Using the 3-tiered system for categorizing workup of incidental thyroid nodules detected on CT, MRI, or PET/CT: how many cancers would be missed?

BACKGROUND: A 3-tiered system has been proposed by radiologists for the reporting and workup of incidental thyroid nodules (ITN) detected on computed tomography (CT), magnetic resonance imaging (MRI), or positron emission tomography/computed tomography (PET/CT). It has been shown to reduce the workup rate, but there remains concern about missed malignancies. This study aims at estimating the proportion of incidental cancers that would be missed relative to all thyroid cancers if the 3-tiered system were applied to ITN seen on CT, MRI, or PET/CT. We also aim to characterize these missed incidental cancers by histology and tumor stage. METHODS: A retrospective review was performed of 680 consecutive patients with thyroid cancer who underwent surgery between January 2003 and December 2012. Medical records were reviewed to identify incidental thyroid cancers detected on imaging. Patients with incidental cancers detected on CT, MRI, or PET/CT were categorized according to the system as 3-tiered system-positive and 3-tiered system-negative. The system recommends that only 3-tiered system-positive ITN undergo further workup with ultrasound. Three-tiered system-negative cancers were the cancers that would have been missed if the system were used in practice. These tumors are described by tumor type, size, and stage to determine the potential impact if the 3-tiered system were adopted. RESULTS: One hundred and one patients had imaging-detected incidental cancers, of whom 64 met the inclusion criteria and were originally detected on CT, MRI, or PET/CT. Eight were 3-tiered system-negative, which represents 13% of the 64 incidental cancers that could be categorized and 1.2% of all thyroid cancers treated at our institution in the 10-year period. Three-tiered system-negative tumors were all papillary in histology and had a median size of 12 mm (interquartile range 10-12 mm). Six tumors (75%) were American Joint Committee on Cancer (AJCC) stage I, one was AJCC stage II, and one was AJCC stage III at diagnosis. CONCLUSIONS: Based on thyroid cancers diagnosed during a decade, incidental malignancies missed by the 3-tiered system represent 1.2% of all thyroid malignancies. Three-tiered system-negative incidental cancers were all small papillary cancers. Given that few cancers would be missed and most are less aggressive, we propose that the 3-tiered system could be adopted in clinical practice to guide the workup of ITN identified on CT, MRI, and PET/CT.

Computer-extracted MR imaging features are associated with survival in glioblastoma patients.

Automatic survival prognosis in glioblastoma (GBM) could result in improved treatment planning for the patient. The purpose of this research is to investigate the association of survival in GBM patients with tumor features in pre-operative magnetic resonance (MR) images assessed using a fully automatic computer algorithm. MR imaging data for 68 patients from two US institutions were used in this study. The images were obtained from the Cancer Imaging Archive. A fully automatic computer vision algorithm was applied to segment the images and extract eight imaging features from the MRI studies. The features included tumor side, proportion of enhancing tumor, proportion of necrosis, T1/FLAIR ratio, major axis length, minor axis length, tumor volume, and thickness of enhancing margin. We constructed a multivariate Cox proportional hazards regression model and used a likelihood ratio test to establish whether the imaging features are prognostic of survival. We also evaluated the individual prognostic value of each feature through multivariate analysis using the multivariate Cox model and univariate analysis using univariate Cox models for each feature. We found that the automatically extracted imaging features were predictive of survival (p = 0.031). Multivariate analysis of individual features showed that two individual features were predictive of survival: proportion of enhancing tumor (p = 0.013), and major axis length (p = 0.026). Univariate analysis indicated the same two features as significant (p = 0.021, and p = 0.017 respectively). We conclude that computer-extracted MR imaging features can be used for survival prognosis in GBM patients.

A fully automatic extraction of magnetic resonance image features in glioblastoma patients.

PURPOSE: Glioblastoma is the most common malignant brain tumor. It is characterized by low median survival time and high survival variability. Survival prognosis for glioblastoma is very important for optimized treatment planning. Imaging features observed in magnetic resonance (MR) images were shown to be a good predictor of survival. However, manual assessment of MR features is time-consuming and can be associated with a high inter-reader variability as well as inaccuracies in the assessment. In response to this limitation, the authors proposed and evaluated a computer algorithm that extracts important MR image features in a fully automatic manner. METHODS: The algorithm first automatically segmented the available volumes into a background region and four tumor regions. Then, it extracted ten features from the segmented MR imaging volumes, some of which were previously indicated as predictive of clinical outcomes. To evaluate the algorithm, the authors compared the extracted features for 73 glioblastoma patients to the reference standard established by manual segmentation of the tumors. RESULTS: The experiments showed that their algorithm was able to extract most of the image features with moderate to high accuracy. High correlation coefficients between the automatically extracted value and reference standard were observed for the tumor location, minor and major axis length as well as tumor volume. Moderately high correlation coefficients were also observed for proportion of enhancing tumor, proportion of necrosis, and thickness of enhancing margin. The correlation coefficients for all these features were statistically significant (p < 0.0001). CONCLUSIONS: The authors proposed and evaluated an algorithm that, given a set of MR volumes of a glioblastoma patient, is able to extract MR image features that correlate well with their reference standard. Future studies will evaluate how well the computer-extracted features predict survival.

Applying the Society of Radiologists in Ultrasound recommendations for fine-needle aspiration of thyroid nodules: effect on workup and malignancy detection.

