Current Medical Imaging - Volume 20, Issue 1, 2024

It has been reported in the literature that Vitamin D can inhibit the growth of uterine fibroids, but the evaluation index is only the size of the uterine fibroids. The purpose of this study was to evaluate the effect of vitamin D on the size, hardness, and blood flow of uterine fibroids in pre-menopausal women by multimodal ultrasound.

A total of 64 pre-menopausal women with uterine fibroids complicated vitamin D deficiency were enrolled in this study and randomly divided into two groups: the vitamin D group (n=32) which received oral vitamin D (1600 IU/ day) and the control group (n=32) without vitamin D supplementation. After three months of intervention, the mean diameter of uterine fibroids, elastic strain ratio, and blood flow grade were evaluated by multimodal ultrasound, and the clinical symptoms of the two groups were evaluated by questionnaire.

The vitamin D group reported a significant increment in the serum 25-hydroxyvitamin D (P < 0.001). In addition, there were significant reductions in the mean diameter, and elastic strain ratio of uterine fibroids (P =.043 and P =.038, respectively), but no significant difference in the blood flow grade of uterine fibroids was observed (P =.272). Compared with the control group, the vitamin D group achieved significant relief in dysmenorrhea and frequent urination, as well as improvement in heavy menstrual bleeding.

The application of multimodal ultrasound provides a more comprehensive theoretical basis for vitamin on uterine fibroids. Vitamin D can effectively reduce the size of uterine fibroids in pre-menopausal women and relieve their symptoms. It is highly likely to be a promising, safe, effective, and inexpensive drug for uterine fibroids, which has good application value and promotion prospects.

Osteoarthritis is a condition that poses a risk to the knee joint, resulting in pain and impaired function. However, traditional knee X-ray evaluations using the Kellgren-Lawrence grading system have proven to be inefficient. These evaluations are subjective, time-consuming, and labor-intensive, particularly in busy hospital settings.

The objective of this research was to present a deep learning-based approach that can detect knee joint regions in medical images. By addressing the limitations of traditional methods, the aim was to develop a more efficient and automated approach for knee joint analysis.

The proposed method utilizes the Faster R-CNN model, which consists of a region proposal network (RPN) and Fast R-CNN. The RPN generates region proposals that potentially contain knee joint regions, while the Fast R-CNN network categorizes and extracts features from these proposals. To train the model, a dataset of knee joint images was employed. The performance of the model was evaluated using metrics, such as accuracy, precision, recall, F1-score, and mean IoU (Intersection Over Union).

The results demonstrated the high accuracy of the proposed method in detecting knee joint regions. The model achieved a mean IoU of 94.5, indicating a strong overlap between the predicted and ground truth regions. These findings highlight the potential of deep learning-based approaches in automating medical image analysis, specifically in the diagnosis and management of knee joint disorders.

This study emphasizes the significance of leveraging advanced technologies, such as deep learning, in medical imaging. By developing more efficient and accurate methods for identifying knee joint regions in medical images, it becomes feasible to enhance patient outcomes and healthcare delivery. The proposed deep learning-based approach showcases promising results, paving the way for further advancements in the field of medical image analysis and contributing to improved diagnostic capabilities for knee joint disorders.

The aim of this study was to explore the criteria that can predict bladder cancer among the lesions that could not be differentiated from intravesical prostate protrusion (IPP) and to create a scoring system using these criteria.

A retrospective analysis was made of patients with an ultrasound report indicating lesions in the bladder neck, for which differentiation between bladder cancer and IPP could not be determined. A total of 174 patients diagnosed with bladder cancer (n=102) or benign prostate lesion (n=72) according to the biopsy results were enrolled in the study. Hemoglobin, prostate-specific antigen (PSA), prostate volume (PV), bladder wall thickness (BWT), lesion height (LH), and the ratio of lesion width to base (LW/B) were compared between the two groups.

