Name: synchronous triplanar reconstruction integrated with color doppler mapping for precise and rapid localization of thyroid lesions
Uploaded: 2024-02-09T15:00:00.000+00:00
Duration: 5 min 41 s
Description: Watch this Scientific Journal Video about Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis at JoVE.com

This publication received support from the Shaanxi Provincial Key Research and Development Plan: 2023-ZDLSF-56 and the Shaanxi Provincial &#34;Scientist + Engineer&#34; Team Construction: 2022KXJ-019.

This study was approved by the Institutional Review Board of Sunsimiao Hospital affiliated with the Beijing University of Chinese Medicine. The patient was recruited from the Department of Thyroid, Sunsimiao Hospital. The patient underwent a thyroid ultrasound examination and gave informed consent for the study. In this investigation, 4D ultrasound data acquired using a handheld device were utilized to reconstruct triplanar views of the thyroid gland. Furthermore, real-time synchronous color Doppler imaging was achieved. The software tools used in this research are listed in the Table of Materials.
1. Data collection and preparation
<ol>
	<li>Using a portable handheld ultrasound device, place the linear array transducer transversely on the patient&#39;s neck to image the thyroid in the cross-sectional plane. Slide the probe slowly and steadily along the length of the thyroid while maintaining probe contact and orientation.</li>
	<li>Acquire a sequence of transverse B-mode images visualizing thyroid morphology at a frame rate of 33 Hz.</li>
	<li>Concurrently, apply color Doppler to detect blood flow in the gland and vessels. Scan from the superior to inferior thyroid poles to cover the entire gland. The resulting dynamic imaging sequence comprises consecutive transverse slices that form two 4D data sets.</li>
	<li>Loading and browsing of 4D B-mode ultrasound data
	<ol>
		<li>Copy all DICOM data to a customized working directory. 
		NOTE: The working directory is the same in both the operating system and MATLAB. Press Enter after typing each line to run the command in MATLAB.</li>
		<li>Import the B-mode US data file into MATLAB using the dicomread function, and use the size function to view the dimensions of the data.
		<ol>
			<li>Open MATLAB on the computer.</li>
			<li>In the Command window, type: 
			VB0 = dicomread(&#39;fname.dcm&#39;); 
			Where &#39;fname.dcm&#39; could be replaced with the actual filename of the DICOM data. This will read in the DICOM file and store the image data in the variable VB0.</li>
			<li>To view the size of the loaded data, type: 
			size(VB0), 
			NOTE: The 4D data imported here had dimensions of 768 pixels x 1024 pixels x 3 x 601 layers. The 768 pixels x 1024 pixels x 3 corresponds to a standard RGB image, where each pixel is represented by three channels with 24-bit depth. The 601 layers indicate the total number of scanned slices.</li>
		</ol>
		</li>
		<li>Call the US_B_Show function to convert the 4D matrix data into a continuous grayscale video sequence to be played back continuously for detailed examination (see Figure 1).
		<ol>
			<li>To convert this 4D ultrasound data matrix VB0 imported in Step 1.4.2.2 using the dicomread function on the DICOM files into a continuously playing grayscale video sequence, call the US_B_Show function by typing the following command in the MATLAB Command window: 
			US_B_Show(VB0) 
			Where VB0 is the 4D matrix variable containing the ultrasound data imported previously.</li>
		</ol>
		</li>
		<li>The GUI in Figure 1 shows playback buttons for pause, forward, rewind, etc.
		<ol>
			<li>Press the play button to initiate continuous video playback of the frame sequence. Use the pause and play control tool icons for flexible navigation of any frame. Use the zoom in/out buttons to dynamically magnify or minify the images during playback and the default zoom button to reset to the original 1x view.</li>
			<li>Click on the inspect pixel values button and move the mouse over a region to overlay crosshairs with pixel coordinates and intensities for localized analysis. 
			NOTE: These interactive controls enable flexible inspection of ultrasound data characteristics across both space and time.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Loading and browsing of 4D color Doppler ultrasound data
	<ol>
		<li>Import the color Doppler ultrasound data file into MATLAB using the dicomread function, and use the size function to view the dimensions of the data. 
