRI and pathological findings was fair (k = 0.3902 (0.0531-0.7274)), whereas that between on-site and off-site pathological analyses was poor (k = -0.0949 (-0.4661 to 0.2763)).

CONCLUSION

Benign vascular tumors have non-specific imaging features on imaging with some overlap with atypical vascular malformations. Therefore, histological analysis is recommended. Imaging and pathological analyses should be performed in accordance with the ISSVA classification to minimize inter-observer discrepancies.

CRITICAL RELEVANCE STATEMENT

Imaging features of benign vascular tumors on MRI are non-specific, leading to discrepancies with pathological findings and potential overlap with atypical vascular malformations. Imaging and histological analyses should be performed in accordance with ISSVA guidelines to improve patient management.

KEY POINTS

The imaging features of benign vascular tumors are non-specific. Histological analysis is recommended for soft tissue vascular tumors in adults. Analyses of soft tissue vascular tumors should be performed in accordance with ISSVA guidelines.

Applying dynamic contrast-enhanced MRI tracer kinetic models to differentiate benign and malignant soft tissue tumors

BACKGROUND

To explore the potential of different quantitative dynamic contrast-enhanced (qDCE)-MRI tracer kinetic (TK) models and qDCE parameters in discriminating benign from malignant soft tissue tumors (STTs).

METHODS

This research included 92 patients (41females, 51 males; age range 16-86 years, mean age 51.24 years) with STTs. The qDCE parameters (Ktrans, Kep, Ve, Vp, F, PS, MTT and E) for regions of interest of STTs were estimated by using the following TK models: Tofts (TOFTS), Extended Tofts (EXTOFTS), adiabatic tissue homogeneity (ATH), conventional compartmental (CC), and distributed parameter (DP). We established a comprehensive model combining the morphologic features, time-signal intensity curve shape, and optimal qDCE parameters. The capacities to identify benign and malignant STTs was evaluated using the area under the curve (AUC), degree of accuracy, and the analysis of the decision curve.

RESULTS

TOFTS-Ktrans, EXTOFTS-Ktrans, EXTOFTS-Vp, CC-Vp and DP-Vp demonstrated good diagnostic performance among the qDCE parameters. Compared with the other TK models, the DP model has a higher AUC and a greater level of accuracy. The comprehensive model (AUC, 0.936, 0.884-0.988) demonstrated superiority in discriminating benign and malignant STTs, outperforming the qDCE models (AUC, 0.899-0.915) and the traditional imaging model (AUC, 0.802, 0.712-0.891) alone.

CONCLUSIONS

Various TK models successfully distinguish benign from malignant STTs. The comprehensive model is a noninvasive approach incorporating morphological imaging aspects and qDCE parameters, and shows significant potential for further development.

Unplanned Sarcoma Excisions: Understanding How They Happen

BACKGROUND

Soft-tissue sarcomas present as a mass with nonspecific symptoms, and unplanned excisions commonly occur. The purpose of this study was to analyze the incidence of unplanned excisions performed by orthopaedic surgeons and to conduct a root cause analysis (RCA) of the steps that led to unplanned excisions in all the cases.

METHODS

A retrospective case-control study was conducted. Two cohorts were identified, one including patients who underwent an unplanned excision of a soft-tissue sarcoma (n = 107) and a second cohort with patients whose entire care was performed at our sarcoma center (n = 102). A RCA was conducted with the whole sample to identify the preventable causes that led to sarcoma unplanned excisions.

RESULTS

Orthopedic surgeons were the second group of physicians to perform the most unplanned excisions, only behind general surgeons. Inadequate imaging was encountered in 76.6% of the patients (n = 82, 95% confidence interval, 67.8 to 83.6). Forty-five patients (42.1%) had no imaging studies before the unplanned procedure. In the RCA, the most notable obstacles found were (1) incorrect assumption of a benign diagnosis, (2) failure to obtain the appropriate imaging study, (3) incorrectly reported imaging studies, (4) failure to order a biopsy, and (5) incorrect reporting of the biopsy.

