Non-invasive Amide Proton Transfer Imaging and ZOOM Diffusion-Weighted Imaging in Differentiating Benign and Malignant Thyroid Micronodules

Multiplexed sensitivity-encoding versus single-shot echo-planar imaging: a comparative study for diffusion-weighted imaging of the thyroid lesions

PURPOSE

To compare multiplexed sensitivity-encoding diffusion-weighted magnetic resonance imaging (MUSE-DWI) and conventional DWI (cDWI) techniques in thyroid MRI.

MATERIALS AND METHODS

Nineteen patients who underwent thyroid MRI using both MUSE-DWI and cDWI at a 3.0 T MRI system were enrolled. Qualitative parameters (image quality, thyroid contour, and lesion conspicuity) and quantitative parameters (signal-to-noise ratio (SNR), lesion-to-thyroid contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC)) were compared between the two sequences. In addition, ADC values derived from MUSE-DWI and cDWI were separately compared between benign and malignant lesions.

RESULTS

MUSE-DWI outperformed cDWI in terms of image quality, thyroid contour, and lesion conspicuity. Significantly, higher signal-to-noise ratio (SNR) in both the thyroid and its lesion were found in MUSE-DWI than those in cDWI (both P < 0.05). The lesion-to-thyroid contrast-to-noise ratio (CNR) values were also significantly higher in MUSE-DWI than those in cDWI (P < 0.05). The apparent diffusion coefficient (ADC) of the thyroid in MUSE-DWI was significantly lower than that in cDWI (P < 0.05). The ADC of the lesion in MUSE-DWI was also significantly lower than that in cDWI (P < 0.05). In addition, ADC values derived from MUSE-DWI and cDWI were significantly higher in benign lesions than malignant lesions (P < 0.05).

CONCLUSION

Compared with cDWI, MUSE-DWI can improve the image quality, thyroid contour sharpness, lesion conspicuity, SNR in both the thyroid and its lesions, and enhancing the CNR between lesions and thyroid.

Diagnostic value of cervical spine ZOOM-DWI in cervical spondylotic myelopathy

PURPOSE

To investigate the clinical application value of the non-shared incentive diffusion imaging technique (ZOOM-DWI) diagnoses of cervical spondylotic myelopathy (CSM).

METHODS

49 CSM patients who presented from January 2022 to December 2022 were selected as the patient group, and 50 healthy volunteers are recruited as the control group. All subjects underwent conventional MRI and ZOOM-DWI of the cervical spine and neurologic mJOA scores in patients with CSM. The spinal ADC values of segments C2-3, C4-5, C5-6, and C6-7 are measured and analyzed in all subjects, with C5-6 being the most severe level of spinal canal compression in the patient group. In addition, the study also analyzes and compares the relationship between the C5-6 ADC value and mJOA score in the patient group.

RESULTS

The mean ADC shows no significantly different levels in the control group. Among the ADC values at each measurement level in the patient group, except for C4-5 and C6-7 segments are not statistically significant, the remaining pair-wise comparisons all show statistically significant differences (F = 24.368, p < 0.001). And these individuals have the highest ADC value at C5-6. The C5-6 ADC value in the patient group is significantly higher compared with the ADC value in the control group (t = 9.414, p < 0.001), with statistical significance. The ADC value at the patient stenosis shows a significant negative correlation with the mJOA score (r = -0.493, p < 0.001).

CONCLUSION

Cervical ZOOM-DWI can be applied to diagnose CSM, and spinal ADC value can use as reliable imaging data for diagnosing cervical myelopathy.

The Application of Artificial Intelligence in Thyroid Nodules: A Systematic Review Based on Bibliometric Analysis

BACKGROUND

Thyroid nodules are common lesions in benign and malignant thyroid diseases. More and more studies have been conducted on the feasibility of artificial intelligence (AI) in the detection, diagnosis, and evaluation of thyroid nodules. The aim of this study was to use bibliometric methods to analyze and predict the hot spots and frontiers of AI in thyroid nodules.

METHODS

Articles on the application of artificial intelligence in thyroid nodules were retrieved from the Web of Science core collection database. A website (https://bibliometric.com/), VOSviewer and CiteSpace software were used for bibliometric analyses. The collaboration maps of countries and institutions were analyzed. The cluster and timeline view based on cocitation references and keywords citation bursts visualization map were generated.

RESULTS

The study included 601 papers about AI in thyroid nodules. China contributed to more than half (52.41%) of these publications. The cluster view and timeline view of co-citation references were assembled into 9 clusters, "AI", "deep learning", "papillary thyroid carcinoma", "radiomics", "ultrasound image", "biomarkers", "medical image segmentation", "central lymph node metastasis (CLNM)", and "self-organizing auto-encoder". The "AI", "radiomics", "medical image segmentation", "deep learning", and "CLNM", emerging in the last 10 years and continuing until recent years.

