Improving liver lesions classification on CT/MRI images based on Hounsfield Units attenuation and deep learning

The early sign detection of liver lesions plays an extremely important role in preventing, diagnosing, and treating liver diseases. In fact, radiologists mainly consider Hounsfield Units to locate liver lesions. However, most studies focus on the analysis of unenhanced computed tomography images without considering an attenuation difference between Hounsfield Units before and after contrast injection. Therefore, the purpose of this work is to develop an improved method for the automatic detection and classification of common liver lesions based on deep learning techniques and the variations of the Hounsfield Units density on computed tomography scans. We design and implement a multi-phase classification model developed on the Faster Region-based Convolutional Neural Networks (Faster R–CNN), Region-based Fully Convolutional Networks (R–FCN), and Single Shot Detector Networks (SSD) with the transfer learning approach. The model considers the variations of the Hounsfield Unit density on computed tomography scans in four phases before and after contrast injection (plain, arterial, venous, and delay). The experiments are conducted on three common types of liver lesions including liver cysts, hemangiomas, and hepatocellular carcinoma. Experimental results show that the proposed method accurately locates and classifies common liver lesions. The liver lesions detection with Hounsfield Units gives high accuracy of 100%. Meanwhile, the lesion classification achieves an accuracy of 95.1%. The promising results show the applicability of the proposed method for automatic liver lesions detection and classification. The proposed method improves the accuracy of liver lesions detection and classification compared with some preceding methods. It is useful for practical systems to assist doctors in the diagnosis of liver lesions. In our further research, an improvement can be made with big data analysis to build real-time processing systems and we expand this study to detect lesions from all parts of the human body, not just the liver.     

Uninterpretable Dynamic Susceptibility Contrast-Enhanced Perfusion MR Images in Patients with Post-Treatment Glioblastomas: Cross-Validation of Alternative Imaging Options

Purpose

The purpose of this study was to evaluate the accuracy of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) perfusion MR imaging for distinguishing tumor recurrence from post-treatment effect as alternatives to dynamic-susceptibility contrast-enhanced (DSC) perfusion MR imaging when the DSC image is uninterpretable.

Materials and Methods

This retrospective study was approved by our institutional review board. Seventy one post-treatment glioblastoma patients who showed enlarged contrast-enhancing lesions on follow-up MR images after concurrent chemoradiotherapy and uninterpretable DSC images for corresponding enhancing lesions, underwent additional DWI and DCE MR imaging. The primary outcome was the frequency of interpretable DWI and DCE MR cases in these 71 patients. The secondary outcome was the area under the receiver operating characteristic curve (AUC) of DWI and DCE imaging parameters for distinguishing tumor recurrence from post-treatment effect in selected patients with interpretable DWI and DCE images. The imaging parameters were quantified as 10% cumulative histogram cutoff of apparent diffusion coefficient (ADC10) and 90% cumulative histogram cutoff of initial area under the time signal intensity curve (IAUC90). The AUCs were cross-validated by using leave-one-out method.

Results

Of the 71 patients, the uninterpretable DSC images were associated with treatment-related hemorrhage within the corresponding enhancing lesions (n = 54, 76.1%) and a near skull base location (n = 17, 23.9%). The frequencies of interpretable DWI and DCE image were 51 (71.8%) and 59 (83.1%) of the 71 cases with uninterpretable DSC images, respectively. Of the 45 selected patients with interpretable DWI and DCE images, the combination of DWI with DCE imaging showed a superior diagnostic performance than DWI or DCE imaging alone for differentiating tumor recurrence from post-treatment effect (cross-validated AUC: 0.78 versus 0.55 and 0.73 for reader 1; cross-validated AUC: 0.78 versus 0.53 and 0.75 for reader 2, respectively). Cross-validated accuracy of the single and combined imaging parameters also showed the highest for the combination of DWI with DCE MR imaging (72.9% for reader 1; 72.5% for reader 2) and the lowest for DWI alone (54.0% for reader 1; 56.4% for reader 2). Inter-reader agreement for DCE imaging was higher than that for DWI (intraclass correlation coefficient: 0.95 versus 0.87).

