Series Of CT Images Research Articles

Dynamic change of COVID-19 lung infection evaluated using co-registration of serial chest CT images.

PurposeTo evaluate the volumetric change of COVID-19 lesions in the lung of patients receiving serial CT imaging for monitoring the evolution of the disease and the response to treatment.Materials and methodsA total of 48 patients, 28 males and 20 females, who were confirmed to have COVID-19 infection and received chest CT examination, were identified. The age range was 21–93 years old, with a mean of 54 ± 18 years. Of them, 33 patients received the first follow-up (F/U) scan, 29 patients received the second F/U scan, and 11 patients received the third F/U scan. The lesion region of interest (ROI) was manually outlined. A two-step registration method, first using the Affine alignment, followed by the non-rigid Demons algorithm, was developed to match the lung areas on the baseline and F/U images. The baseline lesion ROI was mapped to the F/U images using the obtained geometric transformation matrix, and the radiologist outlined the lesion ROI on F/U CT again.ResultsThe median (interquartile range) lesion volume (cm3) was 30.9 (83.1) at baseline CT exam, 18.3 (43.9) at first F/U, 7.6 (18.9) at second F/U, and 0.6 (19.1) at third F/U, which showed a significant trend of decrease with time. The two-step registration could significantly decrease the mean squared error (MSE) between baseline and F/U images with p < 0.001. The method could match the lung areas and the large vessels inside the lung. When using the mapped baseline ROIs as references, the second-look ROI drawing showed a significantly increased volume, p < 0.05, presumably due to the consideration of all the infected areas at baseline.ConclusionThe results suggest that the registration method can be applied to assist in the evaluation of longitudinal changes of COVID-19 lesions on chest CT.

Measure of Frontal Morphology in Sagittal Craniosynostosis: The Frontal Bossing Index

Background: Frontal bossing is a prominent forehead feature common in sagittal craniosynostosis (SC). Assessment of severity of frontal bossing is limited by the use of serial CT imaging or complex computer programing. Three-dimensional measurements of cranial surface morphology provide a radiation-free alternative for assessing cranial shape. This study describes the creation of a frontal bossing index (FBI), a novel tool using surface morphology to assess the frontal severity in patients with SC. Methods: Surface imaging from CT scans or 3D photographs of 359 individuals with sagittal craniosynostosis and 224 normocephalic individuals were compared to identify differences in frontal morphology. Cartesian grids were created on each individual’s surface mesh using equidistant axial and sagittal planes yielding 33 unique points of intersection on the forehead. Area under the curve (AUC) analyses were performed to identify frontal points with the greatest discrepancy between groups. Results: All points in the SC population had significantly greater protrusion than corresponding points in the control group. The largest differences were located in the superior lateral regions. Combining the superior- and lateral-most points gave the maximal AUC (0.9707) and was therefore selected to generate the frontal bossing index (FBI). The FBI distinguished between the 2 groups with a sensitivity of 93.5% and specificity of 92.9%. Conclusions: The frontal bossing index is a useful tool for evaluating the severity of the frontal region in patients with SC, comparing outcomes of differing surgical techniques, and tracking frontal changes in individuals over time, without the need for radiation.

Serial CT Images of Annulus Rupture Treated by Conservative Strategy After Transcatheter Aortic Valve Replacement.

Serial CT Images of Annulus Rupture Treated by Conservative Strategy After Transcatheter Aortic Valve Replacement.

New insights into the fracture evolution and instability warning predication for fissure-contained hollow-cylinder granite with different hole diameter under multi-stage cyclic loads

This work aims to investigate the fracture evolution and instability warning predication for the fissure-contained hollow-cylinder granite exposed to multi-stage cyclic loads. The influence of the hollow hole diameter on rock fracture was experimentally investigated in terms of deformation, hysteresis damping effects, energy conversion, and failure modes. The testing results show that the fracture of rock is impacted by the communication of the hole and fissure, and the fracture at the rock bridge segment leads to the final instability. The instability waring, i.e., obvious dilatancy initiation, was predicted using volumetric deformation, strain rate, hysteresis damping, and energy rate, it is suggested that an early warning can be realized from the dissipated energy rate. Rock damage is quantificationally characterized by the dissipated energy, and a damage evolution model is proposed that exhibits good performance to fit the testing data. A series of CT images highlight the fracture of rock bridge segment and good agreement was found between the energy evolution and failure patterns.