		NOTE: The 4D data imported here had dimensions of 768 pixels x 1024 pixels x 3 x 331 layers. The 768 pixels x 1024 pixels x 3 corresponds to a standard RGB image, with red and blue representing blood flow in different directions. The 331 layers indicate the total number of scanned slices.</li>
		<li>Use the US_C_Show function to convert the 4D matrix data into a continuous color video sequence to be played back continuously for detailed examination (see Figure 2). 
		NOTE The GUI in Figure 2 has the same set of interactive controls and operations as described previously in step 1.4.4 for Figure 1.</li>
	</ol>
	</li>
</ol>
2. Synchronous observation of B-mode and color Doppler ultrasound
NOTE: The 4D B-Mode Ultrasound Data shown in Figure 1 and the 4D Color Doppler Ultrasound Data shown in Figure 2 contain the same absolute time stamps in the fourth dimension along the temporal axis. This field is recorded in the DICOM metadata as FrameTimeVector. Based on the time values in this field, Figure 1 and Figure 2 can be synchronized in real time.
<ol>
	<li>After reading the two 4D files using the dicomread command, execute the Synchronize_B_C function with the two 4D matrices as inputs. 
	NOTE: Figure 3 shows the resulting video that can still be played back continuously. The difference now is that the 4D B-Mode Ultrasound Data and the 4D Color Doppler Ultrasound Data are synchronized in real time within the same video frames. The GUI in Figure 3 has the same set of interactive controls and operations as described previously in step 1.4.4 for Figure 1.</li>
</ol>
3. Synchronous triplanar reconstruction for thyroid
NOTE: To enable more precise localization and quantification of lesions, this study performed triplanar reconstruction of the thyroid gland from the acquired 4D ultrasound data, with real-time interactivity. This allows clinicians to rapidly and accurately pinpoint lesions, laying a solid foundation for subsequent quantification of the affected regions.
<ol>
	<li>Call the thyroid_triplanar function with the 4D B-mode ultrasound data from Figure 1 as input to derive the three orthogonal planes (coronal, sagittal, and axial) as shown in Figure 4.</li>
	<li>The crosshair interaction in Figure 4 enables real-time inspection of different parts of the thyroid gland. Click and drag the center of the crosshair for an arbitrary 3D examination of the thyroid anatomy reconstructed from ultrasound. 
	NOTE: The GUI in Figure 4 also enables adjustment of the grayscale intensity range, contrast, and brightness of the triplanar views.</li>
	<li>Press and drag the left mouse button over any region of the images for real-time modification of brightness and contrast levels. Release the mouse button to confirm and finalize the adjustments.</li>
</ol>
4. Synchronous triplanar reconstruction for 3D blood flow field
NOTE: Reconstructing the synchronous triplanar views for the 3D blood flow field based on 4D color Doppler ultrasound data is also clinically important for characterizing Hashimoto&#39;s Thyroiditis (HT).
<ol>
	<li>Call the thyroid_3D_blood function with the 4D C-mode ultrasound data from Figure 2 as input to derive the three orthogonal planes (coronal, sagittal, and axial) as shown in Figure 5.</li>
	<li>The crosshair interaction in Figure 5 enables real-time inspection of different parts of the thyroid gland. Click and drag the center of the crosshair for an arbitrary 3D examination of the thyroid anatomy reconstructed from ultrasound. 
	NOTE: The GUI in Figure 5 also enables adjustment of the grayscale intensity range, contrast, and brightness of the triplanar views.</li>
	<li>Press and drag the left mouse button over any region of the images for real-time modification of brightness and contrast levels. Release the mouse button to confirm and finalize the adjustments.</li>
</ol>
5. Synchronization of B-mode triplanar views and color Doppler triplanar views
NOTE: Building upon the triplanar views shown in Figure 4, synchronizing the corresponding color Doppler flow images to the lesion locations would undoubtedly facilitate the diagnosis and quantification of the pathological progression in Hashimoto&#39;s Thyroiditis (HT).
<ol>
	<li>Drag the crosshair interaction in Figure 4 to locate the region of interest, and execute US_B2C to obtain the corresponding location in the color Doppler triplanar views.</li>
	<li>Drag the crosshair interaction in Figure 5 to locate the region of interest, and execute US_C2B to obtain the corresponding location in the B-mode triplanar views. 
	NOTE: Figure 6 lays a solid ultrasonographic foundation for the precise localization and definitive diagnosis of Hashimoto&#39;s thyroiditis (HT) lesions.</li>
</ol>