ROC analysis revealed an AUC value >0.7 for all factors, and the best cut-off value was identified for each factor. In the multivariate analysis, by determining a score for each factor according to the ORs, the BCa-IPP scoring system was developed to provide a total score in the range of minimum 0 and maximum 15. In the ROC analysis, the AUC value was 0.954 (95% CI: 0.923–0.986) for the BCa-IPP score. The best cut-off value was found to be 10, with sensitivity of 0.93 and specificity of 0.85.

Using simple laboratory and ultrasound findings, the BCa-IPP scoring system was created, which was seen to have high predictive value and can be easily applied in the clinic. The BCa-IPP scoring system is a non-invasive test that can be successfully applied for the differentiation of bladder cancer from benign lesions.

Rheumatoid Arthritis Magnetic Resonance Imaging Score (RAMRIS) is usually used for the semi-quantitative evaluation of joint changes in Rheumatoid Arthritis (RA). However, this method cannot evaluate early changes in bone marrow edema (BME).

To determine whether T1 mapping of wrist BME predicts early treatment response in RA.

This study prospectively enrolled 48 RA patients administered oral anti-rheumatic drugs. MRI of the most severely affected wrist was performed before and after 4 (48 patients) and 8 weeks of treatment (38 patients). Mean T1 values of BME in the lunate, triangular, and capitate bones; RAMRIS for each wrist; Erythrocyte-Sedimentation Rate (ESR); and 28-joint Disease Activity Score (DAS28)-ESR score were analyzed. Patients were divided into responders (4 weeks, 30 patients; 8 weeks, 32 patients) and non-responders (4 weeks, 18 patients; 8 weeks, 6 patients), according to EULAR response criteria. Receiver operating characteristic (ROC) curves were used to evaluate the efficacy of T1 values.

ESR and DAS28-ESR were not correlated with T1 value and RAMRIS at each examination (P > 0.05). Changes in T1 value and DAS28-ESR relative to the baseline were moderately positively correlated with each other at 4 and 8 weeks (r = 0.555 and 0.527, respectively; P < 0.05). At 4 weeks, the change and rate of change in T1 value significantly differed between responders and non-responders (-85.63 vs. -19.92 ms; -12.89% vs. -2.81%; P < 0.05). The optimal threshold of the rate of change in T1 value at 4 weeks for predicting treatment response was -5.32% (area under the ROC curve, 0.833; sensitivity, 0.900; specificity, 0.667).

T1 mapping provides a new imaging method for monitoring RA lesions; changes in wrist BME T1 values reflect early treatment response.

This study sought to analyze the ¹⁸F-FDG PET/CT and contrast-enhanced computed tomography (CT) images of synchronous colorectal cancer (CRC) and renal clear cell carcinoma (ccRCC) and identify the shared genes between these two types of cancer through bioinformatic analysis.

A retrospective analysis was conducted on a patient with synchronous CRC and ccRCC who underwent ¹⁸F-FDG PET/CT and contrast-enhanced CT before treatment. Databases were analyzed to identify differentially expressed genes between CRC and ccRCC, and co-expression genes were extracted for RCC and CRC.

¹⁸F-FDG PET/CT revealed intense metabolic activity in the primary colorectal lesion (SUVmax 13.2), while a left renal mass (diameter = 35 mm) was observed with no significant uptake. Contrast-enhanced CT during the arterial phase showed heterogeneous intense enhancement of the renal lesion, and the lesion washed out earlier than in the renal cortex in the nephrographic and excretory phases, indicating ccRCC. The histopathological results confirmed synchronous double primary malignant tumors. Our bioinformatic analysis results showed that synchronous occurrence of CRC and ccRCC may correlate with simultaneous expression of Carbonic Anhydrase 9 (CA9), integrin-binding sialoprotein (IBSP), and Fibrinogen γ chain (FGG).