A multiple organ segmentation system for CT image series using Attention-LSTM fused U-Net

A multiple organ segmentation system for CT image series using Attention-LSTM fused U-Net

Does Single Computed Tomography Attenuation Correction able to Surrogate Serial Computed Tomography Attenuation Correction in Single-Photon Emission Computed Therapy Imaging for Peptide Receptor Radionuclide Therapy Dosimetry Result?

Peptide Receptor Radionuclide Therapy (PRRT) is the administration of a radionuclide, such as the Lu-177 label, along with a pharmaceutical agent to destroy the lesion cell. The first cycle of Lu-177 DOTA-TATE is an excellent way to estimate radionuclide uptake for organs at risk. To estimate the absorbed dose for a kidney, serial SPECT-CT imaging with up to five sets is required. In general, serial CT on patients would result in additional external exposure and extra time consuming, especially for low dose CT such as cone beam CT technology. However, by introducing a new method, such as optimized single CT (24 h) to perform with serial SPECT attenuation correction, additional external exposure from serial CT exposure could be reduced.Aims:The purpose of this study is to assess the agreement between single CT scanning as CT attenuation Correction with serial CT scanning for serial SPECT imaging as well as estimated absorbed dose to the organ at risk.Settings and Design:During the first cycle of Lu177-DOTA-TATE, all patients should undergo internal dosimetry technique using SPECT-CT imaging with a PHILIP Brightview XCT gamma camera. The quantifications of SPECT images are being used to measure the uptake activity to the organ. In this investigation, Partik's categorical grading criteria are being used to convert the numeric value of Lin's concordance coefficient into an ordinal scale.Method:Total of 9 patients at our institution was administered with Lu177-DOTA-TATE enroll in this study. SPECT-CT data were acquired using automatic body contouring with a total of 48 angular views at steps of 6° (15 s/projections). The pixel size is 4.66 x 4.66 x 4.66 mm, the images size set to one, and SPECT data has been acquired for three-bed positions extending from the abdomen to the thorax region. Low-dose CT imaging performed at an X-ray tube voltage of 120 kVp.Results:Our current result demonstrated by single CT scanning for SPECT attenuation shown the excellent agreement with standard serial CT imaging for organs at risk such as kidney 0.999, spleen 0.9951, liver 0.9951 and bladder 0.9972.Conclusions:When compared to the previous method, patients benefit significantly more from this study, such as lower CT exposure.

Weakly-supervised lesion analysis with a CNN-based framework for COVID-19

Objective. Lesions of COVID-19 can be clearly visualized using chest CT images, and hence provide valuable evidence for clinicians when making a diagnosis. However, due to the variety of COVID-19 lesions and the complexity of the manual delineation procedure, automatic analysis of lesions with unknown and diverse types from a CT image remains a challenging task. In this paper we propose a weakly-supervised framework for this task requiring only a series of normal and abnormal CT images without the need for annotations of the specific locations and types of lesions. Approach. A deep learning-based diagnosis branch is employed for classification of the CT image and then a lesion identification branch is leveraged to capture multiple types of lesions. Main Results. Our framework is verified on publicly available datasets and CT data collected from 13 patients of the First Affiliated Hospital of Shantou University Medical College, China. The results show that the proposed framework can achieve state-of-the-art diagnosis prediction, and the extracted lesion features are capable of distinguishing between lesions showing ground glass opacity and consolidation. Significance. The proposed approach integrates COVID-19 positive diagnosis and lesion analysis into a unified framework without extra pixel-wise supervision. Further exploration also demonstrates that this framework has the potential to discover lesion types that have not been reported and can potentially be generalized to lesion detection of other chest-based diseases.

A Convolutional Neural Network Approach to Quantify Lung Disease Progression in Patients with Fibrotic Hypersensitivity Pneumonitis (HP)