CONCLUSIONS

Despite educational efforts, unplanned excisions and the devastating consequences that sometimes follow continue to occur. Orthopaedic surgeons persist in playing a role in the unplanned procedure burden.

Peripheral vascular lesions in adults referred to MRI/MRA: Multivariable analysis of imaging features to help differentiate benign vascular anomalies from malignancies

PURPOSE

Symptomatic peripheral vascular lesions in adults are often clinically diagnosed as benign vascular anomalies and may receive MRI/MRA for pre-treatment vascular mapping. Malignant neoplasms are difficult to distinguish from benign vascular anomalies on MRI/MRA. This study was performed to determine if there are imaging signs that can distinguish malignancies from benign vascular anomalies in adults imaged with MRI/MRA.

MATERIALS AND METHODS

A radiology database was retrospectively searched for ISSVA classification terms in MRI/MRA reports from 1/1/2002-1/1/2019. Adult patients (n = 50, 52 corresponding lesions) with contrast-enhanced MRI/MRA, peripheral soft tissue based lesion (s), and available pathology or long-term (>1 year) imaging follow-up were included. MRI/MRA images were reviewed by 3 readers for the following lesional characteristics: morphology (marginal lobulation, internal septations, distinct soft tissue mass), peri-articular location, T2-weighted characteristics (hyperintensity, heterogeneity, perilesional edema, and adjacent triangular T2-peaks), bulk fat, hemorrhage, enhancement pattern (peripheral, diffuse, or absent), neovascularity, low-flow venous malformation type enhancement, arterial enhancement within 6 s, enhancement curve (progressive, plateau, or washout), measured size, and multifocality. The MRI/MRA features' associated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. To identify factors predictive of malignancy, a two-stage multivariable analysis was performed.

RESULTS

23% (12/52) of the lesions, corresponding to 22% (11/50) of the patients, were malignant neoplasms. No single imaging feature reliably predicted malignancy (PPV ≤ 60%). Absence of distinct soft tissue mass excluded malignancy (NPV 100%). Multivariate analysis derived a summary score based on the five strongest predictors of malignancy: adjacent T2 peaks, age ≥ 70 years, distinct soft tissue mass, lesion size ≥ 5 cm, and absence of septations. A score ≥ 3 resulted in sensitivity of 92% and specificity of 85%.

CONCLUSION

Extremity MRI/MRA rarely differentiates malignant from benign soft-tissue vascular tumors in adults. However, MRI/MRA can suggest malignancy when patient age and multiple imaging features are considered. Periodic clinical follow-up after the planned endovascular or operative procedure should be performed to avoid missing a malignancy.

The EFSUMB Guidelines and Recommendations for Musculoskeletal Ultrasound - Part II: Joint Pathologies, Pediatric Applications, and Guided Procedures

The second part of the Guidelines and Recommendations for Musculoskeletal Ultrasound (MSUS), produced under the auspices of EFSUMB, following the same methodology as for Part 1, provides information and recommendations on the use of this imaging modality for joint pathology, pediatric applications, and musculoskeletal ultrasound-guided procedures. Clinical application, practical points, limitations, and artifacts are described and discussed for every joint or procedure. The document is intended to guide clinical users in their daily practice.

MRI imaging of soft tissues tumours and tumour like lesions-SLAM approach

Imaging is vital in characterising and delineating the extent of soft tissue tumours and there is abundant literature on this. A simplified approach is required to characterise the lesions on MR and we describe a simplified street-smart approach called SLAM (signal, location, age, multiplicity and matrix).

WHO classification of soft tissue tumours 2020: An update and simplified approach for radiologists

The WHO classification of soft tissue tumours categorizes the lesions based on histological differentiation. In the recent fifth edition (2020), many new entities have been introduced, based on their distinct biological behaviour, genetics and morphology. With the recent advances and better understanding of molecular genetics, several novel recurrent genetic alterations have been incorporated in this edition. These may serve as reliable diagnostic and prognostic markers for various soft tissue tumours. Though predominantly a pathologist's game; the radiologists must be aware of the recent updates to contribute towards the optimal diagnosis and management of soft tissue tumours. The imaging features of the new entities have not yet been described but are expected to be explored in the coming years. We hereby present a concise review of the updates in the recent WHO classification of soft tissue tumours. We have tried to emphasize the novel molecular genetics and their surrogate immunohistochemical markers which have brought a paradigm shift in the diagnosis, therapeutics, and prognosis of soft tissue tumours. We also present simplified diagnostic algorithms to characterize soft tissue tumours based on the clinico-radiological features.

