How accurate is the clinical and radiological evaluation of orbital lesions in comparison to surgical orbital biopsy?

Can 18F-FDG PET/CT findings be used to predict orbital tumor histology?

PURPOSE

To investigate whether 18F-FDG PET/CT might be useful to predict the histology of various orbital tumors based on the maximum standard uptake value (SUVmax) and the OMSUV (orbital max SUV)/MLSUV (mean liver SUV) ratio.

PATIENTS AND METHODS

A retrospective single-center study was conducted between May 2019 and December 2020. Patients with an orbital mass who underwent preoperative 18F-FDG PET/CT followed by an orbital biopsy were included. Tumor histology was classified as follows: orbital inflammation, solid tumor, low-grade lymphoid tumor, and high-grade lymphoid tumor. Orbital tumors were also classified as indolent or aggressive. Data recorded included the orbital SUVmax, OMSUV/MLSUV ratio and additional extra-orbital SUV sites.

RESULTS

Forty-five patients (24 men) were included. There were 15 (33.3%), 14 (31.1%), 9 (20%), and 7 (15.5%) cases of orbital inflammation, solid tumor, low-grade lymphoid tumor, and high-grade lymphoid tumor, respectively. No correlation was found between the OMSUV/MLSUV ratio and orbital SUVmax and tumor histology (Z = -0.77, Z = -0.6, Z = -1.6, and Z = 0.94, all P > 0.05, respectively). No correlation was found between the OMSUV/MLSUV ratio (Z = -1.42, P > 0.05) and orbital SUVmax (Z = -0.82, P > 0.05) and tumor aggressiveness (indolent versus aggressive). Subgroup analyses showed that SUVmax was predictive of lymphoma aggressiveness (P = 0.05) and was able to distinguish orbital cancers (all lymphomas+solid tumors) from benign tumors (P = 0.02).

CONCLUSION

18F-FDG PET/CT could not be used to predict the underlying orbital tumor histology. However, more aggressive tumors, especially high-grade lymphomas and cancers, tended to have a higher orbital SUVmax compared to indolent lesions.

Radiopathological Correlation in Orbital Lesions

PURPOSE

The objective is to analyze the radiological diagnosis of orbital lesions and their correlation with the final histopathological findings. We compared the initial reports by extramural radiologists and an in-house radiologist specialized in orbital imaging to evaluate the diagnostic accuracy in the interpretation of orbital imaging.

METHODS

This was a retrospective chart review of forty patients referred to a Tertiary Eye Care Center in South India over a period of 7 years. These patients already had their imaging done elsewhere. The imaging was re-evaluated by an in-house radiologist. The radiological findings were correlated with the histopathological diagnosis. The diagnostic accuracy between the two radiologists was compared. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value in differentiating malignant from benign lesions were calculated in both groups. The sensitivity and PPV of the radiological diagnosis for neoplastic and inflammatory lesions in both groups were analyzed.

RESULTS

The accuracy in differentiating malignant from benign and inflammatory lesions by our in-house radiologist and extramural radiologists was 95% (κ = 0.9 [0.764, 0.997]) and 50% (κ = 0.036 [-0.160, 0.232]), respectively. The sensitivity and PPV of the radiological diagnosis by our in-house radiologist were 93.31% and 100% for benign lesions and 95.24% and 95.24% for malignant lesions. On the contrary, reports from the extramural radiologists showed a sensitivity and PPV of 76.92% and 66.67% for benign lesions and 14.28% and 60% for malignant lesions.

CONCLUSION

A high radiological diagnostic accuracy is possible when analyzed by radiologists experienced in orbital imaging.

The transconjunctival orbitotomy: A versatile approach to the orbit and beyond

In the management of orbital disorders and defects, minimally invasive surgical approaches have become increasingly efficient for their reduction of operative trauma and access without compromise of therapeutic benefit or diagnostic yield. Various approaches have focused on bone- and canthal-sparing techniques and concealed and small skin incisions. We review the current state of knowledge of procedures to enter the orbit via the conjunctiva. Any quadrant of the orbit can be accessed via the conjunctiva. Surgical incisions involve the orbital palpebral, forniceal, and bulbar conjunctiva. According to the location, nature, and size of the lesion, the transconjunctival orbitotomy can be used as a single procedure, in combination with a caruncular approach or as an adjunct in a multidisciplinary procedure for lesions extending deep into or outside the orbit. The working space and field of operating view can be expanded by releasing the horizontal tension of the eyelid with a lateral cantholysis, lateral paracanthal blepharotomy, or medial lid split procedure. Complications related to the conjunctival incision are reduced to dry eye disease.