¹⁸F-FDG PET/CT combined with contrast-enhanced CT is an effective diagnostic tool in evaluating synchronous CRC and RCC. By analyzing this clinical case and conducting bioinformatic analysis, we improved our current understanding of the mechanisms underlying synchronous tumors.

The aim of this study is to evaluate (i) the reasons for requesting ultrasonography (USG) in a dentistry faculty and (ii) the scanning regions, the type of probe used, and the use of Doppler USG.

USG request forms of patients who applied to our radiology clinic for USG were analyzed retrospectively. According to the clinical information of the patients in the request forms, the reasons for requesting USG were divided into four groups: soft tissue swelling, soft tissue calcification, lymph node, and other examinations. Data were statistically compared between sex (female and male) and age groups (≤40−years−old and ˃40−years−old).

The USG request forms of 50 patients were obtained. The mean patient age was 45.06±14.50 years. Twenty-six patients were female (52%), while twenty-four patients were male (48%). Soft tissue swelling, soft tissue calcification, lymph node, and other examinations were noted as the reasons for requesting USG in 42%, 26%, 18%, and 14% of the patients, respectively. The most scanned regions were the submandibular (56%), parotid (16%), and cheek (10%) regions. Extraoral probe was used more frequently than intraoral probe (78% vs. 22%). Doppler USG was used in most patients (98%). A statistically significant difference was found between age groups and calcification examination (p<0.05).

The reasons for requesting USG were mostly soft tissue swelling, soft tissue calcification, and lymph node examinations. The most commonly scanned region and used type of probe were the submandibular region and extraoral probe, respectively. Doppler USG was used in most patients.

High-altitude pulmonary edema (HAPE) is a serious life-threatening disease that occurs after rapid ascent to high altitude; its main early-stage presentations include fatigue, headache, low-grade fever, dyspnea, and cough. X-ray and computed tomography (CT) images show pulmonary shadows and patches, which may be localized (initial right lung field predomination) or generalized to the bilateral lung base.

In this report, we present a case of a 25-year-old man diagnosed with HAPE combined with spontaneous pneumomediastinum. After a quick descent and effective medical treatment, this patient made a full recovery. The case may provide helpful information for the prevention and treatment of this disease since an increased number of people, especially young men, currently travel and work at high altitudes.

After accurate clinical diagnosis with the help of CT or X-ray, immediate descent and appropriate oxygen supplementation are the most effective treatments for HAPE at high altitude.

Non-neoplastic liver lesions show low signal intensity in the hepatobiliary phase (HBP) of gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI) after biliary stenting and require differentiation from liver metastases.

The study aimed to evaluate the imaging findings and clinical association of non-neoplastic liver lesions showing hypointensity in the HBP of EOB-MRI after biliary stenting, and assess their differentiation from liver metastases.

This study included 30 patients who underwent EOB-MRI after biliary stenting for pancreaticobiliary malignancies. Among these, 7 patients had pathologically diagnosed non-neoplastic liver lesions, which appeared hypointense in the HBP, and were categorized into the non-neoplastic group. The remaining 23 patients without non-neoplastic liver lesions were included in the control group. Additionally, 29 patients with liver metastasis were included in the liver metastasis group. Clinical associations and imaging features were compared between the groups.

A history of cholangitis and two or more biliary interventional procedures were significantly more frequently observed in the non-neoplastic group (p=0.002 and p=0.01, respectively) than in the control groups. Regarding the imaging findings, the liver-to-lesion signal intensity ratio in the HBP in the liver metastasis group was significantly higher than that in the non-neoplastic group (2.13 vs. 1.53, p=0.002). Additionally, liver metastases were visualized significantly more clearly on diffusion-weighted images (p=0.033) and HBP images (p<0.001) in comparison to non-neoplastic lesions.

Non-neoplastic liver lesions due to biliary inflammation may be observed in the HBP of EOB-MRI in patients after biliary stenting. These lesions may be associated with a history of cholangitis and repeated biliary intervention procedure, and need to be differentiated from liver metastases.