Disseminated Nocardiosis Masquerading as Soft-Tissue Malignancy: A Case Report

CASE

A 59-year-old man, immunosuppressed after renal transplant, presented with a painful posterior thigh mass concerning for malignancy, as well as pulmonary and posterior chest wall nodules. Cultures and mass spectrometry identified Nocardia paucivorans. The patient underwent operative irrigation and debridement of the posterior thigh and chest wall, with 12 months of antibiotic therapy.

CONCLUSION

A 2-week delay in appropriate treatment was due to low suspicion for infectious etiology. Since cultures generally take weeks for positive diagnosis, advanced molecular or biochemical methods should be used. This case demonstrates importance in maintaining a high index of suspicion for nocardiosis in immunocompromised patients with soft-tissue masses.

A Pattern-based Imaging Approach to Pediatric Jaw Lesions

Jaw lesions in the pediatric population, although infrequently encountered in clinical practice, can cause functional impairment and cosmetic disfiguring. It is further complicated by the difficulty in diagnosis due to complex anatomy and facial developmental process during infancy and childhood. Intraosseous pediatric jaw lesions may vary from odontogenic to nonodontogenic types with nonspecific clinical features in most cases. They deserve careful attention by a systematic approach to provide a relevant diagnosis or differential diagnosis for timely management. Imaging plays a major role in diagnosis with orthopantomograph being the foremost investigation, followed by cross-sectional imaging, essentially computed tomography as a problem-solving tool. This article highlights the imaging spectrum of various jaw lesions in the pediatric population with a pattern-based approach for radiological diagnosis.

Whole-tumor 3D volumetric MRI-based radiomics approach for distinguishing between benign and malignant soft tissue tumors

OBJECTIVES

Our purpose was to differentiate between malignant from benign soft tissue neoplasms using a combination of MRI-based radiomics metrics and machine learning.

METHODS

Our retrospective study identified 128 histologically diagnosed benign (n = 36) and malignant (n = 92) soft tissue lesions. 3D ROIs were manually drawn on 1 sequence of interest and co-registered to other sequences obtained during the same study. One thousand seven hundred eight radiomics features were extracted from each ROI. Univariate analyses with supportive ROC analyses were conducted to evaluate the discriminative power of predictive models constructed using Real Adaptive Boosting (Adaboost) and Random Forest (RF) machine learning approaches.

RESULTS

Univariate analyses demonstrated that 36.89% of individual radiomics varied significantly between benign and malignant lesions at the p ≤ 0.05 level. Adaboost and RF performed similarly well, with AUCs of 0.77 (95% CI 0.68-0.85) and 0.72 (95% CI 0.63-0.81), respectively, after 10-fold cross-validation. Restricting the machine learning models to only sequences extracted from T2FS and STIR sequences maintained comparable performance, with AUCs of 0.73 (95% CI 0.64-0.82) and 0.75 (95% CI 0.65-0.84), respectively.

CONCLUSION

Machine learning decision classifiers constructed from MRI-based radiomics features show promising ability to preoperatively discriminate between benign and malignant soft tissue masses. Our approach maintains applicability even when the dataset is restricted to T2FS and STIR fluid-sensitive sequences, which may bolster practicality in clinical application scenarios by eliminating the need for complex co-registrations for multisequence analysis.