Rationale and Objectives To evaluate associations between longitudinal changes of quantitative CT parameters and spirometry in patients with fibrotic hypersensitivity pneumonitis (HP). Materials and Methods Serial CT images and spirometric data were retrospectively collected in a group of 25 fibrotic HP patients. Quantitative CT analysis included histogram parameters (median, interquartile range, skewness, and kurtosis) and a pretrained convolutional neural network (CNN)-based textural analysis, aimed at quantifying the extent of consolidation (C), fibrosis (F), ground-glass opacity (GGO), low attenuation areas (LAA) and healthy tissue (H). Results At baseline, FVC was 61(44-70) %pred. The median follow-up period was 1.4(0.8-3.2) years, with 3(2-4) visits per patient. Over the study, 8 patients (32%) showed a FVC decline of more than 5%, a significant worsening of all histogram parameters (p≤0.015) and an increased extent of fibrosis via CNN (p=0.038). On histogram analysis, decreased skewness and kurtosis were the parameters most strongly associated with worsened FVC (respectively, r2=0.63 and r2=0.54, p<0.001). On CNN classification, increased extent of fibrosis and consolidation were the measures most strongly correlated with FVC decline (r2=0.54 and r2=0.44, p<0.001). Conclusion CT histogram and CNN measurements provide sensitive measures of functional changes in fibrotic HP patients over time. Increased fibrosis was associated with FVC decline, providing index of disease progression. CNN may help improve fibrotic HP follow-up, providing a sensitive tool for progressive interstitial changes, which can potentially contribute to clinical decisions for individualizing disease management.

The ultrafast, high‐pitch turbo FLASH mode of third‐generation dual‐source CT: Effect of different pitch and corresponding SFOV on image quality in a phantom study

PurposeTo investigate the effect of different pitches and corresponding scan fields of view (SFOVs) on the image quality in the ultrafast, high‐pitch turbo FLASH mode of the third‐generation dual‐source CT using an anthropomorphic phantom.MethodsThe phantom was scanned using the ultrafast, high‐pitch turbo FLASH protocols of the third‐generation dual‐source CT with the different pitches and corresponding SFOVs (pitches: 1.55 to 3.2 with increments of 0.1, SFOVs: 50 cm to 35.4 cm). The objective parameters such as the CT number, image noises, signal‐to‐noise ratio (SNR), contrast‐to‐noise ratio (CNR), and artifacts index (AI), and image features from the head, chest, and abdomen were compared between the CT images with a pitch of 1.55 and SFOV of Ø 50 cm and a pitch of 3.2 and SFOV of Ø 35.4 cm. Then, the 18 series of CT images of the head, chest, and abdomen were evaluated by three radiologists independently.ResultsThe differences in the CT numbers were not statically significant between the CT images with a pitch of 1.55 and SFOV of Ø 50 cm and a pitch of 3.2 and SFOV of Ø 35.4 cm from most body parts and potential combinations (p > 0.05), Most of the image noises and the AI from the images with the pitch of 1.55 were significantly lower than those with the pitch of 3.2 (p < 0.05), and the SNR and CNR from the images with the pitch of 1.55 were higher than those with the pitch of 3.2. There were significant differences in the first‐order features and texture features of the head (59.3%, 28.3%), chest (66%, 35.7%), and abdomen (71.6%, 64.7%) (p < 0.05). The subjective image quality was excellent when the pitch was less than 2.0 and gradually decreased with the increasing pitch. In addition, the image quality decreased significantly when the pitch was higher than 3.0 (all k≥0.69), especially in the head and chest.ConclusionsIn the ultrafast, high‐pitch turbo FLASH mode of the third‐generation DSCT, increasing the pitch and lowering the corresponding SFOV will change the image features and cause more artifacts degrading the image quality. Specific to the clinical needs, decreasing the pitch not only can expand the SFOV but also can improve the image quality.

Comparison of direct oral anticoagulants to vitamin-K antagonists as treatment for leaflet thrombosis after Transcatheter Aortic Valve Implantation (TAVI)