Conclusion

DCE MR imaging could be a superior and more reproducible imaging biomarker than DWI for differentiating tumor recurrence from post-treatment effect in patients with post-treatment glioblastoma when DSC MR images are not interpretable.     

Characterizing Venous Vasculatures of Hepatocellular Carcinoma Using a Multi-Breath-Hold Two-Dimensional Susceptibility Weighted Imaging

The aim of our study is to characterize the venous vasculatures of hepatocellular carcinoma (HCC) using a multi-breath-hold two-dimensional (2D) susceptibility weighted imaging (SWI) in comparison with conventional Magnetic Resonance Imaging (MRI) sequences. Twenty-nine patients with pathologically confirmed HCC underwent MR examination at a 3.0 T scanner. The number of venous vascularity in or around the lesion was counted and the image quality was subjectively evaluated by two experienced radiologists independently based on four image sets: 1) SWI, 2) T1-weighted sequence, 3) T2-weighted sequence, and 4) T1-weighted dynamic contrast-enhanced (DCE) sequence. Of the 29 patients, a total of 33 liver lesions were detected by both SWI and conventional MR sequences. In the evaluation of the conspicuity of venous vascularity, a mean of 10.7 tumor venous vessels per mass was detected by the SWI and 3.9 tumor vasculatures were detected by T1-weighted DCE (P<0.0001), while none was detected by T1-, T2-weighted sequences. The Pearson correlation coefficients between the lesion sizes and the number of tumor vasculatures detected by T1-weighted DCE was 0.708 (P<0.001), and 0.883 by SWI (P<0.001). Our data suggest that SWI appears to be a more sensitive tool compared to T1-weighted DCE sequence to characterize venous vasculature in liver lesions.     

Differentiation of Breast Cancer from Fibroadenoma with Dual-Echo Dynamic Contrast-Enhanced MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) of the breast is a routinely used imaging method which is highly sensitive for detecting breast malignancy. Specificity, though, remains suboptimal. Dynamic susceptibility contrast magnetic resonance imaging (DSC MRI), an alternative dynamic contrast imaging technique, evaluates perfusion-related parameters unique from DCE MRI. Previous work has shown that the combination of DSC MRI with DCE MRI can improve diagnostic specificity, though an additional administration of intravenous contrast is required. Dual-echo MRI can measure both T₁W DCE MRI and T₂*W DSC MRI parameters with a single contrast bolus, but has not been previously implemented in breast imaging. We have developed a dual-echo gradient-echo sequence to perform such simultaneous measurements in the breast, and use it to calculate the semi-quantitative T₁W and T₂*W related parameters such as peak enhancement ratio, time of maximal enhancement, regional blood flow, and regional blood volume in 20 malignant lesions and 10 benign fibroadenomas in 38 patients. Imaging parameters were compared to surgical or biopsy obtained tissue samples. Receiver operating characteristic (ROC) curves and area under the ROC curves were calculated for each parameter and combination of parameters. The time of maximal enhancement derived from DCE MRI had a 90% sensitivity and 69% specificity for predicting malignancy. When combined with DSC MRI derived regional blood flow and volume parameters, sensitivity remained unchanged at 90% but specificity increased to 80%. In conclusion, we show that dual-echo MRI with a single administration of contrast agent can simultaneously measure both T₁W and T₂*W related perfusion and kinetic parameters in the breast and the combination of DCE MRI and DSC MRI parameters improves the diagnostic performance of breast MRI to differentiate breast cancer from benign fibroadenomas.     

