Deep-learning for automated detection of MSU deposits on DECT: evaluating impact on efficiency and reader confidence.

Introduction: Dual-energy CT (DECT) is a non-invasive way to determine the presence of monosodium urate (MSU) crystals in the workup of gout. Color-coding distinguishes MSU from calcium following material decomposition and post-processing. Manually identifying these foci (most commonly labeled green) is tedious, and an automated detection system could streamline the process. This study aims to evaluate the impact of a deep-learning (DL) algorithm developed for detecting green pixelations on DECT on reader time, accuracy, and confidence. Methods: We collected a sample of positive and negative DECTs, reviewed twice-once with and once without the DL tool-with a 2-week washout period. An attending musculoskeletal radiologist and a fellow separately reviewed the cases, simulating clinical workflow. Metrics such as time taken, confidence in diagnosis, and the tool's helpfulness were recorded and statistically analyzed. Results: We included thirty DECTs from different patients. The DL tool significantly reduced the reading time for the trainee radiologist (p = 0.02), but not for the attending radiologist (p = 0.15). Diagnostic confidence remained unchanged for both (p = 0.45). However, the DL model identified tiny MSU deposits that led to a change in diagnosis in two cases for the in-training radiologist and one case for the attending radiologist. In 3/3 of these cases, the diagnosis was correct when using DL. Conclusions: The implementation of the developed DL model slightly reduced reading time for our less experienced reader and led to improved diagnostic accuracy. There was no statistically significant difference in diagnostic confidence when studies were interpreted without and with the DL model.

Staging of breast cancer in the breast and regional lymph nodes using contrast-enhanced photon-counting detector CT: accuracy and potential impact on patient management.

OBJECTIVES: To describe the feasibility and evaluate the performance of multiphasic photon-counting detector (PCD) CT for detecting breast cancer and nodal metastases with correlative dynamic breast MRI and digital mammography as the reference standard. METHODS: Adult females with biopsy-proven breast cancer undergoing staging breast MRI were prospectively recruited to undergo a multiphasic PCD-CT using a 3-phase protocol: a non-contrast ultra-high-resolution (UHR) scan and 2 intravenous contrast-enhanced scans with 50 and 180 s delay. Three breast radiologists compared CT characteristics of the index malignancy, regional lymphadenopathy, and extramammary findings to MRI. RESULTS: Thirteen patients underwent both an MRI and PCD-CT (mean age: 53 years, range: 36-75 years). Eleven of thirteen cases demonstrated suspicious mass or non-mass enhancement on PCD-CT when compared to MRI. All cases with metastatic lymphadenopathy (3/3 cases) demonstrated early avid enhancement similar to the index malignancy. All cases with multifocal or multicentric disease on MRI were also identified on PCD-CT (3/3 cases), including a 4 mm suspicious satellite lesion. Four of five patients with residual suspicious post-biopsy calcifications on mammograms were detected on the UHR PCD-CT scan. Owing to increased field-of-view at PCD-CT, a 5 mm thoracic vertebral metastasis was identified at PCD-CT and not with the breast MRI. CONCLUSIONS: A 3-phase PCD-CT scan protocol shows initial promising results in characterizing breast cancer and regional lymphadenopathy similar to MRI and detects microcalcifications in 80% of cases. ADVANCES IN KNOWLEDGE: UHR and spectral capabilities of PCD-CT may allow for comprehensive characterization of breast cancer and may represent an alternative to breast MRI in select cases.

Glass shards masquerading as calcifications in the breast: A case report.

Noniatrogenically acquired foreign bodies in the nipple-areola complex or breast skin are rare and can have variable imaging features, depending on the nature of the foreign material. We present the case of a 41-year-old female who had numerous apparent round and punctate calcifications in the right periareolar breast, predominantly within the skin. The biopsy showed multiple glass shards on a background of scar tissue. Further discussion with the patient confirmed that the glass shards were acquired during a motor vehicle accident several years earlier. We also review the types of foreign body material observed in the breast, the imaging appearance of glass foreign bodies in soft tissue, and methods of removal.

Adenomyoepithelioma of the Breast: Radiologic-Pathologic Correlation and Management.