Abstract Introduction Leaflet thrombosis can occur following transcatheter aortic valve implantation (TAVI). While a frequent finding in post-TAVI CT scans, leaflet thrombosis is usually clinically silent and the decision to initiate anticoagulation depends on clinical considerations. Best treatment is unknown. We compared the effectiveness of direct oral anticoagulants (DOAC) and vitamin K antagonists (VKA) to resolve leaflet thrombosis in patients with serial CT imaging following TAVI. Methods Consecutive TAVI patients who had undergone routine follow-up cardiac CT after TAVI procedures were screened for inclusion in this analysis. A total of 44 patients diagnosed with leaflet thrombosis and available follow-up CT after anticoagulation therapy were identified. Leaflet thrombosis on cardiac CT was defined as presence of hypoattenuated leaflet thickening with or without leaflet motion restriction, as previously described. The indication and type of anticoagulation was according to physician discretion. We compared patients on DOAC with patients on VKA therapy for the resolution of leaflet thrombosis. Results Mean age of the 44 patients was 80±6 years (59% men), and the median time interval from TAVI to index CT was 107 days (IQR: 91–189 days). Overall, 39 patients (90%) showed resolution of leaflet thrombosis with anticoagulation therapy, whereas leaflet thrombosis persisted in 5 patients (10%). Resolution of leaflet thrombosis was seen in 26 out of 30 (87%) patients receiving VKA and in 13 out of 14 (93%) patients receiving DOAC, respectively. Groups did not differ regarding age (p=0.97), cardiovascular risk factors (all p&amp;gt;0.1), creatinine levels (p=0.19) TAVI prosthesis type (p=0.54) and size (p=0.66). Also, no difference existed for duration of anticoagulation (median 103 vs. 110 days; p=0.76). The relative risk reduction for persisting leaflet thrombosis using DOACs was 46% in comparison to VKA, however with no statistical significance due to the limited number of patients (p=0.55). Conclusion Anticoagulation therapy resolves leaflet thrombosis after TAVI in the majority of patients. In our exploratory analysis, direct oral anticoagulants seem to be an effective alternative to vitamin-K antagonists. This result is hypothesis generating and needs to be confirmed in larger prospective trials. Funding Acknowledgement Type of funding sources: None.

CST: A Multitask Learning Framework for Colorectal Cancer Region Mining Based on Transformer.

Colorectal cancer is a high death rate cancer until now; from the clinical view, the diagnosis of the tumour region is critical for the doctors. But with data accumulation, this task takes lots of time and labor with large variances between different doctors. With the development of computer vision, detection and segmentation of the colorectal cancer region from CT or MRI image series are a great challenge in the past decades, and there still have great demands on automatic diagnosis. In this paper, we proposed a novel transfer learning protocol, called CST, that is, a union framework for colorectal cancer region detection and segmentation task based on the transformer model, which effectively constructs the cancer region detection and its segmentation jointly. To make a higher detection accuracy, we incorporate an autoencoder-based image-level decision approach that leverages the image-level decision of a cancer slice. We also compared our framework with one-stage and two-stage object detection methods; the results show that our proposed method achieves better results on detection and segmentation tasks. And this proposed framework will give another pathway for colorectal cancer screen by way of artificial intelligence.

Consecutive Serial Non-Contrast CT Scan-Based Deep Learning Model Facilitates the Prediction of Tumor Invasiveness of Ground-Glass Nodules.

IntroductionTumors are continuously evolving biological systems which can be monitored by medical imaging. Previous studies only focus on single timepoint images, whether the performance could be further improved by using serial noncontrast CT imaging obtained during nodule follow-up management remains unclear. In this study, we evaluated DL model for predicting tumor invasiveness of GGNs through analyzing time series CT imagesMethodsA total of 168 pathologically confirmed GGN cases (48 noninvasive lesions and 120 invasive lesions) were retrospectively collected and randomly assigned to the development dataset (n = 123) and independent testing dataset (n = 45). All patients underwent consecutive noncontrast CT examinations, and the baseline CT and 3-month follow-up CT images were collected. The gross region of interest (ROI) patches containing only tumor region and the full ROI patches including both tumor and peritumor regions were cropped from CT images. A baseline model was built on the image features and demographic features. Four DL models were proposed: two single-DL model using gross ROI (model 1) or full ROI patches (model 3) from baseline CT images, and two serial-DL models using gross ROI (model 2) or full ROI patches (model 4) from consecutive CT images (baseline scan and 3-month follow-up scan). In addition, a combined model integrating serial full ROI patches and clinical information was also constructed. The performance of these predictive models was assessed with respect to discrimination and clinical usefulness.ResultsThe area under the curve (AUC) of the baseline model, models 1, 2, 3, and 4 were 0.562 [(95% confidence interval (C)], 0.406~0.710), 0.693 (95% CI, 0.538–0.822), 0.787 (95% CI, 0.639–0.895), 0.727 (95% CI, 0.573–0.849), and 0.811 (95% CI, 0.667–0.912) in the independent testing dataset, respectively. The results indicated that the peritumor region had potential to contribute to tumor invasiveness prediction, and the model performance was further improved by integrating imaging scans at multiple timepoints. Furthermore, the combined model showed best discrimination ability, with AUC, sensitivity, specificity, and accuracy achieving 0.831 (95% CI, 0.690–0.926), 86.7%, 73.3%, and 82.2%, respectively.ConclusionThe DL model integrating full ROIs from serial CT images shows improved predictive performance in differentiating noninvasive from invasive GGNs than the model using only baseline CT images, which could benefit the clinical management of GGNs.