KEY POINTS

• Predictive models constructed from MRI-based radiomics data and machine learning-augmented approaches yielded good discriminative power to correctly classify benign and malignant lesions on preoperative scans, with AUCs of 0.77 (95% CI 0.68-0.85) and 0.72 (95% CI 0.63-0.81) for Real Adaptive Boosting (Adaboost) and Random Forest (RF), respectively. • Restricting the models to only use metrics extracted from T2 fat-saturated (T2FS) and Short-Tau Inversion Recovery (STIR) sequences yielded similar performance, with AUCs of 0.73 (95% CI 0.64-0.82) and 0.75 (95% CI 0.65-0.84) for Adaboost and RF, respectively. • Radiomics-based machine learning decision classifiers constructed from multicentric data more closely mimic the real-world practice environment and warrant additional validation ahead of prospective implementation into clinical workflows.

Soft Tissue Sarcomas

Imaging evaluation of soft tissue masses is essential for diagnosis, preoperative staging, and post-treatment follow-up. Magnetic resonance imaging plays the major role because of its superior resolution that helps in better tissue characterization, and its multiplanar imaging capability in evaluation of soft tissue masses. Additional imaging techniques, such as radiographs, computed tomography, positron-emission tomography-CT, radionuclide scintigraphy and ultrasonography, also play vital roles by providing additional information required in management of soft tissue masses. Knowledge of the usefulness and limitations of these imaging techniques is essential for their judicious selection. This article reviews the current role of various imaging techniques in diagnosis, presurgical planning, and post-treatment follow-up of soft tissue masses.

Characterization of small, deeply located soft-tissue tumors: Conventional magnetic resonance imaging features and apparent diffusion coefficient for differentiation between non-malignancy and malignancy

OBJECTIVES

To compare magnetic resonance imaging (MRI) parameters of small, deeply located non-malignant and malignant soft-tissue tumors (STTs).

METHODS

Between May 2011 and December 2017, 95 MRIs in 95 patients with pathologically proven STTs of small size (<5 cm) and deep location (66 non-malignant and 29 malignant) were identified. For qualitative parameters, consensus reading was performed by three radiologists for presence of necrosis, infiltration, lobulation, and the tail sign. Apparent diffusion coefficient (ADC) was analyzed by two other radiologists independently. Univariable and multivariable analyses were performed to determine the diagnostic performances of MRI parameters in differentiating non-malignancy and malignancy, and for non-myxoid, non-hemosiderin STTs and myxoid STTs as subgroups. Interobserver agreement for ADC measurement was calculated with the intraclass correlation coefficient.

RESULTS

Interobserver agreement on ADC measurement was almost perfect. On univariable analysis, the malignant group showed a significantly larger size, lower ADC, and higher incidence of all qualitative MRI parameters for all STTs. Size (p = 0.012, odds ratio [OR] 2.57), ADC (p = 0.041, OR 3.85), and the tail sign (p = 0.009, OR 6.47) were independently significant on multivariable analysis. For non-myxoid, non-hemosiderin STTs, age, size, ADC, frequency of infiltration, lobulation, and the tail sign showed significant differences between non-malignancy and malignancy on univariable analysis. Only ADC (p = 0.032, OR 142.86) retained its independence on multivariable analysis. For myxoid STTs, only size and tail sign were significant on univariable analysis without independent significance.

CONCLUSIONS

Size, ADC, and incidence of qualitative MRI parameters were significantly different between small, deeply located non-malignant and malignant STTs. Only ADC was independently significant for both overall analysis and the non-myxoid, non-hemosiderin subgroup.

Adventitious bursitis in the plantar fat pad of forefoot presenting as a tumoral mass

Adventitious bursitis of the plantar fat pad is a common cause of forefoot pain. It may develop at sites where subcutaneous tissue is exposed to friction and high pressure. In the forefoot, adventitious bursitis is usually adjacent to bony prominences of the metatarsal heads. Diagnosis and management of adventitious bursitis usually do not require imaging studies. However, the condition occasionally presents as a solid pseudotumoral mass requiring imaging. Magnetic resonance imaging (MRI) may demonstrate a heterogeneous mass with a solid component exhibiting intermediate to high signal intensity on T2-weighted images and thick nodular enhancement suggesting a neoplastic lesion. We report three cases of adventitious bursitis in patients who complained of a painful palpable mass on the forefoot, with a partially solid and enhancing component seen on MRI. In the first case, a biopsy was performed for the diagnosis of adventitious bursitis. The two other cases exhibited a solid component on MRI. However, a diagnosis of adventitious bursitis was suspected, and it was felt that a biopsy could be postponed. The spontaneous regression of the mass with relative discharge of the forefoot pressure confirmed the diagnosis. With these three cases, we illustrate the MR findings that could suggest adventitious bursitis despite the presence of a solid component and that may obviate the need for pathologic proof.