Synchronous Visualization of Thyroid Structural and Functional Information

<ol>
	<li>Ragusa, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hashimotos'+thyroiditis:+Epidemiology,+pathogenesis,+clinic+and+therapy.">Hashimotos' thyroiditis: Epidemiology, pathogenesis, clinic and therapy.</a> Best Pract Res Clin Endocrinol Metab. 33 (6), 101367 (2019).</li><li>Ralli, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hashimoto's+thyroiditis:+An+update+on+pathogenic+mechanisms,+diagnostic+protocols,+therapeutic+strategies,+and+potential+malignant+transformation.">Hashimoto's thyroiditis: An update on pathogenic mechanisms, diagnostic protocols, therapeutic strategies, and potential malignant transformation.</a> Autoimmun Rev. 19 (10), 102649 (2020).</li><li>Soh, S., Aw, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Laboratory+testing+in+thyroid+conditions+-+pitfalls+and+clinical+utility.">Laboratory testing in thyroid conditions - pitfalls and clinical utility.</a> Ann Lab Med. 39 (1), 3-13 (2019).</li><li>Cansu, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diagnostic+value+of+3D+power+Doppler+ultrasound+in+the+characterization+of+thyroid+nodules.">Diagnostic value of 3D power Doppler ultrasound in the characterization of thyroid nodules.</a> Turk J Med Sci. 49, 723-729 (2019).</li><li>Haugen, B. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=2015+American+Thyroid+Association+Management+Guidelines+for+adult+patients+with+thyroid+nodules+and+differentiated+thyroid+cancer:+The+American+Thyroid+Association+Guidelines+Task+Force+on+Thyroid+Nodules+and+Differentiated+Thyroid+Cancer.">2015 American Thyroid Association Management Guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer.</a> Thyroid. 26 (1), 1-133 (2016).</li><li>Acharya, U. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diagnosis+of+Hashimoto's+thyroiditis+in+ultrasound+using+tissue+characterization+and+pixel+classification.">Diagnosis of Hashimoto's thyroiditis in ultrasound using tissue characterization and pixel classification.</a> Proc Inst Mech Eng H. 227 (7), 788-798 (2013).</li><li>Zhang, Q., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Deep+learning+to+diagnose+Hashimoto's+thyroiditis+from+sonographic+images.">Deep learning to diagnose Hashimoto's thyroiditis from sonographic images.</a> Nat Commun. 13 (1), 3759 (2022).</li><li>Huang, J., Zhao, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+diagnosis+progress+of+ultrasound+imaging+technology+in+thyroid+diffuse+diseases.">Quantitative diagnosis progress of ultrasound imaging technology in thyroid diffuse diseases.</a> Diagnostics. 13 (4), 700 (2023).</li><li>Gasic, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Relationship+between+low+vitamin+D+levels+with+Hashimoto+thyroiditis.">Relationship between low vitamin D levels with Hashimoto thyroiditis.</a> Srp Arh Celok Lek. 151 (5-6), 296-301 (2023).</li><li>Sultan, S. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Is+3D+ultrasound+reliable+for+the+evaluation+of+carotid+disease?+A+systematic+review+and+meta-analysis.">Is 3D ultrasound reliable for the evaluation of carotid disease? A systematic review and meta-analysis.</a> Med Ultrason. 25 (2), 216-223 (2023).</li><li>Arsenescu, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=3D+ultrasound+reconstructions+of+the+carotid+artery+and+thyroid+gland+using+artificial-intelligence-based+automatic+segmentation-qualitative+and+quantitative+evaluation+of+the+segmentation+results+via+comparison+with+CT+angiography.">3D ultrasound reconstructions of the carotid artery and thyroid gland using artificial-intelligence-based automatic segmentation-qualitative and quantitative evaluation of the segmentation results via comparison with CT angiography.</a> Sensors. 23 (5), 2806 (2023).</li><li>Kr&#246;nke, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tracked+3D+ultrasound+and+deep+neural+network-based+thyroid+segmentation+reduce+interobserver+variability+in+thyroid+volumetry.">Tracked 3D ultrasound and deep neural network-based thyroid segmentation reduce interobserver variability in thyroid volumetry.</a> PLoS One. 17 (7), e0268550 (2022).</li><li>Hazem, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reliability+of+shear+wave+elastography+in+the+evaluation+of+diffuse+thyroid+diseases+in+children+and+adolescents.">Reliability of shear wave elastography in the evaluation of diffuse thyroid diseases in children and adolescents.</a> Eur J Radiol. 143, 109942 (2021).</li><li>Herickhoff, C. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Low-cost+volumetric+ultrasound+by+augmentation+of+2D+systems:+design+and+prototype.">Low-cost volumetric ultrasound by augmentation of 2D systems: design and prototype.</a> Ultrasound Imaging. 40 (1), 35-48 (2017).</li><li>Seifert, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optimization+of+thyroid+volume+determination+by+stitched+3D-ultrasound+data+sets+in+patients+with+structural+thyroid+disease.">Optimization of thyroid volume determination by stitched 3D-ultrasound data sets in patients with structural thyroid disease.</a> Biomedicines. 11 (2), 381 (2023).</li></ol>

The software tool for thyroid disease precision quantification, listed in the Table of Materials of this study as Thyroid Disease Precision Quantification V1.0, is a product of Beijing Intelligent Entropy Science &#38; Technology Co., Ltd. The intellectual property rights of this software tool belong to the company. The authors have no conflicts of interest to declare.

Critical steps in the protocol 
While Figure 1 and Figure 2 have value for inspection and diagnosis, determining lesion location and views from other perspectives requires expert experience. For the diagnosis of Hashimoto&#39;s thyroiditis (HT), synchronizing Figure 1 and Figure 2 in real time is also an important and critical step. Protocol step 3.3 is one of the key steps where, as shown in Figure 4, the attending physician can interactively examine arbitrary cross-sections of the 3D thyroid anatomy. This is crucial for localizing lesions and identifying abnormal tissue regions. Traditionally, handheld ultrasound scanning only provides 2D transverse views. This unavoidably leads to oversight of 3D pathological details due to blind spots. Similarly, protocol step 4.3 generates the 3D blood flow map, which is also critical for pinpointing lesion locations. Protocol steps 5.1 and 5.2 synchronize the structural and functional thyroid images, equipping clinicians with more powerful digital intelligent tools for managing complex conditions.
Modifications and troubleshooting 
If reconstruction artifacts occur, the acquisition sweep extent may be insufficient. Repeating scanning with extended coverage can overcome this. Parameters such as slice spacing and pixel size can also be adjusted.
Limitations of the method 
Although handheld ultrasound scanning can obtain time stamps for synchronizing various modes, it lacks real-time 3D probe localization. Hence, only the transverse dimensions are precisely reconstructed in the thyroid models. Quantitative measurements on transverse planes are currently accurate, while coronal and sagittal views assist pathological localization but have unreliable quantitative scales at present.
Significance with respect to existing methods 
This 5D ultrasound technique enhances conventional 2D scanning by enabling multi-planar structural examination combined with blood flow mapping in a panoramic visualized space. It overcomes limitations like operator dependence, blind spots, and diagnostic ambiguity that persist in 2D ultrasonography. The proposed workflow lays a robust foundation to standardize and transform the current experience-dependent practices for ultrasound diagnosis of thyroid diseases.
Potential applications 
This method can be applied to precisely localize and quantify thyroid nodules, tumors, and inflammatory lesions such as Hashimoto&#39;s thyroiditis. It provides radiologists and surgeons with enhanced visual perspectives for evaluating pathology. The technique has considerable potential to aid diagnosis, treatment planning, and surgical guidance. Additionally, the study team plans to incorporate biochemical markers with this 5D analysis pipeline to realize AI-empowered precision diagnosis and quantification for thyroid diseases.