Personalized dosimetry of 177Lu-DOTATATE: a comparison of organ- and voxel-level approaches using open-access images

177Lu-DOTATATE (Lutathera®) enables targeted radionuclide therapy of neuroendocrine tumors expressing somatostatin receptor type 2. Though patient-specific dosimetry estimates may be clinically important for predicting absorbed dose-effect relationships, there are multiple relevant dosimetry paradigms which are distinct in terms of clinical effort, numerical output and added-value. This work compares three different approaches for 177Lu-DOTATATE dosimetry, including 1) an organ-level approach based on reference phantom MIRD S-values scaled to patient-specific organ masses (MIRDcalc), 2) an organ-level approach based on Monte Carlo simulation in a patient-specific mesh phantoms (PARaDIM), and 3) a 3D approach based on Monte Carlo simulation in patient-specific voxel phantoms. Method. Serial quantitative SPECT/CT images for two patients receiving 177Lu-DOTATATE therapy were obtained from archive in the Deep Blue database. For each patient, the serial CT images were co-registered to the first time point CT using a deformable registration technique aided by virtual landmarks placed in the kidney pelves and the lesion foci. The co-registered SPECT images were integrated voxel-wise to generate time-integrated activity maps. Lesions, kidneys, liver, spleen, lungs, compact bone, spongiosa, and rest of body were segmented at the first imaging time point and overlaid on co-registered integrated activity maps. The resultant segmentation was used for three purposes: 1) to generate patient-specific phantoms, 2) to determine organ-level time-integrated activities, and 3) to generate dose volume histograms from 3D voxel-based calculations. Results. Mean absorbed doses were computed for lesions and 48 tissues with MIRDcalc software. Mean organ absorbed doses and dose volume histograms were obtained for lesions and 6 tissues with the voxel Monte Carlo approach. Lesion- and organ-level absorbed dose estimates agreed within ±26% for the lesions and ±13% for the critical organs, among the different methods tested. Overall good agreement was observed with the dosimetry estimates from the NETTER-1 trial. Conclusions. For personalized 177Lu-DOTATATE dosimetry, a combined approach was determined to be valuable, which utilized two dose calculation methods supported by a single image processing workflow. In the absence of quantitative imaging limitations, the voxel Monte Carlo method likely provides valuable information to guide treatment by considering absorbed dose non-uniformity in lesions and organs at risk. The patient-scaled reference phantom method also provides valuable information, including absorbed dose estimates for non-segmented organs, and more accurate dose estimates for complex radiosensitive organs including the active marrow.

MO1045DEVELOPMENT OF A HOME CARE SUPPORT SYSTEM FOR PERITONEAL DIALYSIS PATIENTS I - USING DIGITAL WATERMARKING AND STEGANOGRAPHY*

Background and AimsAs it is necessary to refrain from going out due to the COVID-19 pandemic, a system that allows dialysis patients to be treated at a remote location or at home, i.e., a home care support system, is required. Information and communications technology (ICT) used for these purposes is widely applied in various medical fields. Using ICT has the advantage of allowing the sharing of patients’ electronic patient records (EPR) among medical staff, but increases the risk of copyright infringement and privacy leaks during archiving and transmission.We have developed a home care support system for peritoneal dialysis patients using information hiding technology consisting of both digital watermarking technology for copyright protection and steganography technology for communication security when treating patients at home using ICT. In addition, we evaluated the developed system.MethodThe system for sharing medical information was developed in the PHP programming language on a personal computer system using Microsoft Azure cloud services. Figure 1 shows an explanation of the digital watermarking technology and steganography technology used in the developed system.1. Digital watermarking technologyThe patient’s data, such as EPR data, facility name, etc., were hidden in the region of non-interest (RONI) of the patient’s chest CT image series and stored in a database.2. Steganography technologyWe call scene photos “cover pictures.” Medical information (CT images, etc.) was hidden in the cover picture. In this study, the cover picture containing the medical information was designated as a Stego image. A body CT image series (16-bit, 512 × 512, 100 slices) was used to verify the steganography technique. These CT images were compressed using 7-Zip and then saved in a folder, which was then embedded in the cover photo. The Stego image was then sent from the patient’s home to the medical institution via the home care support system.ResultsWe investigated the hash value, peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) of the image series (Fig. 2). If the structure of the image or photograph was exactly the same, the SSIM shows a value of 1. If the PSNR is ≥ 40 dB, the image quality can be maintained without affecting diagnosis. If part of the ROI is changed during transmission, the hash value decoded from the received Stego image will be different from that before transmission. For Stego images containing watermarked or hidden CT images with 4000 words embedded, SSIM and PSNR were ≥ 0.99 dB and 65.3 dB, respectively.If the medical information was embedded in a low bit plane, such as a 1-bit or 2-bit plane, the radiologist could not identify the embedded information.When our technology was applied, there were no changes in the capacity of CT images or Stego images before and after embedding. Therefore, it was not possible to tell that medical information was embedded due to changes in capacity.ConclusionUsing ICT, we have built a home care support system that can conceal medical information by combining digital watermarking technology and steganography technology to ensure the copyright of images and to ensure privacy and secure transmission of EPR and CT images. Using the developed system, daily medical information of dialysis patients could be transmitted safely to the institute, and the medical staff could share the information safely. Both techniques can be applied to all digital image information, and is not just limited to CT images.