Adenomyoepithelioma (AME) is a rare, usually benign breast neoplasm with low potential for malignant transformation. Imaging features are nonspecific and overlap with other benign and malignant breast lesions. On mammography, AME most often presents as a mass, usually oval in shape, with variable reported margins. Less commonly, AME can present mammographically as an asymmetry or can be mammographically occult. Associated calcifications are uncommon. On US, AME is usually seen as a hypoechoic oval mass, but it can also manifest as a complex cystic and solid mass. On US, the majority of AME have noncircumscribed margins (indistinct, angular, or microlobulated). Internal vascularity is usually present, and posterior enhancement can be seen. Although there is limited literature on MRI features, the most frequent finding is an irregular mass with washout kinetics; T2 hyperintensity can be observed. These nonspecific and often suspicious imaging features usually merit biopsy. On histologic analysis, AME is characterized by a biphasic proliferation of myoepithelial and epithelial cells. Pathologic diagnosis can be difficult due to the variety of histologic features of AME and heterogeneity in these tumors, especially when sampling is limited, such as in core needle biopsies. Wide local surgical excision of AME is recommended due to potential for recurrence and malignant transformation.

Trimodality Therapy Improves Disease Control in Radiation-Associated Angiosarcoma of the Breast.

PURPOSE: To evaluate the impact of trimodality treatment versus monotherapy or dual therapy for radiation-associated angiosarcoma of the breast (RAASB) after prior breast cancer treatment. EXPERIMENTAL DESIGN: With Institutional Review Board approval, we identified patients diagnosed with RAASB and abstracted data on disease presentation, treatment, and oncologic outcomes. Trimodality therapy included (i) taxane induction, (ii) concurrent taxane/radiation, and then (iii) surgical resection with wide margins. RESULTS: A total of 38 patients (median age 69 years) met inclusion criteria. Sixteen received trimodality therapy and 22 monotherapy/dual therapy. Skin involvement and disease extent were similar in both groups. All trimodality patients required reconstructive procedures for wound closure/coverage, compared with 48% of monotherapy/dual therapy patients (P < 0.001). Twelve of 16 (75%) patients receiving trimodality therapy had a pathologic complete response (pCR). With median follow-up of 5.6 years, none had local recurrence, 1 patient (6%) had distant recurrence, and no patients died. Among 22 patients in the monotherapy/dual therapy group, 10 (45%) had local recurrence, 8 (36%) had distant recurrence, and 7 (32%) died of disease. Trimodality therapy demonstrated significantly better 5-year recurrence-free survival [RFS; 93.8% vs. 42.9%; P = 0.004; HR, 7.6 (95% confidence interval, CI: 1.3-44.2)]. Combining all patients with RAASB regardless of treatment, local recurrence was associated with subsequent distant recurrence (HR, 9.0; P = 0.002); distant recurrence developed in 3 of 28 (11%) patients without local recurrence compared with 6 of 10 (60%) with local recurrence. The trimodality group had more surgical complications that required reoperation or prolonged healing. CONCLUSIONS: Trimodality therapy for RAASB was more toxic but is promising, with a high rate of pCR, durable local control, and improved RFS.

Seeing More with Less: Clinical Benefits of Photon-counting Detector CT.

Photon-counting detector (PCD) CT is an emerging technology that has led to continued innovation and progress in diagnostic imaging after it was approved by the U.S. Food and Drug Administration for clinical use in September 2021. Conventional energy-integrating detector (EID) CT measures the total energy of x-rays by converting photons to visible light and subsequently using photodiodes to convert visible light to digital signals. In comparison, PCD CT directly records x-ray photons as electric signals, without intermediate conversion to visible light. The benefits of PCD CT systems include improved spatial resolution due to smaller detector pixels, higher iodine image contrast, increased geometric dose efficiency to allow high-resolution imaging, reduced radiation dose for all body parts, multienergy imaging capabilities, and reduced artifacts. To recognize these benefits, diagnostic applications of PCD CT in musculoskeletal, thoracic, neuroradiologic, cardiovascular, and abdominal imaging must be optimized and adapted for specific diagnostic tasks. The diagnostic benefits and clinical applications resulting from PCD CT in early studies have allowed improved visualization of key anatomic structures and radiologist confidence for some diagnostic tasks, which will continue as PCD CT evolves and clinical use and applications grow. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material. See the invited commentary by Ananthakrishnan in this issue.

Clinical applications of photon counting detector CT.