Generative adversarial networks (GANs) have demonstrated superior data generation capabilities compared to other methods, making them popular for use in medical image applications. These features have intrigued researchers in the medical imaging field, resulting in a swift implementation of these techniques in various conventional and novel applications such as image reconstruction, segmentation, detection, classification, and cross-modality synthesis. A comprehensive review of recent medical imaging breakthroughs will benefit researchers interested in this field. In this review, we aimed to introduce the origin, principle, and extended forms of GANs and summarize the state-of-the-art progress of GAN-based medical image processing methods.

We searched the literature for studies on Google Scholar and PubMed using the keywords “Segmentation,” “Classification,” “medical image,” and “generative adversarial network.” Specifically, the initial search revealed 5423 publications after the removal of duplicated and non-accessible full-text publications. Then, after the title and abstract screening, 680 underwent full-text screening. Finally, 121 studies were included in our final analysis after full-text screening.

The date range of the studies covered in this review is from January 1, 2017, to the present. After a thorough screening and qualification assessment, 121 studies involving GAN-based applications in seven areas of medical images were included in the final methodological review. These areas included synthesis, classification, segmentation, conversion, reconstruction, denoising, and lesion detection. We further classified and summarized these papers into clinical applications, classification methods, and imaging modalities.

We thoroughly examined the latest research progress of GAN-based medical image augmentation. These techniques effectively alleviate the challenge of limited training samples for medical image diagnosis and treatment models. Furthermore, several critical issues associated with GANs, such as pattern collapse, instability, and lack of interpretability, require attention in future research.

The objective of this study was to analyze the relationship between quantitative parameters of spectral CT and the Ki67 expression index of tumor cells in hepatocellular carcinoma (HCC).

A total of 19 patients who underwent preoperative spectral CT dual-phase enhancement and who were diagnosed with HCC by postoperative pathology were prospectively selected. Patients with ≥10% Ki67-positive tumor cells formed a high-Ki67 group, and those with <10% Ki67-positive cells formed a low-Ki67 group. The iodine concentrations (ICs) of the lesion and the descending aorta were measured during the arterial and venous phases. Relative iodine concentration (RIC) was calculated thus: RIC=IClesion/ICdescending aorta. CT values of the lesions at 40 and 70 keV were measured during the enhanced arterial and venous phases. The slope of the spectral curve (λ) was calculated thus: λ = (40 keV-70 keV) /(70-30). To compare the differences in quantitative parameters between the high- and low-Ki67 groups, either an independent samples t-test (normal distribution) or a Mann–Whitney U test (non-normal distribution) was used. Receiver operating characteristic curves were used to evaluate the effectiveness of spectral CT parameters in distinguishing between high-Ki67 and low-Ki67 groups. Pearson correlation analysis was used to evaluate the correlation between spectral CT quantitative parameters and Ki67 expression.

IC, RIC and λ values for the high-Ki67 group in arterial and venous phases were higher than those for the low-Ki67 group, P < 0.05. IC, RIC, and λ values in the arterial phase were 0.83, 0.89, and 0.75, respectively; in the venous phase, the values of these three parameters were 0.76, 0.77, and 0.69, respectively. IC, RIC, and λ were positively correlated with Ki67 expression in both arterial and venous phases, with a highest correlation of 0.82 for arterial-phase RIC.

The quantitative parameters of spectral CT in HCC were correlated with Ki67 expression. This finding may make it easier for clinicians to determine whether a tumor is high or low in Ki67 before surgery.

The use of breast MRI for screening has increased over the past decade, mostly in women with a high risk of breast cancer. Abbreviated breast MRI (AB-MR) is introduced to make MRI a more accessible screening modality. AB-MR decreases scanning and reporting time and the overall cost of MRI.