The effect of tube focal spot size and acquisition mode on task-based image quality performance of a GE revolution HD dual energy CT scanner.

To assess the task-based performance of images obtained under different focal spot size and acquisition mode on a dual-energy CT scanner. Axial CT image series of the Catphan phantom were obtained using a tube focus at different sizes. Acquisitions were performed in standard single-energy, high resolution (HR) and dual-energy modes. Images were reconstructed using conventional and high definition (HD) kernels. Task-based transfer function at the 50% level (TTF50%) for teflon, delrin, low density polyethylene (LDPE) and acrylic, as well as image noise and noise texture, were assessed across all focal spots and acquisition modes using Noise Power Spectrum (NPS) analysis. A non-prewhitening mathematical observer model was used to calculate detectability index (dNPW'). TTF50% degraded with increasing focal spot size. TTF50% ranged from 0.67mm-1 for teflon to 0.25mm-1 for acrylic. For standard kernel, image noise and NPS-determined average spatial frequency were 8.3 HU and 0.29mm-1, respectively in single-energy, 12.0 HU and 0.37mm-1 in HR, and 7.9 HU and 0.26mm-1 in dual-energy mode. For standard kernel, dNPW' was 61 in single-energy and HR mode and reduced to 56 in dual-energy mode. The task-based image quality assessment metrics have shown that spatial resolution is higher for higher image contrast materials and detectability is higher in the standard single-energy mode compared to HR and dual-energy mode. The results of the current study provide CT operators the required knowledge to characterize their CT system towards the optimization of its clinical performance.

Patients with advanced solid cancers treated with ERK inhibitors exhibit pseudo-progession in lymphatic nodes.

3138 Background: ERK1/2 signaling is often overactivated in cancer, especially in patients with molecular alterations activating the MAPK pathway. MAPK pathway inhibition can result in the increase of CD8+ and CD4+ T-cells and decreased expression of immunosuppressive cytokines. Methods: This is a retrospective study of 52 patients with advanced solid cancers and oncogenic alterations in the MAPK pathway, who were treated in phase I/II clinical trials with five different single agent ERK1/2 inhibitors at MD Anderson Cancer Center. We reviewed serial PET and/or CT imaging obtained before therapy, on therapy, and after therapy completion. We evaluated dynamic changes in the lymphatic nodes (LN) in the context of overall response per RECIST 1.1 and other outcomes. Results: Of the 52 patients, 19 (37%) patients were evaluated with serial PET/CT and 33 (63%) with serial CT imaging only. Of the 19 patients evaluated with PET/CT, 12 (63%) demonstrated increased FDG uptake in LN compared to pre-treatment imaging (LN enlargement, n = 9; no LN enlargement, n = 3) discrepant from the known target and non-target lesions. These 12 patients were on therapy with ERK inhibitors (11 at doses &gt; recommended phase 2 dose [RP2D]) for a median of 3.6 months (range, 1.8-12 months) with a best response per RECIST 1.1. as follows: partial response, n = 1; stable disease (SD), n = 10; progressive disease (PD), n = 1. Of interest, in 6 of those 12 patients, FDG uptake in LN decreased or resolved after treatment discontinuation. Further, one patient had a biopsy of an emerged LN, which showed lymphocytic infiltrate without tumor cells. Of the 33 patients evaluated with CT only, 5 (15%) demonstrated increased size of LN discrepant from the known target and non-target lesions compared to pre-treatment imaging. These 5 patients were on therapy with ERK inhibitors (all at doses &lt; RP2D) for a median of 1.4 months (range, 1.1-3.5 months) with a best response per RECIST 1.1. as follows: SD, n = 2; PD, n = 3. Of interest, in 2 of those 5 patients, size of LN decreased or resolved after treatment discontinuation. In addition, one patient had a biopsy of an emerged LN, which showed lymphoid aggerates without tumor cells. Conclusions: Our data suggest that treatment with ERK inhibitors can result in activation of the lymphatic nodes, which can manifest as pseudo-progression. This can lead to an inconclusive assessment of their therapeutic benefit and further suggests exploration of the potential synergistic effects with immune therapy.