OBJECTIVE: The Society of Radiologists in Ultrasound (SRU) recommendations on thyroid nodules are intended to "diagnose thyroid cancers that have reached clinical significance, while avoiding unnecessary tests and surgery in patients with benign nodules." The aim of our study was to determine the proportion of thyroid nodules undergoing ultrasound-guided fine-needle aspiration (FNA) that do not meet SRU recommendations. MATERIALS AND METHODS: This study is a retrospective study of 400 consecutive ultrasound-guided thyroid FNA encounters from July 2010 through June 2011. An encounter was defined as presentation to the department of radiology on a given date for FNA of one or more thyroid nodules. The criteria for performing biopsy of a nodule were determined by the referring clinicians. Nodules were categorized on the basis of sonographic findings as meeting SRU recommendations for biopsy, which we refer to as "SRU-positive," or not, which we refer to as "SRU-negative." Patients without a definitive pathology diagnosis of Bethesda class benign or malignant nodules were excluded. The characteristics of malignancies were compared for SRU-positive and SRU-negative encounters. RESULTS: The final study group consisted of 360 biopsy encounters for 350 patients and 29 malignancies (8%). Of the 360 biopsy encounters, 86 (24%) were SRU-negative encounters. Malignancy rates in SRU-positive and SRU-negative encounters were 9% (24/274) and 6% (5/86), respectively, and were not significantly different (p=0.5). Eighteen malignancies (75%) in the SRU-positive group were localized, whereas the others had nodal metastases (4/24) or distant metastases (2/24). SRU-positive encounters included medullary carcinoma, anaplastic carcinoma, and melanoma metastasis in addition to papillary carcinoma. All SRU-negative malignancies were localized papillary carcinomas. CONCLUSION: One in four thyroid biopsy encounters at our institution did not meet SRU recommendations for biopsy. The application of SRU recommendations reduces the number of benign nodules that undergo workup. Potentially missed malignancies in SRU-negative nodules are less aggressive by histologic type and stage compared with SRU-positive malignancies.

Thyroid cancers incidentally detected at imaging in a 10-year period: how many cancers would be missed with use of the recommendations from the Society of Radiologists in Ultrasound?

PURPOSE: To estimate the prevalence of incidental thyroid cancer (ITC) among patients undergoing thyroid surgery and to apply the Society of Radiologists in Ultrasound (SRU) guidelines to ITC. MATERIALS AND METHODS: This HIPAA-compliant study was approved by the institutional review board, with waiver of the need to obtain informed consent. A retrospective review of data in patients who underwent thyroid surgery between January 1, 2003, and December 31, 2012, was performed. Imaging studies and reports were reviewed for ITCs that were first detected at either ultrasonography (US) or a different imaging modality and that included US as part of the work-up. ITCs were categorized by using the SRU guidelines to determine the characteristics of SRU criteria-positive and SRU criteria-negative malignancies. Patient demographic data, tumor histologic findings, tumor size, and tumor stage were compared for the SRU criteria-positive and SRU criteria-negative cancers by using the unpaired t test and the χ(2) test. RESULTS: Among 2090 patients who underwent thyroid surgery, 680 had thyroid cancer; of these patients, 101 (15%) had imaging-detected ITC. The SRU recommendations were applied to the findings in 90 of the 101 patients who had undergone US with images or had reports available for review. Sixteen (18%) of the 90 patients had SRU criteria-negative tumors, which represented 2% (16 of 680) of all thyroid cancers. SRU criteria-negative tumors were smaller than SRU criteria-positive tumors (mean, 1.1 cm [range, 0.9-1.4 cm] vs mean, 2.5 cm [range, 1.0-7.6 cm]; P < .001) and were more likely to be stage I (15 [94%] of 16 vs 47 [64%] of 74; P = .02). CONCLUSION: Imaging-detected ITCs are uncommon. Two percent (16 of 680) of malignancies would not undergo fine-needle aspiration biopsy or surgery if the SRU guidelines were used for work-up of incidental thyroid nodules. SRU criteria-negative tumors are lower in stage than SRU criteria-positive tumors.

Journal Club: incidental thyroid nodules detected at imaging: can diagnostic workup be reduced by use of the Society of Radiologists in Ultrasound recommendations and the three-tiered system?

OBJECTIVE: The purpose of this study was to determine the number of thyroid nodule workups that could be eliminated and the number of malignant tumors that would be missed if the Society of Radiologists in Ultrasound (SRU) recommendations and the three-tiered system were applied to incidental thyroid nodules (ITN) detected at imaging. MATERIALS AND METHODS: This retrospective study included ITN in 390 consecutively registered patients who underwent ultrasound-guided fine-needle aspiration of one or more thyroid nodules from July 2010 to June 2011. Images were reviewed, and nodules were categorized according to two workup criteria: ITN seen on ultrasound images were categorized according to SRU recommendations, and those seen on CT, MR, or PET/CT images were classified according to the three-tiered risk-categorization system. RESULTS: In this study 114 of 390 (29%) patients had nodules first detected incidentally during imaging studies, and 107 patients met the inclusion criteria. These patients had 47 ITN seen at ultrasound and 60 ITN seen at either CT, MRI, or PET/CT. If the SRU recommendations had been applied, 14 of 47 (30%) patients with ITN on ultrasound images would not have received fine-needle aspiration and one of four cases of cancer would have been missed. The missed malignant tumor was a 14-mm localized papillary carcinoma. If the three-tiered system had been applied, 21 of 60 (35%) patients with ITN on CT, MR, or PET/CT images would not have received fine-needle aspiration, but none of the three malignancies would have been missed. Overall, 35 of 107 (33%) of patients with ITN did not meet the SRU recommendations or the three-tiered criteria. CONCLUSION: Use of the SRU recommendations and three-tiered system can reduce the workup of ITN by one third compared with current practice without specific guidelines. One case of localized papillary carcinoma was missed when the SRU recommendations were used.