The X-ray detector is a fundamental component of a CT system that determines the image quality and dose efficiency. Until the approval of the first clinical photon-counting-detector (PCD) system in 2021, all clinical CT scanners used scintillating detectors, which do not capture information about individual photons in the two-step detection process. In contrast, PCDs use a one-step process whereby X-ray energy is converted directly into an electrical signal. This preserves information about individual photons such that the numbers of X-ray in different energy ranges can be counted. Primary advantages of PCDs include the absence of electronic noise, improved radiation dose efficiency, increased iodine signal and the ability to use lower doses of iodinated contrast material, and better spatial resolution. PCDs with more than one energy threshold can sort the detected photons into two or more energy bins, making energy-resolved information available for all acquisitions. This allows for material classification or quantitation tasks to be performed in conjunction with high spatial resolution, and in the case of dual-source CT, high pitch, or high temporal resolution acquisitions. Some of the most promising applications of PCD-CT involve imaging of anatomy where exquisite spatial resolution adds clinical value. These include imaging of the inner ear, bones, small blood vessels, heart, and lung. This review describes the clinical benefits observed to date and future directions for this technical advance in CT imaging. KEY POINTS: • Beneficial characteristics of photon-counting detectors include the absence of electronic noise, increased iodine signal-to-noise ratio, improved spatial resolution, and full-time multi-energy imaging. • Promising applications of PCD-CT involve imaging of anatomy where exquisite spatial resolution adds clinical value and applications requiring multi-energy data simultaneous with high spatial and/or temporal resolution. • Future applications of PCD-CT technology may include extremely high spatial resolution tasks, such as the detection of breast micro-calcifications, and quantitative imaging of native tissue types and novel contrast agents.

Breast imaging of infectious disease.

Infectious diseases of the breast can demonstrate a wide variety of clinical presentations and imaging appearances. Breast abscesses are often a complication of infectious mastitis of the breast. Puerperal mastitis is the most common cause of breast abscess, typically affecting postpartum females. Often diagnosed clinically, it is usually treated with antibiotics without need for imaging. Non-puerperal mastitis is relatively uncommon and typically subareolar in location. Patients can present with asymmetric breast thickening, a palpable lump, nipple discharge, or axillary adenopathy. These presentations can mimic malignancy. Herein, this pictorial review demonstrates imaging findings of common and uncommon infectious processes of the breast and clinically important mimickers of breast infection.

Multimodality evaluation of transfascial muscle and other soft tissue herniations of the extremities.

This review illustrates the multimodality assessment of transfascial muscle and other soft tissue herniations of the extremities. Transfascial herniations of the extremities can develop from congenital or acquired disruptions of the deep fascia, resulting in herniation of the underlying muscle, nerve, or soft tissue tumor into the subcutaneous tissues. While most patients present with a painless subcutaneous nodule that may change in size with muscle activation, some may experience focal or diffuse extremity symptoms such as pain and paresthesias. Although the diagnosis may be clinically suspected, radiologic evaluation is useful for definitive diagnosis and characterization. Ultrasound is the preferred modality for initial workup through a focused and dynamic examination. Magnetic resonance imaging can be utilized for equivocal, complicated, and preoperative cases. Computed tomography is less useful in the evaluation of transfascial herniations in the extremities due to similarities in the attenuation between muscle and fascia, which can decrease the conspicuity of small defects.

Photon-counting Detector CT with Deep Learning Noise Reduction to Detect Multiple Myeloma.

Background Photon-counting detector (PCD) CT and deep learning noise reduction may improve spatial resolution at lower radiation doses compared with energy-integrating detector (EID) CT. Purpose To demonstrate the diagnostic impact of improved spatial resolution in whole-body low-dose CT scans for viewing multiple myeloma by using PCD CT with deep learning denoising compared with conventional EID CT. Materials and Methods Between April and July 2021, adult participants who underwent a whole-body EID CT scan were prospectively enrolled and scanned with a PCD CT system in ultra-high-resolution mode at matched radiation dose (8 mSv for an average adult) at an academic medical center. EID CT and PCD CT images were reconstructed with Br44 and Br64 kernels at 2-mm section thickness. PCD CT images were also reconstructed with Br44 and Br76 kernels at 0.6-mm section thickness. The thinner PCD CT images were denoised by using a convolutional neural network. Image quality was objectively quantified in two phantoms and a randomly selected subset of participants (10 participants; median age, 63.5 years; five men). Two radiologists scored PCD CT images relative to EID CT by using a five-point Likert scale to detect findings reflecting multiple myeloma. The scoring for the matched reconstruction series was blinded to scanner type. Reader-averaged scores were tested with the null hypothesis of equivalent visualization between EID and PCD. Results Twenty-seven participants (median age, 68 years; IQR, 61-72 years; 16 men) were included. The blinded assessment of 2-mm images demonstrated improvement in viewing lytic lesions, intramedullary lesions, fatty metamorphosis, and pathologic fractures for PCD CT versus EID CT (P < .05 for all comparisons). The 0.6-mm PCD CT images with convolutional neural network denoising also demonstrated improvement in viewing all four pathologic abnormalities and detected one or more lytic lesions in 21 of 27 participants compared with the 2-mm EID CT images (P < .001). Conclusion Ultra-high-resolution photon-counting detector CT improved the visibility of multiple myeloma lesions relative to energy-integrating detector CT. © RSNA, 2022 Online supplemental material is available for this article.