End-to-End Deep-Learning-Based Diagnosis of Benign and Malignant Orbital Tumors on Computed Tomography Images

Determining the nature of orbital tumors is challenging for current imaging interpretation methods, which hinders timely treatment. This study aimed to propose an end-to-end deep learning system to automatically diagnose orbital tumors. A multi-center dataset of 602 non-contrast-enhanced computed tomography (CT) images were prepared. After image annotation and preprocessing, the CT images were used to train and test the deep learning (DL) model for the following two stages: orbital tumor segmentation and classification. The performance on the testing set was compared with the assessment of three ophthalmologists. For tumor segmentation, the model achieved a satisfactory performance, with an average dice similarity coefficient of 0.89. The classification model had an accuracy of 86.96%, a sensitivity of 80.00%, and a specificity of 94.12%. The area under the receiver operating characteristics curve (AUC) of the 10-fold cross-validation ranged from 0.8439 to 0.9546. There was no significant difference on diagnostic performance of the DL-based system and three ophthalmologists (p > 0.05). The proposed end-to-end deep learning system could deliver accurate segmentation and diagnosis of orbital tumors based on noninvasive CT images. Its effectiveness and independence from human interaction allow the potential for tumor screening in the orbit and other parts of the body.

Multi-disciplinary team meetings with specialist radiologists may improve pre-operative clinico-radiological diagnostic accuracy in patients requiring orbital biopsy and offer reciprocal educational opportunities

BACKGROUND

Accurate pre-operative diagnosis of orbital lesions supports appropriate prioritisation of patients into available theatre time. We examine the accuracy of pre-operative clinico-radiological diagnosis in a tertiary centre with weekly dedicated orbital clinics and associated multi-disciplinary team meetings.

METHODS

A retrospective case notes review was undertaken for all patients who had an orbital biopsy performed at Bristol Eye Hospital between 2007 and 2017. In this centre, pre-operative clinico-radiological differential diagnoses are discussed during multi-disciplinary team meetings including two orbital specialist ophthalmologists and a specialist neuro-radiologist. Clinico-radiological diagnoses were compared with histopathological outcomes. Subcategory analysis according to histopathological diagnosis was undertaken to look for trends.

RESULTS

172 biopsies were taken from 156 patients, median age 59 years (range 3 months to 91 years). 60.9% of patient were females, with equal numbers of right and left-sided biopsies. 11 patients had inconclusive histopathology. 15 patients did not have a documented preoperative diagnosis or differential offered in available notes. 71 patients (49.0%) demonstrated an exact match between clinico-radiological and histopathological diagnosis, 93 (64.1%) demonstrated a category match (e.g. inflammatory, lymphoproliferative) and for 111 (76.6%), the histopathological diagnosis was considered within the list of proffered clinico-radiological differential diagnoses.

CONCLUSIONS

Accuracy of pre-operative diagnosis of orbital lesions undergoing biopsy was higher in our series than previously reported by Koukoulli et al. Specialist head and neck radiology input via regular orbital multi-disciplinary meetings might be reciprocally educational and explain this difference. The authors recommend all surgeons who perform orbital surgery should have access to such multi-disciplinary meetings.

Point-of-Care Ultrasound Assessment of Orbital Rhabdomyosarcoma in a Pediatric Patient

ABSTRACT

Rhabdomyosarcoma is the most common soft tissue tumor in children and orbital lesions account for 10% of these diagnoses. This case describes a young boy who presented with eyelid swelling that was initially concerning for an expanding hematoma given a history of recent trauma to the eye. Point-of-care ultrasound identified 2 distinct lesions surrounding the globe, which prompted further investigation, including ophthalmology consult and computed tomography. The case presented highlights the initial misdiagnosis on both point-of-care ultrasound and computed tomography and the importance of using color Doppler on ultrasound to distinguish an orbital rhabdomyosarcoma from a posttraumatic hematoma.

[Differential diagnosis of intraorbital masses - a narrative review]

OBJECTIVE

Intraorbital masses represent a condition that is frequently threatening for the visual system. A rigorous differential diagnosis is essential to promptly initiate appropriate therapy and optimize prognosis.

MATERIALS/METHODS

Narrative review of current literature and expert recommendations. For further illustration we describe the case of a 71-year-old male admitted to our department three months after sinus surgery. Postoperative intraorbital hematoma of the right orbit had been treated conservatively with antibiotics/corticosteroids, leading to a near-complete unilateral visual loss. The immediate surgical intervention aimed at decompression of the orbit and the optical nerve. Due to the delay, the intervention could not prevent formation of a lipogranuloma. Inflammatory phases associated with the lipogranuloma are successfully managed by conservative treatment based on multidisciplinary recommendations.