Diagnostic importance of clinicopathologic features and p16, CD34, MDM2 expression in differential diagnosis of adipocytic tumors

OBJECTIVE

The aim of this study was to investigate the immunohistochemical stain profiling of adipocytic tumors.

METHODS

From our archive files between the years of 2012-2018, excised, formalin-fixed and paraffin-embedded adipocytic tumors were retrospectively screened and 61 subjects were selected. The gender, age, tumor location and tumor diameter were evaluated. The cases were investigated in terms of p16, CD34, MDM2 expression and clinicopathological information.

RESULTS

Of the 61 patients included in the study, we found that 2 had hibernoma, 4 had lipoblastoma, 14 had spindle cell lipoma (SCL), 10 had lipoma, 20 had atypical lipomatous tumor/well differentiated liposarcoma (ALT/WDL), and 11 had dedifferentiated liposarcoma (DDL). In terms of diameter, ALT/WDL and DDL were significantly different from the others (p=0.001, p=0.001, respectively). There was a significant difference between the groups according to the location (p=0.001). 35% (7/20) of ALT/WDLs were in the lower extremities (thighs) and 35% (7/20) were located in the retroperitoneal region. 70% of DDLs (7/11) were located in the retroperitoneum. When CD34 expression was evaluated among the groups, a significant difference was observed (p=0.001). CD34 was positive in 92.9% of SCL cases. p16 immunoreactivity was significantly different between the groups (p=0.001). p16 expression was observed in 50.5% of ALT / WDL cases and 79% of DDL cases.

CONCLUSION

p16 and CD34 expression are valuable in the differential diagnosis of lipomatous tumors when radiological and clinical considerations do not help to differential diagnosis of adipocytic tumors.

LEVEL OF EVIDENCE

Level IV, Therapeutic Study.

Is MRI diffusion-weighted imaging a reliable tool for the diagnosis and posttherapeutic follow-up of extremity soft tissue neoplasms?

Purpose: The aim of this study was to evaluate the benefit of using quantitative diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping in the initial diagnosis and post-therapeutic follow-up of extremity soft tissue masses. Patients and Methods: This study included 90 patients with extremity soft tissue masses. The DWI was obtained with 3 b values, including 0, 400, and 800 s/mm2. Calculation of the ADC value of the lesion was done by placing the region of interest (ROI) to include the largest area of the lesion. ADC values were compared with the histopathology. Eighteen patients had posttherapeutic magnetic resonance imaging (MRI). Results: Benign masses, fibromatosis, and malignant soft tissue masses had mean ADC values of 1.18 ± 1.0191 × 10−3 mm2/s; 1.31 ± 0.245 × 10−3 mm2/sec; and 1.3 ± 0.7 × 10−3 mm2/s, respectively. Myxomatous malignant masses had an ADC value of 2.6 ± 0.55 × 10−3 mm2/s, while nonmyxomatous malignant masses had an ADC value of 1.1 ± 0.8 × 10−3 mm2/s. ADC cutoff value between benign and non-benign (including malignant and locally aggressive masses) was 0.6 × 10−3 mm2/sec with 98.3% sensitivity and 50% specificity (P = 0.5123). The statistical difference between malignant soft tissue masses (mean ADC 1.309 ± 0.723 × 10−3 mm2/s) and fibromatosis masses (mean ADC value 1.31 ± 0.245 × 10−3 mm2/s) using a comparative T-test proved to be of poor significance level (P value ~ 0.9757). Nine patients with soft tissue sarcomas (STSs) had pre and post-therapeutic MRI examinations showing a mean increase of the recorded ADC values by about 0.28 × 10−3 mm2/s in the post-therapy study as compared with the recorded initial pretreatment values. Analysis of the post-therapy follow-up studies of fibromatosis showed that lesions with favorable response to chemotherapy or radiotherapy (8/12) exhibited significantly lower ADC values than those showing progressive disease course. Conclusion: DWI with ADC mapping of extremity soft tissue tumors are so complicated that they alone may not be of much value in differentiating between benign and malignant tumors; however, it can be used as a tool for monitoring response to treatment.