CONCLUSION

An increasing number of scholars were devoted to this field. The potential future research hotspots include risk factor assessment and CLNM prediction of thyroid carcinoma based on radiomics and deep learning, automatic segmentation based on medical images (especially ultrasound images).

Comparing the clinical utility of single-shot, readout-segmented and zoomit echo-planar imaging in diffusion-weighted imaging of the kidney at 3 T

We compared the clinical utility of single-shot echo-planar imaging (SS-EPI) using different breathing schemes, readout-segmented EPI and zoomit EPI in the repeatability of apparent diffusion coefficient (ADC) measurements, cortico-medullary contrast to noise ratio (c-mCNR) and image quality. In this institutional review board-approved prospective study, some common clinically applicable diffusion-weighted imaging (b = 50, 400, 800 s/mm²) of kidney on 3.0 T MRI were performed on 22 volunteers using SS-EPI with breath-hold diffusion-weighted imaging (BH-DWI), free-breathing (FB-DWI), navigator-triggered (NT-DWI) and respiratory-triggered (RT-DWI), readout-segmented DWI (RS-DWI), and Zoomit DWI (Z-DWI). ADC and c-mCNR were measured in 12 anatomic locations (the upper, middle, and lower pole of the renal cortex and medulla), and image quality was assessed on these DWI sequences. A DWI with the optimal clinical utility was decided by systematically assessing the ADC repeatability, c-mCNR and image quality among the DWIs. For ADC measurements, Z-DWI had an excellent intra-observer agreement (intra-class correlation coefficients (ICCs): 0.876–0.944) and good inter-observer agreement (inter-class ICCs: 0.798–0.856) in six DWI sequences. Z-DWI had the highest ADC repeatability in most of the 12 anatomic locations of the kidneys (mean ADC absolute difference: 0.070–0.111 × 10⁻³ mm²/s, limit of agreement: 0.031–0.056 × 10⁻³ mm²/s). In all DWIs, Z-DWI yielded a slightly higher c-mCNR than other DWIs in most representative locations (P > 0.05), which was significantly higher than BH-DWI and FB-DWI in the middle pole of both kidneys and the upper pole of the left kidney (P < 0.05). In addition, Z-DWI yielded image quality that was similar to RT-DWI and NT-DWI (P > 0.05) and superior to BH-DWI, FB-DWI and RS-DWI (P < 0.05). Our results suggest that Z-DWI provides the highest ADC reproducibility, better c-mCNR and good image quality on 3.0 T MRI, making it the recommended sequence for clinical DWI of the kidney.

Baseline Amide Proton Transfer Imaging at 3T Fails to Predict Early Response to Induction Chemotherapy in Nasopharyngeal Carcinoma

Background

Early identification of nasopharyngeal carcinoma (NPC) patients with high risk of failure to induction chemotherapy (IC) would facilitate prompt individualized treatment decisions and thus reduce toxicity and improve overall survival rate. This study aims to investigate the value of amide proton transfer (APT) imaging in predicting short-term response of NPC to IC and its potential correlation with well-established prognosis-related clinical characteristics.

Methods and Materials

A total of 80 pathologically confirmed NPC patients receiving pre-treatment APT imaging at 3T were retrospectively enrolled. Using asymmetry analysis, APT maps were calculated with mean (APT_mean), 90^th percentile (APT₉₀) of APT signals in manually segmented NPC measured. APT values were compared among groups with different histopathological subtypes, clinical stages (namely, T, M, N, and overall stages), EBV-related indices (EBV-DNA), or responses to induction chemotherapy, using Mann–Whitney U test or Kruskal–Wallis H test.

Results

NPC showed significantly higher APT_mean than normal nasopharyngeal tissues (1.81 ± 0.62% vs.1.32 ± 0.56%, P <0.001). APT signals showed no significant difference between undifferentiated and differentiated NPC subtypes groups, different EBV-DNA groups, or among T, N, M stages and overall clinical stages of II, III, IVA and IVB (all P >0.05). Similarly, baseline APT-related parameters did not differ significantly among different treatment response groups after IC, no matter if evaluated with RECIST criteria or sum volumetric regression ratio (SVRR) (all P >0.05).

Conclusion

NPC showed significantly stronger APT effect than normal nasopharyngeal tissue, facilitating NPC lesion detection and early identification. However, stationary baseline APT values exhibited no significant correlation with histologic subtypes, clinical stages and EBV-related indices, and showed limited value to predict short-term treatment response to IC.

Dynamic Change of Amide Proton Transfer Imaging in Irradiated Nasopharyngeal Carcinoma and Related Histopathological Mechanism

OBJECTIVE

To investigate the dynamic change of amide proton transfer (APT) imaging before and after irradiation in nasopharyngeal carcinoma (NPC) and the underlying histopathological mechanism.

MATERIALS AND METHODS

Tumor-bearing BALB/C nude mouse models were established and randomly divided into three groups: high-dose group (20 Gy/2 fractions), low-dose group (10 Gy/2 fractions), and control group (0 Gy). MRI scanning was performed before irradiation and 3rd, 6th, and 9th day post-irradiation. Scanning sequence included T1 weighted, T2 weighted, and APT. HE staining and TUNEL immunofluorescence detection were performed to detect necrosis and apoptosis.