Hashimoto's thyroiditis (HT), the most frequent autoimmune thyroid disorder (AITD), is the leading cause of hypothyroidism in iodine-sufficient areas of the world1. It is characterized by lymphocytic infiltration and autoantibodies against thyroid antigens, leading to the destruction of thyroid architecture and hypothyroidism2. Staging of HT aims to assess the severity and guide treatment decisions. It relies on a combination of biochemical markers such as thyroid stimulating hormone (TSH) and thyroid autoantibodies3, as well as ultrasonographic features visible on thyroid ultrasound4,5,6.
On ultrasound examination, HT demonstrates characteristic findings, including diffusely decreased echogenicity, heterogeneous echotexture, micronodularity, and increased blood flow on color Doppler6,7. However, conventional two-dimensional (2D) grayscale ultrasound lacks quantitative methods for systematically analyzing these features for HT staging8. The assessment of vascularity changes is also limited to qualitative visual inspection in 2D mode. The complex three-dimensional (3D) architecture of the thyroid gland further hampers thorough evaluation using conventional 2D slicing9,10. These factors lead to imaging blind spots and misinterpretation, resulting in low sensitivity and specificity, especially for less experienced practitioners11,12.
Conventional handheld ultrasound scanning integrates real-time acquisition and diagnosis. This coupled workflow reliance increases the likelihood of oversight errors during scanning. The lack of spatial localization and tracking also makes lesion identification and monitoring imprecise12,13. Dedicated 3D ultrasound systems have emerged to address these limitations and have shown promising results14,15. However, most 3D ultrasound technologies require complex mechanical scanning mechanisms and specialized transducers, leading to high costs and barriers to adoption.
To overcome the limitations of conventional 2D and 3D ultrasound techniques, this study proposes a novel 3D reconstruction and visualization solution tailored for thyroid examination. Using widely available handheld ultrasound, multiple 2D sweeps are first acquired to scan the entire thyroid gland. 3D volumetric reconstruction is then realized by spatial registration and fusion of the 2D sequences. Concurrently, color Doppler frames are coregistered to create vascularity maps visualizing blood flow changes. The reconstructed 3D grayscale volumes and colored vascularity maps are finally integrated into a single platform, enabling synchronized multi-planar visualization and combined structural-functional inspection.
This proposed 3D fusion technique provides a systematic and comprehensive evaluation of the complex thyroid morphology from different aspects. By minimizing blind spots and enabling global overview, it could help improve diagnostic accuracy and reduce oversight errors, especially benefiting novice practitioners. The multi-modal visualization also facilitates rapid and precise localization of lesions, holding promise for early diagnosis and treatment of thyroid nodules and tumors. Moreover, the method introduces quantitative 3D feature analysis which has not been investigated for HT staging before. With wide adoption, it has the potential to standardize and objectify the currently experience-dependent ultrasound diagnosis procedures. By synergistically integrating handheld 3D reconstruction, multi-modal fusion, quantitative feature analysis, and flexible visualization into a streamlined workflow, this low-cost, easy-to-use technique represents a diagnostically powerful leap from conventional 2D ultrasound for advancing thyroid examination.

<table><tbody><tr><td>MATLAB</td><td>MathWorks&amp;nbsp;</td><td>2023B</td><td>Computing and visualization&amp;nbsp;</td></tr><tr><td>Tools for Thyroid Disease Precision Quantification</td><td>Intelligent Entropy</td><td>Thyroid-3D V1.0</td><td>Beijing Intelligent Entropy Science &amp;amp; Technology Co Ltd.&lt;br/&gt; Modeling for Thyroid Disease</td></tr></tbody></table>

synchronous triplanar reconstruction integrated with color doppler mapping for precise and rapid localization of thyroid lesions

This paper proposes a novel thyroid examination technique based on five-dimensional (5D) synchronous reconstruction of ultrasound data. The raw temporal sequences are reconstructed into 3D volumetric data reflecting anatomical structure. Triplanar visualization from three orthogonal planes is realized to provide a systematic inspection of the entire gland. Color Doppler imaging is integrated into each triplanar slice to map vascularity changes. This multi-modal fusion enables synchronous display of structural, functional, and blood flow information in the reconstructed 5D space. Compared to conventional scanning, this technique offers the benefits of flexible offline diagnosis, reduced dependency on scanning, enhanced intuitive interpretation, and comprehensive multi-aspect evaluation. By minimizing oversight errors, it could improve diagnostic accuracy, especially for novice practitioners. The proposed 5D fusion method allows rapid and precise localization of lesions for early detection. Future work will explore integration with biochemical markers to further improve diagnostic precision. The technique has considerable clinical value for advancing thyroid examination.