This study aims to evaluate the diagnostic efficacy of abbreviated MRI protocol in detecting breast cancer in screening and diagnostic populations, using histopathology as the reference standard.

This is a single-centre retrospective cross-sectional study of 134 patients with 198 histologically proven breast lesions who underwent full diagnostic protocol contrast-enhanced breast MRI (FDP-MR) at the University Malaya Medical Centre (UMMC) from 1st January 2018 to 31st December 2019. AB-MR was pre-determined and evaluated with regard to the potential to detect and exclude malignancy from 3 readers of varying radiological experiences. The sensitivity of both AB-MR and FDP-MR were compared using the McNemar test, where both protocols' diagnostic performances were assessed via the receiver operating characteristic (ROC) curve. Inter-observer agreement was analysed using Fleiss Kappa.

There were 134 patients with 198 lesions. The average age was 50.9 years old (range 27 – 80). A total of 121 (90%) MRIs were performed for diagnostic purposes. Screening accounted for 9.4% of the cases, 55.6% (n=110) lesions were benign, and 44.4% (n=88) were malignant. The commonest benign and malignant lesions were fibrocystic change (27.3%) and invasive ductal carcinoma (78.4%). The mean sensitivity, specificity, positive predictive value, and negative predictive value for AB-MR were 0.96, 0.57, 0.68 and 0.94, respectively. Both AB-MR and FDP-MR showed excellent diagnostic performance with AUC of 0.88 and 0.96, respectively. The general inter-observer agreement of all three readers for AB-MR was substantial (k=0.69), with fair agreement demonstrated between AB-MR and FDP-MR (k=0.36).

The study shows no evidence that the diagnostic efficacy of AB-MR is inferior to FDP-MR. AB-MR, with high sensitivity, has proven its capability in cancer detection and exclusion, especially for biologically aggressive cancers.

The diagnosis and quantification of early-stage alcoholic liver fibrosis (ALF) are vital and the objective is to establish a noninvasive PET technique to quantify the collagenogenesis of hepatic stellate cells (HSC) in an ALF mouse model.

To establish the ALF animal model, a liquid alcohol diet (8 weeks), and CCl4 were injected intraperitoneally at 5-8 weeks. A liquid scintillation counter was used to measure [³H]proline uptake by rats HSC in vitro experiment. Collagen type 1 production was tested by ELISA in a culture medium. The expression of type 1 collagen and proline transporters in ex vivo experiments was compared between ALF rats and mice. Different doses of unlabeled proline and benztropine were ex vivo quantified [³H]proline in liver tissues. Tracer uptake in different organs including the liver in ALF and control mice in vivo was quantified using [¹⁸F]fluoro-proline microPET/CT.

The optimal dose and time of [³H]proline uptake by HSC was 19-37MBq/L and 30-90min after culture. Higher [³H]proline uptake and type 1 collagen production in HSC were found in ALF and control rats. There was a high correlation between [³H]proline uptake and type 1 collagen in ALF rats. To cut the costs of tracer usage and imaging in vivo, the mouse-to-rat model was compared. Type 1 collagen levels of ALF mice liver tissue in ex vivo were similar to ALF rats, as was proline transporter protein. Unlabeled proline of type 1 collagen and [³H]proline uptake of ALF mice was blocked by benztropine. in vivo [¹⁸F]fluoro-proline PET/CT imaging, SUVmax in the liver, normalized liver/brain and liver/thigh ratio were significantly different between ALF mice and controls and there was a strong positive correlation among these three indexes in ALF mice.

[¹⁸F]fluoro-proline microPET/CT is feasible to quantify collagenogenesis in HSC in early-stage ALF animal models, which may be used as a promising and reliable noninvasive diagnostic technique.