RESULTS

In the case reported, delay of surgical therapy acted as a cause of intraorbital lipogranuloma formation. Literature supports our recommendation of immediate surgical intervention in case of acute retrobulbar hematoma. Besides acute conditions, intraorbital masses can be a sign of systemic disease. In every case, a multidisciplinary therapeutic approach is required for adequate management.

CONCLUSIONS

Intraorbital masses can occur as a complication of trauma or e.g. sinus surgery. On the other hand they can be a sign of systemic disease. Timely diagnosis and treatment prevents from visual loss. That is why rigorous differential diagnosis is essential for every discipline managing intraorbital lesions.

A Magnetic Resonance Imaging Radiomics Signature to Distinguish Benign From Malignant Orbital Lesions

OBJECTIVES

Distinguishing benign from malignant orbital lesions remains challenging both clinically and with imaging, leading to risky biopsies. The objective was to differentiate benign from malignant orbital lesions using radiomics on 3 T magnetic resonance imaging (MRI) examinations.

MATERIALS AND METHODS

This institutional review board-approved prospective single-center study enrolled consecutive patients presenting with an orbital lesion undergoing a 3 T MRI prior to surgery from December 2015 to July 2019. Radiomics features were extracted from 6 MRI sequences (T1-weighted images [WIs], DIXON-T2-WI, diffusion-WI, postcontrast DIXON-T1-WI) using the Pyradiomics software. Features were selected based on their intraobserver and interobserver reproducibility, nonredundancy, and with a sequential step forward feature selection method. Selected features were used to train and optimize a Random Forest algorithm on the training set (75%) with 5-fold cross-validation. Performance metrics were computed on a held-out test set (25%) with bootstrap 95% confidence intervals (95% CIs). Five residents, 4 general radiologists, and 3 expert neuroradiologists were evaluated on their ability to visually distinguish benign from malignant lesions on the test set. Performance comparisons between reader groups and the model were performed using McNemar test. The impact of clinical and categorizable imaging data on algorithm performance was also assessed.

RESULTS

A total of 200 patients (116 [58%] women and 84 [42%] men; mean age, 53.0 ± 17.9 years) with 126 of 200 (63%) benign and 74 of 200 (37%) malignant orbital lesions were included in the study. A total of 606 radiomics features were extracted. The best performing model on the training set was composed of 8 features including apparent diffusion coefficient mean value, maximum diameter on T1-WIs, and texture features. Area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity on the test set were respectively 0.869 (95% CI, 0.834-0.898), 0.840 (95% CI, 0.806-0.874), 0.684 (95% CI, 0.615-0.751), and 0.935 (95% CI, 0.905-0.961). The radiomics model outperformed all reader groups, including expert neuroradiologists (P < 0.01). Adding clinical and categorizable imaging data did not significantly impact the algorithm performance (P = 0.49).

CONCLUSIONS

An MRI radiomics signature is helpful in differentiating benign from malignant orbital lesions and may outperform expert radiologists.

Pitfalls in diagnosing orbital malignancy through orbital incisional biopsy: A report of two cases with different scenarios

Several methods have been implemented to obtain suitable samples from patients for the purpose of histopathological examination and definitive diagnosis. This has been of paramount importance in dealing with oncology cases including orbital neoplasms. Open surgical biopsy has been the common standard technique used in our eye centers in Saudi Arabia for diagnosing various orbital lesions. Other modalities such as fine-needle aspiration biopsy, core biopsy, and imaging-guided core biopsy are not popular. We report two cases where open surgical biopsies may have not been optimal in reaching the desired tissue diagnosis of orbital malignancy on time, thus resulting in delaying further management of the two patients.

Intravoxel incoherent motion (IVIM) 3 T MRI for orbital lesion characterization

OBJECTIVES

To determine the diagnostic accuracy of MRI intravoxel incoherent motion (IVIM) when characterizing orbital lesions, which is challenging due to a wide range of locations and histologic types.

METHODS

This IRB-approved prospective single-center study enrolled participants presenting with an orbital lesion undergoing a 3-T MRI prior to surgery from December 2015 to July 2019. An IVIM sequence with 15 b values ranging from 0 to 2000 s/mm² was performed. Two neuroradiologists, blinded to clinical data, individually analyzed morphological MRIs. They drew one region of interest inside each orbital lesion, providing apparent diffusion coefficient (ADC), true diffusion coefficient (D), perfusion fraction (f), and pseudodiffusion coefficient (D*) values. T test, Mann-Whitney U test, and receiver operating characteristic curve analyses were performed to discriminate between orbital lesions and to determine the diagnostic accuracy of the IVIM parameters.