Automated analysis of low-field brain MRI in cerebral malaria

A central challenge of medical imaging studies is to extract biomarkers that characterize disease pathology or outcomes. Modern automated approaches have found tremendous success in high-resolution, high-quality magnetic resonance images. These methods, however, may not translate to low-resolution images acquired on magnetic resonance imaging (MRI) scanners with lower magnetic field strength. In low-resource settings where low-field scanners are more common and there is a shortage of radiologists to manually interpret MRI scans, it is critical to develop automated methods that can augment or replace manual interpretation, while accommodating reduced image quality. We present a fully automated framework for translating radiological diagnostic criteria into image-based biomarkers, inspired by a project in which children with cerebral malaria (CM) were imaged using low-field 0.35 Tesla MRI. We integrate multiatlas label fusion, which leverages high-resolution images from another sample as prior spatial information, with parametric Gaussian hidden Markov models based on image intensities, to create a robust method for determining ventricular cerebrospinal fluid volume. We also propose normalized image intensity and texture measurements to determine the loss of gray-to-white matter tissue differentiation and sulcal effacement. These integrated biomarkers have excellent classification performance for determining severe brain swelling due to CM.     

Analysis of fluorescent MRI contrast agent behavior in the liver and thoracic aorta of mice

OBJECTIVE: To characterize the behavior of magnetofluorescent products injected in mice intravenously. STUDY DESIGN: The magnetic resonance imaging (MRI) products were labelled with fluorescent molecules to examine the biodistribution process in vivo and observe them at the cellular level by means of confocal microscopy. Three-dimensional (3D) sequences of images were obtained by spectral analysis of sample preparations in a multiphoton confocal microscope and analyzed by the factor analysis of medical image sequence algorithm, which provides factor curves. Factor images are the result of image-processing methods that utilize information from emission spectra. Preparations are also screened in the counting mode to provide fluorescent lifetime imaging microscopy (FLIM) characterizations. RESULTS: Factor images and FLIM images can help to analyze MRI targeting inside the liver and thoracic aorta of mice. They show positive detection of Fe-Texas red and BOPTA-Eu in the liver and positive detection of Fe-Texas red and negative detection of BOPTA-Eu inside the thoracic aorta. CONCLUSION: This investigation established the utility of fluorescent MRI contrast agents as in vivo staining tools for cellular sites.     

Magnetic resonance imaging in the diagnosis of nonorganic hydatid disease

This article evaluates MRI diagnostic value in discovering of the non-organic hydatid disease. MRI data of 21 patients, suffering from parasite pathology of liver (n = 12), liver and peritoneum cavity (n = 2), liver and retroperitoneal space (n = 2), liver and thigh's muscles (n = 1), peritoneum cavity (n = 2), retroperitoneal space (n = 1), spine and paravertebral area (n = 1) were analyzed. Based on histopathological results, features of unusually localized hydatid cysts (HC) MRI- semiotics are described in detail and compared with liver echinococcosis. MRI technique for identification of some hydatid cyst's structures is shown. The authors discuss the MRI reliability in differential diagnosis of non-organic HC and several disorders (non-parasite congenital and acquired cysts, hematoma, abscess, metastasis) of the same anatomical region. They underline some MRI advantages in GD disclosing comparing with ultrasonography and computed tomography. However, serological tests are needed for diagnosis verification. The authors also postulate the importance of clinical data being taken into account for radiological conclusion.     

Comparison of the diagnostic capacities of imaging methods for childhood hemangiomas

The diagnostic capacities of three imaging methods: B-mode ultrasonography, computed tomography (CT), and magnetic resonance imaging (MRI) in orbital hemangiomas in babies were compared. Orbital ultrasound, computed tomography, and MRI scans were examined in 358, 384, and 48 babies, respectively. Their mean age was 6.7 months. Out of three techniques, ultrasound scanning proved to be of less informative value. MRI and CT were much more informative although each of them had advantages and limitations. The authors give some preference to CT despite its ionization.     