Breast cancer is one of the leading causes of mortality among women. In addition, 1 in 8 women and 1 in 833 men will be diagnosed with breast cancer in 2022. The detection of breast cancer can not only lower treatment costs but also increase survival rates. Due to increased cancer awareness, more women are undergoing breast cancer screening, leading to more cases being diagnosed worldwide, but doctors' ability to analyze these images is limited. As a result, they get overloaded leading to misinterpretations. The advent of computer-aided diagnosis (CAD) minimized man’s involvement and achieved good results. CAD helps medical doctors automatically detect and analyze abnormalities found in the breast. Such abnormalities may be benign or malignant tumors.

The goal of this study is to evaluate the effectiveness of using seven layers to classify breast cancer as either benign or malignant using mammograms.

The open-source MIAS dataset of 322 images was used for our study, of which 207 were normal images and 115 were abnormal images. The proposed CNN model convolves an image into seven layers that extract features from the input images, and these features are used to classify breast cancer as malignant or benign.

The proposed CNN used a limited data set and achieved the best result compared to previous work. The method achieved results with a 0.39% loss, 99.89% accuracy, 99.85% precision, 99.89% recall, 99.87% F1-score, and an area under the curve noted to be 100.0%.

CNN uses a small amount of data to determine abnormalities; the method will assist a medical doctor in determining whether or not a specific patient has cancer.

Ultrasound is extensively used for soft tissue pathology. Scanning bone superficial structures may reveal clear pathologic features to aid diagnosis.

We present the case of a stress fracture in the second metatarsal, with the clinical aspect of a gouty attack. Ultrasound examination showed cortical thickening and disruption, hypoechoic periosteal swelling, hyperemia, soft tissue edema, and displacement of the extensor tendon. The diagnosis was confirmed by X-ray and MRI. The value of different diagnostic tools is discussed, and the importance of gray-scale and color Doppler ultrasound as a first-hand modality is underlined.

Sonography clearly identifies cortical and periosteal abnormalities, differentiates surrounding soft tissue pathologies, and offers dynamic evaluation, and follow-up possibility with low cost, high accessibility, and no risks. Periosteal and cortical irregularities are important diagnostic issues when performing ultrasound examinations for soft tissue pathology.

Liposarcoma (LPS) is a malignant mesenchymal tumor that mostly occurs in the extremities and retroperitoneum and rarely in the scrotum.

In this case report, we introduced a patient who was diagnosed with LPS in the scrotum. In his right scrotum, we found a large soft tissue mass, including fat and calcification.

We reviewed the clinical, pathological and computed tomography (CT) features of patients diagnosed with LPS of the scrotum to help improve the understanding of the disease and the accuracy of diagnosis.

This work aimed to evaluate the level set segmentation algorithm on ocular surface thermograms. In addition, the vascularity functioning between the contralateral portions of two eyes (right and left) was identified using statistical analysis methods.

A total of 25 healthy participants with an average age of 35 years (20 men and 5 women) were selected in April 2022. Thermogram images were captured using a FLIR T series thermal camera. Conventional image processing techniques, such as filtering and edge detection, were used to preprocess thermograms. Next, the level set approach was used with the edge-detected pattern as an input to an automated segmented region of interest (ROI).

Five metrics, namely Dice Coefficient, Tanimoto Index, Jaccard Index, Volume Similarity, and Structural Similarity, were used to assess the performance of the segmentation technique compared to ground truth, which showed 97.5%, 92.5%, 94.5%, 96.5%, and 96.5% correlation, respectively, between the segmented and the ground truth images with average values for both the eyes. Statistical analysis demonstrated that the contralateral portions of the ocular thermograms were significantly different in terms of vascular distribution between the left and right eyes (p < 0.005).

The level set method efficiently segmented the ROI in ocular thermograms with maximum correlation. According to the segmentation’s results, the model showed the dissimilarity between the contralateral parts of the left and right eyes in healthy cases.

This study aims to investigate the efficiency of a radiomics model in identifying high-frequency microsatellite instability (MSI-H) and microsatellite stability (MSS) of colorectal liver metastasis (CRLM) according to machine learning radiomics features of enhanced CT liver images.