As shown in the graphical user interface (GUI) in Figure 1 and Figure 2, the ultrasound scanning sequence can be checked continuously. However, this two-dimensional examination relies heavily on the thyroidologist's anatomical knowledge to mentally reconstruct the lesion's location, which is challenging for novices and results in a lack of quantitative consistency. Figure 3 fuses the B-mode grayscale with color Doppler flow images to enable more informed inspection on the 2D scans.
To facilitate a comprehensive and reliable assessment of thyroid disorders, Figure 4 shows the 3D spatial distribution of B-mode intensities, while Figure 5 exhibits the 3D vascularity map reconstructed from color Doppler data. As illustrated in the GUI (Figure 6), synchronized visualization of the structural and functional information along three orthogonal planes is realized. Clinicians can continuously inspect the multiplanar cross-sections of thyroid grayscale images and the corresponding blood flow images. This seamless integration of complementary modalities could play a pivotal role in precisely localizing and determining the severity of thyroid pathologies.
If the 3D grayscale volumes and 3D color Doppler volumes are essentially 4D data spanning the spatial and pathological dimensions, linking their interaction across the two synchronized triplanar visualizations could empower the thyroidologist to swiftly pinpoint lesions in a unified 5D space and deliver accurate diagnoses based on the joint intensity and flow patterns.
<img alt="Ultrasound thyroid scan, 2D imaging, medical diagnosis, anatomical visualization, transverse section." class="xfigimg" src="/files/ftp_upload/66569/66569fig01.jpg" data-altupdatedat="1747736610000" data-alt="Ultrasound thyroid scan; diagnostic imaging; shows gland structure; non-invasive medical examination."> 
Figure 1: Transverse B-mode ultrasound video loops. Consecutive B-mode frames acquired by continuous transverse scanning show thyroid morphology. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66569/66569fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Thyroid ultrasound with Doppler imaging; color flow Doppler technique; medical diagnostic procedure." class="xfigimg" src="/files/ftp_upload/66569/66569fig02.jpg" data-altupdatedat="1747736610000" data-alt="Ultrasound color Doppler image of thyroid showing blood flow dynamics; used for thyroid assessment."> 
Figure 2: Transverse color Doppler ultrasound video loops. Consecutive color Doppler frames obtained by transverse scanning reveal blood flow characteristics of the thyroid tissue. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66569/66569fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Ultrasound imaging with Doppler analysis; medical diagnostic tool; blood flow visualization." class="xfigimg" src="/files/ftp_upload/66569/66569fig03.jpg" data-altupdatedat="1747736610000" data-alt="Ultrasound imaging showing vascular flow, Doppler mode, medical diagnostic tool, anatomy analysis."> 
Figure 3: Synchronized B-mode and Doppler ultrasound. Integrated video synchronously exhibiting thyroid structure (grayscale) and blood flow (colored overlay). The color Doppler overlay depicts the direction and velocity of flow using a color scale-red indicates flow toward the transducer; blue indicates flow away from the transducer. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66569/66569fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Ultrasound imaging; 3D scan slices in X, Y, Z planes; tissue structure analysis diagram." class="xfigimg" src="/files/ftp_upload/66569/66569fig04.jpg" data-altupdatedat="1747736610000" data-alt="Ultrasound imaging diagram: X, Y, Z axes view displaying tissue cross-sections and coordinates for analysis."> 
Figure 4: Triplanar views extracted from B-mode ultrasound. Orthogonal coronal, sagittal, and axial planes reconstructed from 4D B-mode scans using triplanar visualization. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66569/66569fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Multidimensional spectroscopy data analysis diagram showing X, Y, Z axes with intensity color map." class="xfigimg" src="/files/ftp_upload/66569/66569fig05.jpg" data-altupdatedat="1747736610000" data-alt="Spectroscopy heatmap; false-color images show absorption data across X, Y, Z axes; spectral analysis."> 
Figure 5: Triplanar views extracted from Doppler ultrasound. Orthogonal coronal, sagittal, and axial planes reconstructed from 4D Doppler scans to map blood flow characteristics of the thyroid tissue. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66569/66569fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Ultrasound imaging and thermal mapping, diagram showing cross-sectional analysis and heat distribution." class="xfigimg" src="/files/ftp_upload/66569/66569fig06.jpg" data-altupdatedat="1747736610000" data-alt="Ultrasound vs. thermal maps; medical imaging comparison, cross-sectional diagrams, temperature analysis."> 
Figure 6: Synchronized triplanar views fusing structural and vascularity data. Fused multiplanar reconstruction synchronizing B-mode and Doppler data to enable combined morphological and functional inspection. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66569/66569fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis at JoVE.com

Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis

Here we present a 5D ultrasound technique combining multi-planar 3D reconstruction and color Doppler fusion, which enables synchronous visualization of thyroid structural and functional information. By minimizing blind spots, this method allows rapid, precise localization of lesions to improve diagnostic accuracy, especially benefiting novice practitioners.

Synchronous Triplanar Reconstruction Integrated with Color Doppler Mapping for Precise and Rapid Localization of Thyroid Lesions

This paper proposes a novel thyroid examination technique based on five-dimensional (5D) synchronous reconstruction of ultrasound data. The raw temporal ...

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Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers

Small animal fluorescence molecular imaging (FMI) can be a powerful tool for preclinical drug discovery and development studies1. However, light absorption by tissue chromophores (e.g., hemoglobin, water, lipids, melanin) typically limits optical signal propagation through thicknesses larger than a few millimeters2. Compared to other visible wavelengths, tissue absorption for red and near-infrared (near-IR) light absorption dramatically decreases and non-elastic scattering becomes the dominant light-tissue interaction mechanism. The relatively recent development of fluorescent agents that absorb and emit light in the near-IR range (600-1000 nm), has driven the development of imaging systems and light propagation models that can achieve whole body three-dimensional imaging in small animals3.
Despite great strides in this area, the ill-posed nature of diffuse fluorescence tomography remains a significant problem for the stability, contrast recovery and spatial resolution of image reconstruction techniques and the optimal approach to FMI in small animals has yet to be agreed on. The majority of research groups have invested in charge-coupled device (CCD)-based systems that provide abundant tissue-sampling but suboptimal sensitivity4-9, while our group and a few others10-13 have pursued systems based on very high sensitivity detectors, that at this time allow dense tissue sampling to be achieved only at the cost of low imaging throughput. Here we demonstrate the methodology for applying single-photon detection technology in a fluorescence tomography system to localize a cancerous brain lesion in a mouse model.
The fluorescence tomography (FT) system employed single photon counting using photomultiplier tubes (PMT) and information-rich time-domain light detection in a non-contact conformation11. This provides a simultaneous collection of transmitted excitation and emission light, and includes automatic fluorescence excitation exposure control14, laser referencing, and co-registration with a small animal computed tomography (microCT) system15. A nude mouse model was used for imaging. The animal was inoculated orthotopically with a human glioma cell line (U251) in the left cerebral hemisphere and imaged 2 weeks later. The tumor was made to fluoresce by injecting a fluorescent tracer, IRDye 800CW-EGF (LI-COR Biosciences, Lincoln, NE) targeted to epidermal growth factor receptor, a cell membrane protein known to be overexpressed in the U251 tumor line and many other cancers18. A second, untargeted fluorescent tracer, Alexa Fluor 647 (Life Technologies, Grand Island, NY) was also injected to account for non-receptor mediated effects on the uptake of the targeted tracers to provide a means of quantifying tracer binding and receptor availability/density27. A CT-guided, time-domain algorithm was used to reconstruct the location of both fluorescent tracers (i.e., the location of the tumor) in the mouse brain and their ability to localize the tumor was verified by contrast-enhanced magnetic resonance imaging.
Though demonstrated for fluorescence imaging in a glioma mouse model, the methodology presented in this video can be extended to different tumor models in various small animal models potentially up to the size of a rat17.

Diffuse fluorescence tomography offers a relatively low-cost and potentially high-throughout approach to preclinical in vivo tumor imaging. The methodology of optical data collection, calibration, and image reconstruction is presented for a computed tomography-guided non-contact time-domain system using fluorescent targeting of the tumor biomarker epidermal growth factor receptor in a mouse glioma model.

Small animal fluorescence molecular imaging (FMI) can be a powerful tool for preclinical drug discovery and development studies1. However, light ...

Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization

The advent of cone-beam computed tomography (CBCT) in the angiography suite has been revolutionary in interventional radiology. CBCT offers 3 dimensional&#160;(3D) diagnostic imaging in the interventional suite and can enhance minimally-invasive therapy beyond the limitations of 2D angiography alone. The role of CBCT has been recognized in transarterial chemo-embolization (TACE) treatment of hepatocellular carcinoma (HCC). The recent introduction of a CBCT technique: dual-phase CBCT (DP-CBCT) improves intra-arterial HCC treatment with drug-eluting beads (DEB-TACE). DP-CBCT can be used to localize liver tumors with the diagnostic accuracy of multi-phasic multidetector computed tomography (M-MDCT) and contrast enhanced magnetic resonance imaging (CE-MRI) (See the tumor), to guide intra-arterially guidewire and microcatheter to the desired location for selective therapy (Reach the tumor), and to evaluate treatment success during the procedure (Treat the tumor). The purpose of this manuscript is to illustrate how DP-CBCT is used in DEB-TACE to see, reach, and treat HCC.

Dual-phase cone-beam computed tomography (DP-CBCT) is a useful intraprocedural imaging technique for transarterial chemo-embolization treatment with drug-eluting beads of hepatocellular carcinoma. DP-CBCT has been used to perform three major steps in oncologic interventional radiology: tumor localization (see), navigation and intraprocedural catheter guidance (reach), and intraprocedural evaluation of treatment success (treat).

The advent of cone-beam computed tomography (CBCT) in the angiography suite has been revolutionary in interventional radiology. CBCT offers 3 ...

High-Resolution Ultrasonography for the Analysis of Orthotopic ATC Tumors in a Genetically Engineered Mouse Model

Anaplastic thyroid carcinoma (ATC) is associated with a poor prognosis and short median survival time, but no effective treatment improves the outcomes significantly. Genetically engineered murine models that mimic ATC&#39;s progression may help researchers to study treatments for this disease. Crossing three different genotypes of mice, a TPO-cre/ERT2; BrafCA/wt; Trp53&#916;ex2-10/&#916;ex2-10&#160;transgenic ATC model was developed. The ATC murine model was induced by an intraperitoneal injection of tamoxifen with overexpression of BrafV600E and deletion of Trp53, and the tumors were generated within about 1 month. High-resolution ultrasound was applied to investigate the tumor initiation and progression, and the dynamic growth curve was obtained by measuring the tumor sizes. Compared to magnetic resonance imaging (MRI) and computed tomography scanning, ultrasound has advantages in observing the ATC murine model, such as being noninvasive, portable, in real-time, and without radiation exposure. High-resolution ultrasound is suitable for dynamic and multiple measurements. However, ultrasonographic examination of the thyroid in mice requires relevant anatomical knowledge and experience. This article provides a detailed procedure for utilizing high-resolution ultrasound to scan tumors in the transgenic ATC model. Meanwhile, ultrasonic parameter adjustment, ultrasound scanning skills, anesthesia and recovery of the animals, and other elements that need attention during the process are listed.

The present protocol describes high-frequency ultrasonography for visualizing the entire mouse thyroid gland and monitoring the growth of anaplastic thyroid carcinoma.

Anaplastic thyroid carcinoma (ATC) is associated with a poor prognosis and short median survival time, but no effective treatment improves the outcomes ...