Photon-Counting Detector CT for Musculoskeletal Imaging: A Clinical Perspective.

Photon-counting detector (PCD) CT has emerged as a novel imaging modality that represents a fundamental shift in the way that CT systems detect x-rays. After pre-clinical and clinical investigations showed benefits of PCD CT for a range of imaging tasks, the U.S. FDA in 2021 approved the first commercial PCD CT system for clinical use. The technologic features of PCD CT are particularly well suited for musculo-skeletal imaging applications. Advantages of PCD CT compared with conventional energy-integrating detector (EID) CT include smaller detector pixels and excellent geometric dose efficiency that enable imaging of large joints and central skeletal anatomy at ultrahigh spatial resolution; advanced multienergy spectral postprocessing that allows quantification of gout deposits and generation of virtual noncalcium images for visualization of bone edema; improved metal artifact reduction for imaging of orthopedic implants; and higher CNR and suppression of electronic noise. Given substantially improved cortical and trabecular detail, PCD CT images more clearly depict skeletal abnormalities, including fractures, lytic lesions, and mineralized tumor matrix. The purpose of this article is to review, by use of clinical examples comparing EID CT and PCD CT, the technical features of PCD CT and their associated impact on musculoskeletal imaging applications.

Radiation-associated angiosarcoma of the breast with initial presentation as non-mass enhancement on MRI.

Radiation-associated angiosarcoma of the breast (RAASB) is a rare and aggressive malignancy occurring after radiation therapy as part of breast cancer treatment. RAASB usually presents several years after prior radiation and typically involves the skin with or without involvement of the parenchyma. Most RAASB are detected as cutaneous changes on physical exam. Herein, we present a unique case of a clinically occult RAASB diagnosed as non-mass enhancement on annual surveillance breast MRI.

Dedicated convolutional neural network for noise reduction in ultra-high-resolution photon-counting detector computed tomography.

Objective.To develop a convolutional neural network (CNN) noise reduction technique for ultra-high-resolution photon-counting detector computed tomography (UHR-PCD-CT) that can be efficiently implemented using only clinically available reconstructed images. The developed technique was demonstrated for skeletal survey, lung screening, and head angiography (CTA).Approach. There were 39 participants enrolled in this study, each received a UHR-PCD and an energy integrating detector (EID) CT scan. The developed CNN noise reduction technique uses image-based noise insertion and UHR-PCD-CT images to train a U-Net via supervised learning. For each application, 13 patient scans were reconstructed using filtered back projection (FBP) and iterative reconstruction (IR) and allocated into training, validation, and testing datasets (9:1:3). The subtraction of FBP and IR images resulted in approximately noise-only images. The 5-slice average of IR produced a thick reference image. The CNN training input consisted of thick reference images with reinsertion of spatially decoupled noise-only images. The training target consisted of the corresponding thick reference images without noise insertion. Performance was evaluated based on difference images, line profiles, noise measurements, nonlinear perturbation assessment, and radiologist visual assessment. UHR-PCD-CT images were compared with EID images (clinical standard).Main results.Up to 89% noise reduction was achieved using the proposed CNN. Nonlinear perturbation assessment indicated reasonable retention of 1 mm radius and 1000 HU contrast signals (>80% for skeletal survey and head CTA, >50% for lung screening). A contour plot indicated reduced retention for small-radius and low contrast perturbations. Radiologists preferred CNN over IR for UHR-PCD-CT noise reduction. Additionally, UHR-PCD-CT with CNN was preferred over standard resolution EID-CT images.Significance.CT images reconstructed with very sharp kernels and/or thin sections suffer from increased image noise. Deep learning noise reduction can be used to offset noise level and increase utility of UHR-PCD-CT images.