Occurrence of Hepatocellular Carcinoma in a 40-Year-Old Male With MEN2A Syndrome

Background: Multiple Endocrine Neoplasia Type 2A (MEN 2A) is a genetic syndrome in which the patient is susceptible to the development of: 1. medullary thyroid carcinoma, 2. pheochromocytoma, and 3. parathyroid adenomas or hyperplasia. Our objective is to report the first occurrence of hepatocellular carcinoma in a young adult male with MEN 2A syndrome without prior liver disease.Clinical Case: A 40-year-old male was screened positive for the C634R point mutation of the RET Proto-Oncogene after his sister with MEN 2A syndrome had tested positive. The patient had no history of alcohol or drug abuse. His family history was remarkable for the deaths of his mother and maternal grandmother from unknown malignancies at the ages of 35 and 45 respectively. His physical exam revealed a BP of 135/85mm Hg, BMI 26 kg/m2 and palpable bilateral thyroid nodules. Lab tests included a calcitonin of 131 pg/ml, (0.0-8.4 pg/ml), calcium 11.4 mg/dL (8.4-10.3 mg/dL), parathyroid hormone (PTH) 1765 pg/ml (12-65 pg/ml), ALK PHOS 1856 U/L (20-120 U/L), ALT 16 U/L (<39 U/L), Albumin 4.1gm/dl (3.4-5.0gm/dl), plasma normetanephrine 0.95 nmol/L (0.00- 0.89 nmol L) and urine metanephrines 291 pg/d (62-207 pg/d). A CT scan demonstrated hyperdense 12 mm right and 5 mm left adrenal nodules, both confirmed MIBG positive. Neck ultrasound showed bilateral thyroid nodules, the largest measuring 1.1 x 0.8 x 1.1 cm in the right lobe and a 3.5 x 2.2 x 2.1 cm heterogeneous mass posterior to the right thyroid lobe. The patient was prepped with doxazosin and underwent a laparoscopic right adrenalectomy then 2 months later a total thyroidectomy with neck lymph node dissection, resection of the right parathyroid tumor mass and bilateral inferior parathyroid glands. Surgical pathology confirmed the right adrenal pheochromocytoma, multifocal bilateral medullary thyroid cancer with 1 of 70 neck lymph nodes positive and a single large parathyroid adenoma. He received levothyroxine to maintain euthyroidism. Within 6 months of his surgery, calcitonin was < 2 pg/ml, CEA 2.3 U/ml (<5.0 U/ml) and ALK PHOS 44 U/L. Urine metanephrines remained mildly elevated 291 pg/d (62-207 pg/d). Serial abdominal CT imaging revealed no change of the left adrenal mass but three new bi-lobar 1-2 cm enhancing liver lesions. CT guided needle biopsies of the liver masses revealed hepatocellular cancer without evidence of cirrhosis. The patient underwent successful thermal ablation of all 3 liver lesions. Laboratory evaluation was negative for Hepatitis A, B and C. His alpha fetal protein level has remained stable in the range of 4.7 to 5.8 ng/ml (<15ng/ml).Conclusions: This is the first reported case of hepatocellular carcinoma in a patient with MEN 2A syndrome who had no predisposing liver disease, raising suspicion that his germline RET mutation contributed to his liver cancer.

Correlation of autopsy pathological findings and imaging features from 9 fatal cases of COVID-19 pneumonia.