Development and Validation of Nomograms for Malignancy Prediction in Soft Tissue Tumors Using Magnetic Resonance Imaging Measurements

The objective of this study was to develop, validate, and compare nomograms for malignancy prediction in soft tissue tumors (STTs) using conventional and diffusion-weighted magnetic resonance imaging (MRI) measurements. Between May 2011 and December 2016, 239 MRI examinations from 236 patients with pathologically proven STTs were included retrospectively and assigned randomly to training (n = 100) and validation (n = 139) cohorts. MRI of each lesion was reviewed to assess conventional and diffusion-weighted imaging (DWI) measurements. Multivariate nomograms based on logistic regression analyses were built using conventional measurements with and without DWI measurements. Predictive accuracy was measured using the concordance index (C-index) and calibration plots. Statistical differences between the C-indexes of the two models were analyzed. Models were validated by leave-one-out cross-validation and by using a validation cohort. The mean lesion size, presence of infiltration, edema, and the absence of the split fat sign were significant and independent predictors of malignancy and included in the conventional model. In addition to these measurements, the mean and minimum apparent diffusion coefficient values were included in the DWI model. The DWI model exhibited significantly higher diagnostic performance only in the validation cohort (training cohort, 0.899 vs. 0.886, P = 0.284; validation cohort, 0.791 vs. 0.757, P = 0.020). Calibration plots showed fair agreements between the nomogram predictions and actual observations in both cohorts. In conclusion, nomograms using MRI features as variables can be utilized to predict the malignancy probability in patients with STTs. There was no definite gain in diagnostic accuracy when additional DWI features were used.

The diagnostic significance of repeat ultrasound-guided biopsy of musculoskeletal soft-tissue lesions with initially inconclusive biopsy results

INTRODUCTION

To determine the diagnostic yield of repeat ultrasound (US)-guided biopsy of musculoskeletal soft-tissue lesions with initially inconclusive biopsy results, and to explore predictive factors for success of repeat biopsy.

MATERIALS AND METHODS

This retrospective study included 42 patients who underwent a repeat (second) US-guided biopsy session to target a musculoskeletal soft-tissue lesion because an initial US-guided biopsy session provided inconclusive results. Both biopsy sessions were performed in a tertiary referral center for soft-tissue sarcomas.

RESULTS

The diagnostic yield of repeat US-guided biopsy was 47.6%. Malignant nature of the lesion (P = 0.031), sharp lesion borders on US (P = 0.011), and good to very good lesion visibility on US (P = 0.017) were significantly associated with a diagnostic repeat US-guided biopsy. There was also a trend towards significance (P = 0.073) for a higher number of biopsy passes through the lesion. Other patient characteristics (age and gender), magnetic resonance imaging features (lesion homogeneity on T1-weighted, T2-weighted, and gadolinium chelate enhanced sequences, borders, enhancement pattern, depth and size), US features (lesion appearance, vascular flow, and depth), biopsy-related factors (days between initial and repeat US-guided biopsy, needle diameter, maximum length of acquired samples), and operator-related factors (same or different radiologists/pathologists for initial and repeat biopsies), were not associated with the diagnostic success of the repeat US-guided biopsy.

CONCLUSIONS

Repeat US-guided biopsy of a musculoskeletal soft-tissue lesion with initially inconclusive biopsy results can be useful to establish a final diagnosis. Lesion features on US (borders and visibility) may be used to prospectively determine the utility of a repeat US-guided biopsy.