RESULTS

One hundred fifty-six participants (84 women and 72 men, mean age 54.4 ± 17.5 years) with 167 orbital lesions (98/167 [59%] benign lesions including 54 orbital inflammations and 69/167 [41%] malignant lesions including 32 lymphomas) were included in the study. ADC and D were significantly lower in malignant than in benign lesions: 0.8 × 10^-3 mm²/s [0.45] versus 1.04 × 10^-3 mm²/s [0.33], p < 0.001, and 0.75 × 10^-3 mm²/s [0.40] versus 0.98 × 10^-3 mm²/s [0.42], p < 0.001, respectively. D* was significantly higher in malignant lesions than in benign ones: 12.8 × 10^-3 mm²/s [20.17] versus 7.52 × 10^-3 mm²/s [7.57], p = 0.005. Area under curve was of 0.73, 0.74, 0.72, and 0.81 for ADC, D, D*, and a combination of D, f, and D*, respectively.

CONCLUSIONS

Our study showed that IVIM might help better characterize orbital lesions.

KEY POINTS

• Intravoxel incoherent motion (IVIM) helps clinicians to assess patients with orbital lesions. • Intravoxel incoherent motion (IVIM) helps clinicians to characterize orbital lymphoma versus orbital inflammation. • Management of patients becomes more appropriate.

Orbital Rosai-Dorfman disease initially diagnosed as IgG4-related disease: a case report

Inflammatory orbital lesions include a broad list of diagnoses, many of them with overlapping clinical and radiographic features. They often present a diagnostic conundrum, even to the most experienced orbital specialist, thus placing considerable weight on surgical biopsy and histopathological analysis. However, histopathological diagnosis is also inherently challenging due to the rarity of these lesions and the overlaps in histologic appearance among distinct disease entities. We herein present the case of an adolescent male with a subacutely progressive orbital mass that generated a significant diagnostic dilemma. Early orbital biopsy was consistent with a benign fibro-inflammatory lesion, but corticosteroid therapy was ineffective in halting disease progression. After an initial substantial surgical debulking, histopathological analysis revealed several key features consistent with IgG4-related disease (IgG4-RD), a systemic fibro-inflammatory process typically accompanied by multifocal tumor-like lesions. Surprisingly, within months, there was clear evidence of clinical and radiographic disease progression despite second-line rituximab treatment, prompting a second surgical debulking. This final specimen displayed distinctive features of Rosai-Dorfman disease (RDD), a systemic inflammatory disease characterized by uncontrolled histiocytic proliferation. Interestingly, certain features of this re-excision specimen were still reminiscent of IgG4-RD, which not only reflects the difficulty in differentiating RDD from IgG4-RD in select cases, but also illustrates that these diagnoses may exist along a spectrum that likely reflects a common underlying pathogenetic mechanism. This case emphasizes the importance of surgical biopsy or resection and histopathological analysis in diagnosing—and, ultimately, treating—rare, systemic inflammatory diseases involving the orbit, and, furthermore, highlights the shared histopathological features between RDD and IgG4-RD.

Diagnosis of orbital mass lesions: clinical, radiological, and pathological recommendations

The orbit can harbor mass lesions of various cellular origins. The symptoms vary considerably according to the nature, location, and extent of the disease and include common signs of proptosis, globe displacement, eyelid swelling, and restricted eye motility. Although radiological imaging tools are improving, with each imaging pattern having its own differential diagnosis, orbital mass lesions often pose a diagnostic challenge. To provide an accurate, specific, and sufficiently comprehensive diagnosis, to optimize clinical management and estimate prognosis, pathological examination of a tissue biopsy is essential. Diagnostic orbital tissue biopsy is obtained through a minimally invasive orbitotomy procedure or, in selected cases, fine needle aspiration. The outcome of successful biopsy, however, is centered on its representativeness, processing, and interpretation. Owing to the often small volume of the orbital biopsies, artifacts in the specimens should be limited by careful peroperative tissue handling, fixation, processing, and storage. Some orbital lesions can be characterized on the basis of cytomorphology alone, whereas others need ancillary molecular testing to render the most reliable diagnosis of therapeutic, prognostic, and predictive value. Herein, we review the diagnostic algorithm for orbital mass lesions, using clinical, radiological, and pathological recommendations, and discuss the methods and potential pitfalls in orbital tissue biopsy acquisition and analysis.