A total of 12 patients with MSI-H CRLM and 96 patients with MSS CRLM were randomly divided into the training group and internal validation group according to the ratio of 7: 3 (training: 75 cases, validation: 33 cases). From the enhanced CT (portal phase) image data of patients, 788 radiomics features were extracted, and a random forest model was established with the optimal features selected. The receiver operating characteristics (ROC) curve analysis was performed to assess the model’s diagnostic efficacy.

The training group comprised 8 patients with MSI-H CRLM and 67 patients with MSS CRLM, and the internal validation group included 4 patients with MSI-H CRLM and 29 patients with MSS CRLM. After feature selection, 7 radiomics features good for distinguishing MSI-H CRLM and MSS CRLM were screened out. The ROC curve analysis demonstrated that the random forest model had the AUC (area under the ROC curve) value 0.88, accuracy 0.85, sensitivity 0.85, specificity 0.92, and F1 score 0.88 in the training group. The model had an AUC value of 0.75, accuracy of 0.74, sensitivity of 0.81, specificity of 0.85, and F1_score of 0.78 in the internal validation group in identifying the MSI-H from the MSS CRLM. In order to evaluate the robustness of the overall model, the 788 features obtained were all applied to the 5-fold cross-validation, with the model being built on the random forest and analyzed with the ROC curve analysis. The AUC value of the model was 0.86 (P<0.05), accuracy value 0.91, sensitivity 0.60, and specificity 0.95.

The random forest prediction model built on the radiometric features extracted from enhanced CT images can be used to identify the MSI-H from the MSS CRLM and may provide effective guidance for clinical immunotherapy of CRLM patients with unknown MSI status.

Betel nut chewing is very common in Southeast Asia and other tropical countries. Much clinical evidence suggests that chewing betel nut has pro-inflammatory and carcinogenic effects, but there are few clinical reports of acute toxicity caused by it, especially involving esophageal damage.

We presented a case of a 72-year-old female who was admitted to our hospital for chest pain and hematemesis within several minutes after chewing betel nut. Gastroscopy showed two longitudinal ridge-like mucosal eminences in the esophagus located 20 cm from the incisors down to the gastric cardia, which was similar to varices. At last, a CT scan showed concentric-circle thickening of the esophagus wall, suggesting hematomas. Our treatment included fasting, inhibiting gastric acid and maintaining blood volume. After one week of medical treatment, rechecked gastroscopy showed that esophageal hematomas were gradually absorbed, with the formation of multiple shallow ulcers.

The acute toxicity of chewing betel nut can be easily overlooked. Patients who experience chest pain or hematemesis after chewing betel nut products,especially those who take aspirin at the same time, need to be alert to esophageal hematoma.

Primary anorectal malignant melanoma (ARMM) is a rare tumor. It is often misdiagnosed as hemorrhoids, polyps or colorectal cancer due to the lack of specificity of their clinical symptoms and imaging manifestations.

In this study, we reported an 83-year-old female patient with ARMM. Computed tomography (CT) and Magnetic Resonance Imaging (MRI) showed uneven thickening of the intestinal wall about 7.0 cm from the anal margin, and no typical T1 high signal was seen on MRI. Dual-energy spectral CT showed that the effective atomic number (Zeff) of the tumor and the iodine concentration in the arterial phase (AP) and venous phase (VP) were different from other rectal malignancies reported in the previous literature. Sigmoidoscopy showed a large polypoid mass approximately 7.0 cm from the anal verge. Immunohistochemical staining showed that about 60% of Melan A and HMB-45 were positive, S-100 protein and Ki-67 were positive, and the pathological diagnosis was ARMM.

This was the first dual-energy spectral CT imaging report of ARMM. The Zeff and iodine concentration in the arterial phase and venous phase could help distinguish between ARMM and other rectal malignancies.