We aimed to investigate the relationship of radiological features and the corresponding pulmonary pathology of patients with Coronavirus Disease (COVID-19) pneumonia.In this multicenter study, serial chest CT and radiographic images from 9 patients (51–85 years old, 56% male) were reviewed and analyzed. Postmortem lungs were sampled and studied from these autopsies, with a special focus on several corresponding sites based on imaging features.The predominant pattern of pulmonary injury in these 9 cases was diffuse alveolar damage (DAD) and interstitial inflammation. Moreover, acute fibrinous exudates, organization, inflammatory cell infiltration, hyaline membranes, pulmonary edema, pneumocyte hyperplasia, and fibrosis were all observed. The histopathology features varied according to the site and severity of each lesion. In most of the 9 cases, opacities started from a subpleural area and peripheral structures were more severely damaged based on gross views and pathological examinations. Fibrosis could occur in early stages of infection and this was supported by radiological and pathological findings. The radiological features of COVID-19 pneumonia, at the critically ill stage, were diffuse ground-glass opacities with consolidation, interstitial thickening, and fibrous stripes, which was based in the fibrous tissue proliferation in the alveolar and interlobular septa, and filled alveoli with organizing exudation. Fungal and bacterial co-infections were also observed in 6 cases.Typical imaging features can be correlated with underlying pathological findings. Combining assessments of imaging features with pathological findings therefore can enhance our understanding of the histopathological mechanism of COVID-19 pneumonia, and facilitate early radiological diagnosis and prognosis estimation of COVID-19 pneumonia, which has important implications for the development of clinical targeted treatments and research related to COVID-19 pneumonia.

Serial Optic Nerve Sheath Diameter via Radiographic Imaging: Correlation With ICP and Outcomes.

Evaluation of optic nerve sheath diameter (ONSD) is a suggested correlation of intracranial pressure (ICP) and potential predictor of outcome after neurologic injury. Studies have evaluated sonographic measurement of ONSD; however, clinical limitations to this approach persist. Evaluation of ONSD measurements via routine brain CT imaging is less studied but offers potential for detection of increased ICP in the absence of invasive monitoring. Previous studies have used cross-sectional approaches to ONSD measurements via CT scan among patients with traumatic brain injury (TBI). No studies have evaluated serial correlations between CT ONSD measurements and ICP throughout hospitalization and across diagnosis types. The objective of this study was to investigate correlations between ONSD via serial CT imaging, ICP, and outcome at discharge among patients with neurologic injury. This is a retrospective cohort study of all adult patients admitted during a 12-month period with acute neurologic injury requiring ICP monitoring and critical care admission. N = 48. There was a strong, positive correlation between right/left ONSD across time points (r = 0.7-9, p < 0.001), suggesting a consistent bilateral response. Correlations were strongest between initial inpatient CT scan ONSD readings and ICP (r = 0.5, p < 0.05), but decreased over time. Patients with increased ICP across all diagnosis types experienced higher ONSD values on presentation to the emergency department (ED) and throughout hospitalization (range 5.7-6.4 mm, p < 0.05). Findings contribute to the utility of CT ONSD measurements as a potential indicator of increased ICP. Measurement of ONSD during serial CT brain imaging may inform clinical decisions regarding need for more invasive monitoring after neurologic injury.

3D Printed Model of Airway for Clinical Simulation

Background: The present medical curriculum aims at training the students to be proficient in performing techniques required for clinical practice. This is best achieved through clinical simulation, which has emerged as a successful method for clinical learning. Residents in respiratory medicine need to be trained in the procedure of bronchoscopy for which a functional model of the airway is required. Airway mannequins for this purpose can be produced using 3D printing technology, which involves the usage of sophisticated software. Subjects and Methods: Serial axial CT images of the chest, revealing details of the respiratory tract were selected as the base resource to recreate the bronchial tree by 3D printing. This DICOM (Digital Imaging and Communications in Medicine) images after conversion into STL (Stero lithography) format were transferred into a 3D printer and physical models were made from these data, using Vero clear and rubber. This model which had a life-like form and consistency required for practicing the skill was connected to an airway mannequin using an adaptor to practice the skill. Conclusions: Axial CT scan images provide the base data for reconstructing the airway of a patient, using 3D printing technology and appropriate software. Such reconstructions can be used to produce a functional model of the airway, which can be used for training in bronchoscopy. The training system could be connected to a monitor thereby facilitating tracking of the probe of the bronchoscope. Repeated trials make the trainees perfect their technique. Our attempt to replicating the tracheobronchial tree for such training has been a success.