Comparison of Two Mathematical Models of Cellularity Calculation

OBJECT: Nowadays, there is increasing evidence that functional magnetic resonance imaging (MRI) modalities, namely, diffusion-weighted imaging (DWI) and dynamic-contrast enhanced MRI (DCE MRI), can characterize tumor architecture like cellularity and vascularity. Previously, two formulas based on a logistic tumor growth model were proposed to predict tumor cellularity with DWI and DCE. The purpose of this study was to proof these formulas. METHODS: 16 patients with head and neck squamous cell carcinomas were included into the study. There were 2 women and 14 men with a mean age of 57.0 ± 7.5 years. In every case, tumor cellularity was calculated using the proposed formulas by Atuegwu et al. In every case, also tumor cell count was estimated on histopathological specimens as an average cell count per 2 to 5 high-power fields. RESULTS: There was no significant correlation between the calculated cellularity and histopathologically estimated cell count by using the formula based on apparent diffusion coefficient (ADC) values. A moderate positive correlation (r=0.515, P=.041) could be identified by using the formula including ADC and V_e values. CONCLUSIONS: The formula including ADC and V_e values is more sensitive to predict tumor cellularity than the formula including ADC values only.     

Efficiency of Non-Contrast-Enhanced Liver Imaging Sequences Added to Initial Rectal MRI in Rectal Cancer Patients

Purpose

The purpose of this study was to estimate the value of addition of liver imaging to initial rectal magnetic resonance imaging (MRI) for detection of liver metastasis and evaluate imaging predictors of a high risk of liver metastasis on rectal MRI.

Methods

We enrolled 144 patients who from October 2010 to May 2013 underwent rectal MRI with T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) (b values = 50, 500, and 900 s/mm²) of the liver and abdominopelvic computed tomography (APCT) for the initial staging of rectal cancer. Two reviewers scored the possibility of liver metastasis on different sets of liver images (T2WI, DWI, and combined T2WI and DWI) and APCT and reached a conclusion by consensus for different analytic results. Imaging features from rectal MRI were also analyzed. The diagnostic performances of CT and an additional liver scan to detect liver metastasis were compared. Multivariate logistic regression to determine independent predictors of liver metastasis among rectal MRI features and tumor markers was performed. This retrospective study was approved by the Institutional Review Board, and the requirement for informed consent was waived.

Results

All sets of liver images were more effective than APCT for detecting liver metastasis, and DWI was the most effective. Perivascular stranding and anal sphincter invasion were statistically significant for liver metastasis (p = 0.0077 and p = 0.0471), while extramural vascular invasion based on MRI (mrEMVI) was marginally significant (p = 0.0534).

Conclusion

The addition of non-contrast-enhanced liver imaging, particularly DWI, to initial rectal MRI in rectal cancer patients could facilitate detection of liver metastasis without APCT. Perivascular stranding, anal sphincter invasion, and mrEMVI detected on rectal MRI were important imaging predictors of liver metastasis.     

Multi-Task Linear Programming Discriminant Analysis for the Identification of Progressive MCI Individuals

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer''s disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer''s Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images). Experimental results show very promising performance of our proposed MLPD method.     

Magnetic resonance tomography in the diagnosis of nonorganic bulky masses of the retroperitoneal space. Part 1. Cysts,abscesses and flegmons

The paper considers the diagnostic capacities of magnetic resonance imaging (MRI) in detecting non-organic bulky masses of the retroperitoneal space. Based on the analysis of tomographic findings in 23 patients with non-organic cysts of the retroperitoneal space and 27 patients with its abscesses and phlegmons, the first part of the paper describes the MRI semiotics of these diseases in detail and proposes methodic approaches to their identification. Comparison of the data of MRI and pathomorphological analysis of operation materials has yielded the rates of sensitivity, specificity, and accuracy of the method, which are equal to 100, 88.5, and 94.2% for non-organic cysts and 100, 87.1, and 93.5%, respectively. The authors note the lower efficiency of MRI in recognizing hydatid cysts and foreign bodies than ultrasound study and X-ray computed tomography and show it necessary to take into account clinical information in making a radiological conclusion.     