Beyond hernias: a multimodality review of abdominal wall pathology

The diagnosis of abdominal wall pathology is often obvious on clinical physical examination; however, multimodality imaging often yields incidental, and occasionally important, findings aiding in assessing the overall clinical picture. While various hernias are common, there are numerous other causes of abdominal wall pathology. Knowledge of these entities is crucial to avoid misinterpretation and assure proper radiological judgment.

Assessing the role of ¹⁸F-FDG PET and ¹⁸F-FDG PET/CT in the diagnosis of soft tissue musculoskeletal malignancies: a systematic review and meta-analysis

PURPOSE

Twelve years ago a meta-analysis evaluated the diagnostic performance of (18)F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in assessing musculoskeletal soft tissue lesions (MsSTL). Currently, PET/CT has substituted PET imaging; however, there has not been any published meta-analysis on the use of PET/CT or a comparison of PET/CT with PET in the diagnosis of MsSTL. Therefore, we conducted a meta-analysis to identify the current diagnostic performance of (18)F-FDG PET/CT and determine if there is added value when compared to PET.

METHODS

A systematic review of English articles was conducted, and MEDLINE PubMed, the Cochrane Library, and Embase were searched from 1996 to March 2015. Studies exploring the diagnostic accuracy of (18)F-FDG PET/CT (or dedicated PET) compared to histopathology in patients with MsSTL undergoing investigation for malignancy were included.

RESULTS

Our meta-analysis included 14 articles composed of 755 patients with 757 soft tissue lesions. There were 451 (60 %) malignant tumors and 306 benign lesions. The (18)F-FDG PET/CT (and dedicated PET) mean sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for diagnosing MsSTL were 0.96 (0.90, 1.00), 0.77 (0.67, 0.86), 0.88 (0.85, 0.91), 0.86 (0.78, 0.94), and 0.91 (0.83, 0.99), respectively. The posterior mean (95 % highest posterior density interval) for the AUC was 0.92 (0.88, 0.96). PET/CT had higher specificity, accuracy, and positive predictive value when compared to a dedicated PET (0.85, 0.89, and 0.91 vs 0.71, 0.85, and 0.82, respectively).

CONCLUSION

(18)F-FDG PET/CT and dedicated PET are both highly accurate in the diagnosis of MsSTL. PET/CT is more accurate and specific and has a higher positive predictive value than PET.

Soft-tissue masses: optimal imaging protocol and reporting

OBJECTIVE

Soft-tissue masses derive from a wide spectrum of tissues, and it may be difficult to differentiate nonneoplastic from neoplastic as well as benign from malignant lesions, to say nothing of making a single histologic diagnosis on the basis of imaging. The purpose of this article is to discuss optimal imaging protocols and reporting of soft-tissue masses.

CONCLUSION

The radiologist should be prepared, if at all possible, to knowledgably examine the patient, optimize an imaging protocol, and differentiate among lesions. Specific features of an MRI examination must be discussed in each report to completely evaluate the mass and perform efficacious biopsy, staging, and eventual treatment of the lesion. Careful and systematic reporting of the examinations should avoid the devastating consequences of either overlooking a sarcoma or overtreating a benign lesion.

Non-Invasive Diagnosis of Abdomino-Pelvic Masses: Role of Multimodality Imaging

Recent advances in radiology have greatly increased the ability to make highly accurate diagnosis. Biopsy of many commonly seen lesions is no longer performed as the radiological findings are pathognomonic. This gives rise to the concept of ‘virtual biopsy’, a term coined on the lines of other imaging techniques such as virtual colonoscopy. Virtual biopsy is not a new imaging technique but a new concept which refers to the use of existing imaging modalities to evaluate the morphological features of tumors and arriving at a non-invasive diagnosis with a high degree of confidence obviating the need for true biopsy. Elements of virtual biopsy have already been incorporated into some evidence-based guidelines, and it is expected that with further technological advancements, an increasing number of tumors may be diagnosed and managed accordingly. A wider acceptance of virtual biopsy could further reduce the need for invasive biopsies and its attendant costs and risks. In this review article, we use index cases to further emphasize this concept.