Cancer Research

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of life and survival of breast cancer patients. In this paper a new approach for the detection of breast cancer is described, based on tracking the mammary architectural elements using diffusion tensor imaging (DTI). 
The paper focuses on the scanning protocols and image processing algorithms and software that were designed to fit the diffusion properties of the mammary fibroglandular tissue and its changes during malignant transformation. The final output yields pixel by pixel vector maps that track the architecture of the entire mammary ductal glandular trees and parametric maps of the diffusion tensor coefficients and anisotropy indices. 
The efficiency of the method to detect breast cancer was tested by scanning women volunteers including 68 patients with breast cancer confirmed by histopathology findings. Regions with cancer cells exhibited a marked reduction in the diffusion coefficients and in the maximal anisotropy index as compared to the normal breast tissue, providing an intrinsic contrast for delineating the boundaries of malignant growth. Overall, the sensitivity of the DTI parameters to detect breast cancer was found to be high, particularly in dense breasts, and comparable to the current standard breast MRI method that requires injection of a contrast agent. Thus, this method offers a completely non-invasive, safe and sensitive tool for breast cancer detection.

We describe how to obtain parametric and vector maps of the diffusion tensor of the breast using magnetic resonance imaging. The protocol and final output following imaging processing are tailored for tracking breast architectural features and detecting breast malignancy.

Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of ...

Patient-Specific Polyvinyl Alcohol Phantom Fabrication with Ultrasound and X-Ray Contrast for Brain Tumor Surgery Planning

Phantoms are essential tools for clinical training, surgical planning and the development of novel medical devices. However, it is challenging to create anatomically accurate head phantoms with realistic brain imaging properties because standard fabrication methods are not optimized to replicate any patient-specific anatomical detail and 3D printing materials are not optimized for imaging properties. In order to test and validate a novel navigation system for use during brain tumor surgery, an anatomically accurate phantom with realistic imaging and mechanical properties was required. Therefore, a phantom was developed using real patient data as input and 3D printing of molds to fabricate a patient-specific head phantom comprising the skull, brain and tumor with both ultrasound and X-ray contrast. The phantom also had mechanical properties that allowed the phantom tissue to be manipulated in a similar manner to how human brain tissue is handled during surgery. The phantom was successfully tested during a surgical simulation in a virtual operating room.
The phantom fabrication method uses commercially available materials and is easy to reproduce. The 3D printing files can be readily shared, and the technique can be adapted to encompass many different types of tumor.

This protocol describes the fabrication of a patient specific skull, brain and tumor phantom. It uses 3D printing to create molds, and polyvinyl alcohol (PVA-c) is used as the tissue mimicking material.

Phantoms are essential tools for clinical training, surgical planning and the development of novel medical devices. However, it is challenging to create ...

Bioengineering

Effective Co-Registration of Two Preclinical Imaging Modalities Across Devices

Multimodal Cross-Device and Marker-Free Co-Registration of Preclinical Imaging Modalities

Integrated preclinical multimodal imaging systems, such as X-ray computed tomography (CT) combined with positron emission tomography (PET) or magnetic resonance imaging (MRI) combined with PET, are widely available and typically provide robustly co-registered volumes. However, separate devices are often needed to combine a standalone MRI with an existing PET-CT or to incorporate additional data from optical tomography or high-resolution X-ray microtomography. This necessitates image co-registration, which involves complex aspects such as multimodal mouse bed design, fiducial marker inclusion, image reconstruction, and software-based image fusion. Fiducial markers often pose problems for in vivo data due to dynamic range issues, limitations on the imaging field of view, difficulties in marker placement, or marker signal loss over time (e.g., from drying or decay). These challenges must be understood and addressed by each research group requiring image co-registration, resulting in repeated efforts, as the relevant details are rarely described in existing publications.
This protocol outlines a general workflow that overcomes these issues. Although a differential transformation is initially created using fiducial markers or visual structures, such markers are not required in production scans. The requirements for the volume data and the metadata generated by the reconstruction software are detailed. The discussion covers achieving and verifying requirements separately for each modality. A phantom-based approach is described to generate a differential transformation between the coordinate systems of two imaging modalities. This method showcases how to co-register production scans without fiducial markers. Each step is illustrated using available software, with recommendations for commercially available phantoms. The feasibility of this approach with different combinations of imaging modalities installed at various sites is showcased.

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

The combination of multiple imaging modalities is often necessary to gain a comprehensive understanding of pathophysiology. This approach utilizes phantoms to generate a differential transformation between the coordinate systems of two modalities, which is then applied for co-registration. This method eliminates the need for fiducials in production scans.

Integrated preclinical multimodal imaging systems, such as X-ray computed tomography (CT) combined with positron emission tomography (PET) or magnetic ...