Deep learning-based virtual noncalcium imaging in multiple myeloma using dual-energy CT.

BACKGROUND: Dual-energy CT with virtual noncalcium (VNCa) images allows the evaluation of focal intramedullary bone marrow involvement in patients with multiple myeloma. However, current commercial VNCa techniques suffer from excessive image noise and artifacts due to material decomposition used in synthesizing VNCa images. OBJECTIVES: In this work, we aim to improve VNCa image quality for the assessment of focal multiple myeloma, using an Artificial intelligence based Generalizable Algorithm for mulTi-Energy CT (AGATE) method. MATERIALS AND METHODS: AGATE method used a custom dual-task convolutional neural network (CNN) that concurrently carries out material classification and quantification. The material classification task provided an auxiliary regularization to the material quantification task. CNN parameters were optimized using custom loss functions that involved cross-entropy, physics-informed constraints, structural redundancy in spectral and material images, and texture information in spectral images. For training data, CT phantoms (diameters 30 to 45 cm) with tissue-mimicking inserts were scanned on a third generation dual-source CT system. Scans were performed at routine dose and half of the routine dose. Small image patches (i.e., 40 × 40 pixels) of tissue-mimicking inserts with known basis material densities were extracted for training samples. Numerically simulated insert materials with various shapes increased diversity of training samples. Generalizability of AGATE was evaluated using CT images from phantoms and patients. In phantoms, material decomposition accuracy was estimated using mean-absolute-percent-error (MAPE), using physical inserts that were not used during the training. Noise power spectrum (NPS) and modulation transfer function (MTF) were compared across phantom sizes and radiation dose levels. Five patients with multiple myeloma underwent dual-energy CT, with VNCa images generated using a commercial method and AGATE. Two fellowship-trained musculoskeletal radiologists reviewed the VNCa images (commercial and AGATE) side-by-side using a dual-monitor display, blinded to VNCa type, rating the image quality for focal multiple myeloma lesion visualization using a 5-level Likert comparison scale (-2 = worse visualization and diagnostic confidence, -1 = worse visualization but equivalent diagnostic confidence, 0 = equivalent visualization and diagnostic confidence, 1 = improved visualization but equivalent diagnostic confidence, 2 = improved visualization and diagnostic confidence). A post hoc assignment of comparison ratings was performed to rank AGATE images in comparison to commercial ones. RESULTS: AGATE demonstrated consistent material quantification accuracy across phantom sizes and radiation dose levels, with MAPE ranging from 0.7% to 4.4% across all testing materials. Compared to commercial VNCa images, the AGATE-synthesized VNCa images yielded considerably lower image noise (50-77% noise reduction) without compromising noise texture or spatial resolution across different phantom sizes and two radiation doses. AGATE VNCa images had markedly reduced area under NPS curves and maintained NPS peak frequency (0.7 lp/cm to 1.0 lp/cm), with similar MTF curves (50% MTF at 3.0 lp/cm). In patients, AGATE demonstrated reduced image noise and artifacts with improved delineation of focal multiple myeloma lesions (all readers comparison scores indicating improved overall diagnostic image quality [scores 1 or 2]). CONCLUSIONS: AGATE demonstrated reduced noise and artifacts in VNCa images and ability to improve visualization of bone marrow lesions for assessing multiple myeloma.

Ultra-high-resolution imaging of the shoulder and pelvis using photon-counting-detector CT: a feasibility study in patients.