RESULTS

After high-dose irradiation, the mean tumor APT values decreased significantly on the 3rd day and 6th day (from 3.83 before radiotherapy to 2.41%, P < 0.001, 3rd day; from 2.41 to 1.80%, P = 0.001, 6th day). For low-dose irradiation, the mean tumor APT values decreased slightly on the 3rd day and 6th day (from 3.52 to 3.13%, P = 0.109, 3rd day; from 3.13 to 3.05%, P = 0.64, 6th day). The mean APT values of nonirradiated tumor changed slightly. In contrast, the average volume of high-dose irradiated tumors did not decrease obviously until the 9th day post-irradiation (from 290 before radiotherapy to 208 mm3 on the 9th day). The low-dose irradiated tumors showed slow growth, and the nonirradiated tumors showed rapid growth. Subsequent HE staining and TUNEL staining showed obvious necrosis characteristics and higher proportion of positive apoptotic cell nucleus in high-dose irradiated tumors, but not nonirradiated tumors.

CONCLUSION

The APT signal intensity decreased after irradiation, which is earlier than the change of tumor volume. What is more, the decrease of APT signal intensity is more significant in high-dose group. Histological analysis showed obvious apoptosis and necrosis histological characteristic in irradiated tumor, which may explain the decrease of APT signal intensity. These results indicate that APT imaging has the potential to serve as a reliable biomarker for response assessment in NPC.

Discrimination between malignant and benign thyroid tumors by diffusion-weighted imaging - A systematic review and meta analysis

PURPOSE

Magnetic resonance imaging is used to stage thyroid tumors. Diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) can be used to reflect tumor microstructure. Our aim was to compare ADC values of malignant and benign thyroid lesions based on a large sample.

METHODS

MEDLINE library, EMBASE and SCOPUS databases were screened for the associations between ADC values and thyroid lesions up to August 2021. The primary endpoint of the systematic review were ADC values of benign and malignant thyroid lesions. In total, 29 studies were suitable for the analysis and were included into the present study.

RESULTS

The included studies comprised a total of 2137 lesions, 1118 (52.3%) benign and 1019 (47.7%) malignant lesions. The pooled mean ADC value of the benign thyroid lesions was 1.88 × 10^-3 mm²/s [95% CI 1.77-2.0] and the pooled mean ADC value of malignant thyroid lesions was 1.15 × 10^-3 mm²/s [95% CI 1.04-1.25].

CONCLUSIONS

ADC can well discriminate benign and malignant thyroid tumors. Therefore, DWI should be implemented into the presurgical diagnostic work-up in clinical routine.

Applying Amide Proton Transfer-Weighted Imaging (APTWI) to Distinguish Papillary Thyroid Carcinomas and Predominantly Solid Adenomatous Nodules: Comparison With Diffusion-Weighted Imaging

Background: Amide proton transfer-weighted (ATPw) imaging is a novel MRI technique that has been used to identify benign and malignant tumors. The present study evaluated the role of APTw imaging in differentiating papillary thyroid carcinoma from predominantly solid adenomatous nodule.

Methods: This study included 24 cases of solitary papillary thyroid carcinoma, and 20 cases of solid adenomatous nodules. Normal thyroid tissues were examined in 12 healthy subjects. The healthy subjects, eight cases of adenomatous nodule with cystic degeneration, and 12 cases of thyroid goiter, were only considered in the descriptive analysis, not included in our statistical analysis. The mean APTw value and the apparent diffusion coefficients (ADCs) of papillary thyroid carcinoma and solid adenomatous nodule were compared via a Mann-Whitney U test and receiver operating characteristic (ROC)-curve analyses.

Results: The adenomatous nodule (3.3 ± 1.3%) exhibited significantly higher APTw value (p < 0.05) than that of the papillary thyroid carcinoma (1.8 ± 0.7%). The optimal cut-off value of the mean APTw value in differentiating papillary thyroid carcinoma from adenomatous nodule was 3.15%, with a sensitivity of 60% and a specificity of 100%. The mean ADC of papillary thyroid carcinoma (1.2 ± 0.2 × 10⁻³ mm²/s) was significantly lower than that of adenomatous nodule (2.0 ± 0.4 × 10⁻³ mm²/s). The optimal cut-off value of the mean ADC was 1.35 × 10⁻³ mm²/s, with a sensitivity of 100% and a specificity of 75%. Based on the ROC-curve analysis of APT and ADC, the ADC showed a higher area under the curve (AUC) than that of APT (AUC_APT = 0.84, AUC_ADC = 0.95).

Conclusion: APTw imaging may be as useful as DWI for the differentiation of papillary thyroid carcinoma from predominantly solid adenomatous nodule. Although the sensitivity of ADC was greater than that of APT, APT had greater specificity.