Image Acquisition using Portable Sonography for Emergency Airway Management

With its increasing popularity and accessibility, portable ultrasonography has been rapidly adapted not only to improve the perioperative care of patients, but also to address the potential benefits of employing ultrasound in airway management. The benefits of point of care ultrasound (POCUS) include its portability, the speed at which it can be utilized, and its lack of invasiveness or exposure of the patient to radiation of other imaging modalities.
Two primary indications for airway POCUS include confirmation of endotracheal intubation and identification of the cricothyroid membrane in the event a surgical airway is required. In this article, the technique of using ultrasound to confirm endotracheal intubation and the relevant anatomy is described, along with the associated ultrasonographic images. In addition, identification of the anatomy of the cricothyroid membrane and the ultrasonographic acquisition of appropriate images to perform this procedure are reviewed.
Future advances include utilizing airway POCUS to identify patient characteristics that might indicate difficult airway management. Traditional bedside clinical exams have, at best, fair predictive values. The addition of ultrasonographic airway assessment has the potential to improve this predictive accuracy. This article describes the use of POCUS for airway management, and initial evidence suggests that this has improved the diagnostic accuracy of predicting a difficult airway. Given that one of the limitations of airway POCUS is that it requires a skilled sonographer, and image analysis can be operator dependent, this paper will provide recommendations to standardize the technical aspects of airway ultrasonography and promote further research utilizing sonography in airway management. The goal of this protocol is to educate researchers and medical health professionals and to advance the research in the field of airway POCUS.

Point of care ultrasound (POCUS) is increasingly being utilized in airway management. Presented here are some clinical utilities of POCUS, including differentiating endotracheal and esophageal intubation, identification of the cricothyroid membrane in the event a surgical airway is required, and measuring anterior neck soft tissue to predict difficult airway management.

With its increasing popularity and accessibility, portable ultrasonography has been rapidly adapted not only to improve the perioperative care of ...

A Personalized 3D-Printed Model for Preoperative Evaluation in Thyroid Surgery

The anatomic structure of the surgical area of thyroid cancer is complex. It is very important to comprehensively and carefully evaluate the tumor location and its relation with the capsule, trachea, esophagus, nerves, and blood vessels before operation. This paper introduces an innovative 3D-printed model establishment method based on computerized tomography (CT) DICOM images. We established a personalized 3D-printed model of the cervical thyroid surgery field for each patient who needed thyroid surgery to help clinicians evaluate the key points and difficulties of the surgery and select the operation methods of key parts as a basis. The results showed that this model is conducive to preoperative discussion and the formulation of operation strategies. In particular, as a result of the clear display of the recurrent laryngeal nerve and parathyroid gland locations in the thyroid operation field, injury to them can be avoided during surgery, the difficulty of thyroid surgery reduced, and the incidence of postoperative hypoparathyroidism and complications related to recurrent laryngeal nerve injury reduced too. Moreover, this 3D-printed model is intuitive and aids communication for the signing of informed consent by patients before surgery.

Here, a new method of establishing a personalized 3D-printed model for preoperative evaluation of thyroid surgery is proposed. It is conducive to preoperative discussion, reducing the difficulty of thyroid surgery.

The anatomic structure of the surgical area of thyroid cancer is complex. It is very important to comprehensively and carefully evaluate the tumor ...

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

In recent years, the incidence of thyroid cancer has been increasing. Thyroid nodule detection is critical for both the detection and treatment of thyroid cancer. Convolutional neural networks (CNNs) have achieved good results in thyroid ultrasound image analysis tasks. However, due to the limited valid receptive field of convolutional layers, CNNs fail to capture long-range contextual dependencies, which are important for identifying thyroid nodules in ultrasound images. Transformer networks are effective in capturing long-range contextual information. Inspired by this, we propose a novel thyroid nodule detection method that combines the Swin Transformer backbone and Faster R-CNN. Specifically, an ultrasound image is first projected into a 1D sequence of embeddings, which are then fed into a hierarchical Swin Transformer. 
The Swin Transformer backbone extracts features at five different scales by utilizing shifted windows for the computation of self-attention. Subsequently, a feature pyramid network (FPN) is used to fuse the features from different scales. Finally, a detection head is used to predict bounding boxes and the corresponding confidence scores. Data collected from 2,680 patients were used to conduct the experiments, and the results showed that this method achieved the best mAP score of 44.8%, outperforming CNN-based baselines. In addition, we gained better sensitivity (90.5%) than the competitors. This indicates that context modeling in this model is effective for thyroid nodule detection.

Here, a new model for thyroid nodule detection in ultrasound images is proposed, which uses Swin Transformer as the backbone to perform long-range context modeling. Experiments prove that it performs well in terms of sensitivity and accuracy.

In recent years, the incidence of thyroid cancer has been increasing. Thyroid nodule detection is critical for both the detection and treatment of thyroid ...

Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer

The diagnosis and treatment of locally advanced thyroid carcinoma are challenging. The challenge lies in the evaluation of the tumor scope and the formulation of an individualized treatment plan. Three-dimensional (3D) visualization has a wide range of applications in the field of medicine, although there are limited applications in thyroid cancer. We previously applied 3D visualization for the diagnosis and treatment of thyroid cancer. Through data collection, 3D modeling, and preoperative evaluation, we can obtain 3D information regarding the tumor outline, determine the extent of tumor invasion, and conduct adequate preoperative preparation and surgical risk assessment. This study aimed to demonstrate the feasibility of 3D visualization in locally advanced thyroid cancer. Computer-aided 3D visualization can be an effective method for accurate preoperative evaluation, the development of surgical methods, shortening the surgical time, and reducing the surgical risks. Furthermore, it can contribute to medical education and doctor-patient communication. We believe that the application of 3D visualization technology can improve outcomes and quality of life in patients with locally advanced thyroid cancer.

In diagnosing and treating locally advanced thyroid cancer, the application of computer-aided three-dimensional reconstruction can provide additional information regarding the tumor scope and anatomic characteristics, thereby assisting in risk assessment and surgical planning.

Synchronous Triplanar Reconstruction Integrated with Color Doppler Mapping for Precise and Rapid Localization of Thyroid Lesions

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