Predicting Therapeutic Efficacy of Vascular Disrupting Agent CA4P in Rats with Liver Tumors by Hepatobiliary Contrast Agent Mn-DPDP-Enhanced MRI

To evaluate hepatobiliary-specific contrast agent (CA) mangafodipir trisodium (Mn-DPDP)–enhanced magnetic resonance imaging (MRI) for predicting the therapeutic efficacy of the vascular disrupting agent combretastatin A4 phosphate (CA4P) in rats with primary and secondary liver tumors, 36 primary hepatocellular carcinomas (HCCs) were raised by diethylnitrosamine gavage in 16 male rats, in 6 of which one rhabdomyosarcomas (R1) was intrahepatically implanted as secondary liver tumors. On a 3.0T MR scanner with a wrist coil, tumors were monitored weekly by T2-/T1-weighted images (T2WI/T1WI) and characterized by Mn-DPDP-enhanced MRI. CA4P-induced intratumoral necrosis was depicted by nonspecific gadoterate meglumine (Gd-DOTA)–enhanced MRI before and 12 h after therapy. Changes of tumor-to-liver contrast (ΔT/L) on Mn-DPDP-enhanced images were analyzed. In vivo MRI findings were verified by postmortem microangiography and histopathology. Rat models of primary HCCs in a full spectrum of differentiation and secondary R1 liver tumors were successfully generated. Mn-DPDP-enhanced ΔT/L was negatively correlated with HCC differentiation grade (P < 0.01). After treatment with CA4P, more extensive tumoral necrosis was found in highly differentiated HCCs than that in moderately and poorly differentiated ones (P < 0.01); nearly complete necrosis was induced in secondary liver tumors. Mn-DPDP-enhanced MRI may help in imaging diagnosis of primary and secondary liver malignancies of different cellular differentiations and further in predicting CA4P therapeutic efficacy in primary HCCs and intrahepatic metastases.     

Magnetic resonance tomography, computed tomography and ultrasonic diagnosis of hemangiomas of the liver

The paper is concerned with the potentialities of modern radiation methods in the diagnosis of liver hemangiomas. USI, CT, angiography and MR-tomography (MRT) were used for investigation of 64 patients with liver hemangiomas. The diagnostic potentialities and the role of each of the above methods in the diagnostic algorithm in liver hemangiomas were studied. The results of the investigation have shown that MRT possesses a higher informative value than USI and CT in the diagnosis of liver hemangiomas and can even replace angiography in the verification of diagnosis.     

Integrin αvβ3-Targeted Dynamic Contrast-Enhanced Magnetic Resonance Imaging Using a Gadolinium-Loaded Polyethylene Gycol-Dendrimer-Cyclic RGD Conjugate to Evaluate Tumor Angiogenesis and to Assess Early Antiangiogenic Treatment Response in a Mouse Xenograft Tumor Model

AbstractThe purpose of this study was to validate an integrin αvβ3-targeted magnetic resonance contrast agent, PEG-G3-(Gd-DTPA)6-(cRGD-DTPA)2, for its ability to detect tumor angiogenesis and assess early response to antiangiogenic therapy using dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI). Integrin αvβ3-positive U87 cells and control groups were incubated with fluorescein-labeled cRGD-conjugated dendrimer, and the cellular attachment of the dendrimer was observed. DCE MRI was performed on mice bearing KB xenograft tumors using either PEG-G3-(Gd-DTPA)6-(cRGD-DTPA)2 or PEG-G3-(Gd-DTPA)6-(cRAD-DTPA)2. DCE MRI was also performed 2 hours after anti-integrin αvβ3 monoclonal antibody treatment and after bevacizumab treatment on days 3 and 6t. Using DCE MRI, the 30-minute contrast washout percentage was significantly lower in the cRGD-conjugate injection groups. The enhancement patterns were different between the two contrast injection groups. In the antiangiogenic therapy groups, a rapid increase in 30-minute contrast washout percentage was observed in both the LM609 and bevacizumab treatment groups, and this occurred before there was an observable decrease in tumor size. The integrin αvβ3 targeting ability of PEG-G3-(Gd-DTPA)6-(cRGD-DTPA)2 in vitro and in vivo was demonstrated. The 30-minute contrast washout percentage is a useful parameter for examining tumor angiogenesis and for the early assessment of antiangiogenic treatment response.     