OBJECTIVE: To evaluate ultra-high-resolution (UHR) imaging of large joints using an investigational photon-counting detector (PCD) CT. MATERIALS AND METHODS: Patients undergoing clinical shoulder or pelvis energy-integrating-detector (EID) CT exam were scanned using the UHR mode of the PCD-CT system. Axial EID-CT images (1-mm sections) and PCD-CT images (0.6-mm sections) were reconstructed using Br62/Br64 and Br76 kernels, respectively. Two musculoskeletal radiologists rated visualization of anatomic structures using a 5-point Likert scale. Wilcoxon rank-sum test was used for statistical analysis of reader scores, and paired t-test was used for comparing bone CT numbers and image noise from PCD-CT and EID-CT. RESULTS: Thirty-two patients (17 shoulders and 15 pelvis) were prospectively recruited for this feasibility study. Mean age for shoulder exams was 67.3 ± 15.5 years (11 females) and 47.2 ± 15.8 years (11 females) for pelvis exams. The mean volume CT dose index was lower on PCD-CT compared to that on EID-CT (shoulders: 18 mGy vs. 34 mGy, pelvis: 11.6 mGy vs. 16.7 mGy). PCD-CT was rated significantly better than EID-CT (p < 0.001) for anatomic-structure visualization. Trabecular delineation in shoulders (mean score = 4.24 ± 0.73) and femoroacetabular joint visualization in the pelvis (mean score = 3.67 ± 1.03) received the highest scores. PCD-CT demonstrated significant increase in bone CT number (p < 0.001) relative to EID-CT; no significant difference in image noise was found between PCD-CT and EID-CT. CONCLUSION: The evaluated PCD-CT system provided improved visualization of osseous structures in the shoulders and pelvises at a 31-47% lower radiation dose compared to EID-CT. KEY POINTS: • A full field-of-view PCD-CT with 0.151 mm × 0.176 mm detector pixel size (isocenter) facilitates bilateral, high-resolution imaging of shoulders and pelvis. • The evaluated investigational PCD-CT system was rated superior by two musculoskeletal radiologists for anatomic structure visualization in shoulders and pelvises despite a 31-47% lower radiation dose compared to EID-CT. • PCD-CT demonstrated significantly higher bone CT number compared to EID-CT, while no significant difference in image noise was observed between PCD-CT and EID-CT despite a 31-47% dose reduction on PCD-CT.

Imaging features of adenosquamous carcinoma of the breast - A rare variant of metaplastic breast carcinoma.

Adenosquamous carcinoma of the breast is a rare subtype of metaplastic carcinoma, which accounts for <1% of invasive breast malignancy. Metaplastic carcinoma is usually high grade and aggressive with typically reported benign imaging features when compared to invasive ductal carcinoma. However, the adenosquamous variant is a subtype with a more favorable prognosis. Within the literature, there is limited imaging description with case studies focusing on metaplastic carcinoma. Herein, we report seven cases of the adenosquamous subtype describing the imaging findings with correlation to clinical history and pathology. The majority of patients (n = 6) presented with palpable breast masses. One patient was identified through screening mammography. Mammographically (n = 6), tumors appeared as irregular masses. Sonographically (n = 7), tumors appeared as irregular masses ranging from solid to mixed solid/cystic masses. On MRI (n = 1), one tumor appeared as an irregular rim enhancing mass. FDG PET/CT (n = 2) and whole-body bone scan (n = 1) were also available for review. The majority of tumors were low-grade (n = 6) with only one high-grade tumor. This case series of seven patients demonstrated predominantly suspicious imaging features despite the majority being low-grade tumors.

Evolving Role of Dual-Energy CT in the Clinical Workup of Gout: A Retrospective Study.

BACKGROUND. Dual-energy CT (DECT) allows noninvasive detection of monosodium urate (MSU) crystal deposits and has become incorporated into the routine clinical evaluation for gout at many institutions over the past decade. OBJECTIVE. The purpose of this study was to compare two time periods over the past decade in terms of radiologists' interpretations of DECT examinations performed for the evaluation of gout and subsequent clinical actions. METHODS. This retrospective study included 100 consecutive adult patients who underwent DECT to evaluate for gout in each of two periods (one beginning in March 2013 and one beginning in September 2019). Examinations performed in 2013 were conducted using a second-generation DECT scanner (80 kV [tube A] and 140 kV [tube B] with a 0.4-mm tin filter), and those performed in 2019 were conducted using a third-generation DECT scanner (80 kV [tube A] and 150 kV [tube B] with a 0.6-mm tin filter) that provides improved spectral separation. Original DECT reports were classified as positive, negative, or equivocal for MSU crystals indicative of gout. Joint aspirations occurring after the DECT examinations were recorded on the basis of findings from medical record review. A single radiologist performed a post hoc retrospective blinded image review, classifying examinations as positive, negative, or equivocal. RESULTS. In 2013, 44.0% of DECT examinations were interpreted as positive, 23.0% as negative, and 33.0% as equivocal; in 2019, 37.0% were interpreted as positive, 47.0% as negative, and 16.0% as equivocal (p < .001). The frequency of joint aspiration after DECT was 14.0% in 2013 versus 2.0% in 2019 (p = .002), and that after DECT examinations with negative interpretations was 17.4% in 2013 versus 2.1% in 2019 (p = .02). In post hoc assessment by a single radiologist, the distribution of interpretations in 2013 was positive in 49.0%, negative in 22.0%, and equivocal in 29.0%, and in 2019 it was positive in 39.0%, negative in 50.0%, and equivocal in 11.0% (p < .001). CONCLUSION. When DECT examinations performed for gout in 2013 and 2019 were compared, the frequency of equivocal interpretations was significantly lower in 2019, possibly in relation to interval technologic improvements. Negative examinations were less frequently followed by joint aspirations in 2019, possibly reflecting increasing clinical acceptance of the DECT results. CLINICAL IMPACT. The findings indicate an evolving role for DECT in the evaluation of gout after an institution's routine adoption of the technology for this purpose.