Application of tomographic methods in the diagnosis of pathological changes of the jaw

The aim of this study was to evaluate the frequency of specific diagnostic methods used for diagnosis of oral pathologies. The sample consisted of 198 patients (98 man and 100 women) with formulated diagnosis, confirmed postoperatively by histopathological verification. In 74.7% of subjects only X-ray diagnostic examination was used. Both X-ray and computed tomography (CT) examinations were used in 18.7% of subjects. Magnetic resonance imaging (MRI) wasn't performed in any subject. In 6.6% of subjects neither X-ray nor CT was performed. The study reported on statistically significant differences in the distribution of specific diagnostic methods according to age groups (p = 0.026). Also, there was statistically significant differences in the distribution of diagnostic methods according to diagnostic groups (p = 0.053). In the group of 37 subjects, in whom both X-ray and computed tomography were used, the majority had carcinomas, followed by fractures and inflammatory cysts.     

In vivo detection of c-MET expression in a rat hepatocarcinogenesis model using molecularly targeted magnetic resonance imaging

The multifunctional growth factor scatter factor/hepatocyte growth factor and its tyrosine kinase receptor, c-MET, have been implicated in the genesis and malignant progression of numerous human malignancies, including hepatocellular carcinomas. The incidence of hepatocellular carcinomas in the United States has increased noticeably over the past two decades and is listed as the fifth major cancer in men worldwide. In this study, we used a choline-deficient l-amino acid (CDAA)-defined rat hepatocarcinogenesis model to visualize increased in vivo expression of the c-MET antigen in neoplastic lesion formation with the use of a super paramagnetic iron oxide (SPIO)-anti-c-MET molecularly targeted magnetic resonance imaging (MRI) contrast agent. SPIO-anti-c-MET was used for the first time to detect overexpression of c-MET in neoplastic nodules and tumors within the livers of CDAA-treated rats, as determined by a decrease in MRI signal intensity and a decrease in regional T(2) values. Specificity for the binding of the molecularly targeted anti-c-MET contrast agent was determined using rat hepatoma (H4-II-E-C3) cell cultures and immunofluorescence microscopic imaging of the targeting agents within neoplastic liver tissue 1 to 2 hours following intravenous administration of SPIO-anti-c-MET and MRI investigation. This method has the ability to visualize in vivo the overexpression of c-MET at early developmental stages of tumor formation.     

Radiodiagnosis of liver hemangiomas

A combined use of radiation methods in the diagnosis of liver hemangiomas is considered. Twenty-two hemangiomas were detected in 18 patients using ultrasound investigation (USI), computerized tomography (CT) and angiography. The most characteristic signs of hemangiomas were identified. USI and CT were shown quite reliable in the detection of hemangiomas. They can be used for solving diagnostic problems depending on a situation. A diagnostic algorithm envisaging the most optimum use of USI, CT and angiography in liver hemangiomas, was developed.     

Development of a dynamic imaging method for gravitropism in pea sprouts using clinical magnetic resonance imaging system

Although magnetic resonance imaging (MRI) is a useful technique, only a few studies have investigated the dynamic behavior of small subjects using MRI owing to constraints such as experimental space and signal amount. In this study, to acquire high-resolution continuous three-dimensional gravitropism data of pea (Pisum sativum) sprouts, we developed a small-bore MRI signal receiver coil that can be used in a clinical MRI and adjusted the imaging sequence. It was expected that such an arrangement would improve signal sensitivity and improve the signal-to-noise ratio (SNR) of the acquired image. All MRI experiments were performed using a 3.0-T clinical MRI scanner. An SNR comparison using an agarose gel phantom to confirm the improved performance of the small-bore receiver coil and an imaging experiment of pea sprouts exhibiting gravitropism were performed. The SNRs of the images acquired with a standard 32-channel head coil and the new small-bore receiver coil were 5.23±0.90 and 57.75±12.53, respectively. The SNR of the images recorded using the new coil was approximately 11-fold higher than that of the standard coil. In addition, when the accuracy of MR imaging that captures the movement of pea sprout was verified, the difference in position information from the optical image was found to be small and could be used for measurements. These results of this study enable the application of a clinical MRI system for dynamic plant MRI. We believe that this study is a significant first step in the development of plant MRI technique.