Preoperative ultrasound accurately characterizes surgically confirmed extracranial spinal accessory nerve injuries.

OBJECTIVE: To determine the accuracy of preoperative ultrasound and MRI in surgically confirmed spinal accessory nerve injuries and present the benefits of a multimodality image review. MATERIALS AND METHODS: A retrospective review of 38 consecutive patients referred to a peripheral nerve surgical practice at an academic teaching hospital with surgically confirmed spinal accessory nerve injuries. All cases were reviewed for patient demographics, date and cause of injury, preoperative EMG, and surgical diagnosis and management. Additionally, prospective interpretation of preoperative ultrasound and MRI reports were reviewed for concordance or discordance with the surgical diagnosis. RESULTS: Iatrogenic injury was present in 37 (97%) cases and most commonly a result of an excisional lymph node biopsy (68%). Surgically confirmed spinal accessory nerve injury diagnoses consisted of 25 (66%) stump neuromas and 13 (34%) incomplete nerve injuries. Nine months was the average time from injury to surgery. Twenty-nine patients underwent preoperative ultrasound and/or MRI evaluation: 12 ultrasound only, 10 MRI only, and seven with both ultrasound and MRI. Eighteen (95%) preoperative ultrasound reports compared to four (24%) preoperative MRI reports were concordant with the surgical diagnosis. In the seven cases with both preoperative ultrasound and MRI, six had discordant ultrasound and MRI imaging diagnoses for which the ultrasound was concordant with the surgical diagnoses in all cases. CONCLUSION: Preoperative ultrasound more accurately characterizes spinal accessory nerve injuries compared to MRI and should serve as the modality of choice when a spinal accessory nerve injury is suspected.

Clinical evaluation of a phantom-based deep convolutional neural network for whole-body-low-dose and ultra-low-dose CT skeletal surveys.

OBJECTIVE: This study evaluated the clinical utility of a phantom-based convolutional neural network noise reduction framework for whole-body-low-dose CT skeletal surveys. MATERIALS AND METHODS: The CT exams of ten patients with multiple myeloma were retrospectively analyzed. Exams were acquired with routine whole-body-low-dose CT protocol and projection noise insertion was used to simulate 25% dose exams. Images were reconstructed with either iterative reconstruction or filtered back projection with convolutional neural network post-processing. Diagnostic quality and structure visualization were blindly rated (subjective scale ranging from 0 [poor] to 100 [excellent]) by three musculoskeletal radiologists for iterative reconstruction and convolutional neural network images at routine whole-body-low-dose and 25% dose CT. RESULTS: For the diagnostic quality rating, the convolutional neural network outscored iterative reconstruction at routine whole-body-low-dose CT (convolutional neural network: 95 ± 5, iterative reconstruction: 85 ± 8) and at the 25% dose level (convolutional neural network: 79 ± 10, iterative reconstruction: 22 ± 13). Convolutional neural network applied to 25% dose was rated inferior to iterative reconstruction applied to routine dose. Similar trends were observed in rating experiments focusing on structure visualization. CONCLUSION: Results indicate that the phantom-based convolutional neural network noise reduction framework can improve visualization of critical structures within CT skeletal surveys. At matched dose level, the convolutional neural network outscored iterative reconstruction for all conditions studied. The image quality improvement of convolutional neural network applied to 25% dose indicates a potential for dose reduction; however, the 75% dose reduction condition studied is not currently recommended for clinical implementation.