Sketch-based semantic retrieval of medical images

The volume of medical images stored in hospitals is rapidly increasing; however, the utilization of these accumulated medical images remains limited. Existing content-based medical image retrieval (CBMIR) systems typically require example images, leading to practical limitations, such as the lack of customizable, fine-grained image retrieval, the inability to search without example images, and difficulty in retrieving rare cases. In this paper, we introduce a sketch-based medical image retrieval (SBMIR) system that enables users to find images of interest without the need for example images. The key concept is feature decomposition of medical images, which allows the entire feature of a medical image to be decomposed into and reconstructed from normal and abnormal features. Building on this concept, our SBMIR system provides an easy-to-use two-step graphical user interface: users first select a template image to specify a normal feature and then draw a semantic sketch of the disease on the template image to represent an abnormal feature. The system integrates both types of input to construct a query vector and retrieves reference images. For evaluation, ten healthcare professionals participated in a user test using two datasets. Consequently, our SBMIR system enabled users to overcome previous challenges, including image retrieval based on fine-grained image characteristics, image retrieval without example images, and image retrieval for rare cases. Our SBMIR system provides on-demand, customizable medical image retrieval, thereby expanding the utility of medical image databases.

Prognostic impact of extramural venous invasion detected by contrast-enhanced CT colonography in colon cancer

BACKGROUND

The impact of computed tomography (CT)-detected extramural venous invasion on the recurrence of colon cancer is not fully understood. The aim of this study was to investigate the clinical significance of extramural venous invasion diagnosed before surgery by contrast-enhanced CT colonography using three-dimensional multiplanar reconstruction images.

METHODS

Patients with colon cancer staged greater than or equal to T2 and/or stage I-III who underwent contrast-enhanced CT colonography between 2013 and 2018 at the National Cancer Center Hospital in Japan were retrospectively investigated for CT-detected extramural venous invasion. Inter-observer agreement for the detection of CT-detected extramural venous invasion was evaluated and Kaplan-Meier survival curves were plotted for recurrence-free survival using CT-TNM staging and CT-detected extramural venous invasion. Preoperative clinical variables were analysed using Cox regression for recurrence-free survival.

RESULTS

Out of 922 eligible patients, 544 cases were analysed (50 (9.2 per cent) were diagnosed as positive for CT-detected extramural venous invasion and 494 (90.8 per cent) were diagnosed as negative for CT-detected extramural venous invasion). The inter-observer agreement for CT-detected extramural venous invasion had a κ coefficient of 0.830. The group positive for CT-detected extramural venous invasion had a median follow-up of 62.1 months, whereas the group negative for CT-detected extramural venous invasion had a median follow-up of 60.7 months. When CT-TNM stage was stratified according to CT-detected extramural venous invasion status, CT-T3 N(-)extramural venous invasion(+) had a poor prognosis compared with CT-T3 N(-)extramural venous invasion(-) and CT-stage I (5-year recurrence-free survival of 50.6 versus 89.3 and 90.1 per cent respectively; P < 0.001). In CT-stage III, the group positive for CT-detected extramural venous invasion also had a poor prognosis compared with the group negative for CT-detected extramural venous invasion (5-year recurrence-free survival of 52.0 versus 78.5 per cent respectively; P = 0.003). Multivariable analysis revealed that recurrence was associated with CT-T4 (HR 3.10, 95 per cent c.i. 1.85 to 5.20; P < 0.001) and CT-detected extramural venous invasion (HR 3.08, 95 per cent c.i. 1.90 to 5.00; P < 0.001).

CONCLUSION

CT-detected extramural venous invasion was found to be an independent predictor of recurrence and could be used in combination with preoperative TNM staging to identify patients at high risk of recurrence.

Characteristics of false-positive lesions in evaluating colorectal liver metastases on gadoxetic acid-enhanced magnetic resonance imaging

PURPOSE

Gadoxetic acid-enhanced MRI (Gd-EOB-MRI) shows higher sensitivity for colorectal liver metastases (CRLM) than contrast-enhanced computed tomography (CECT). However, the details of false-positive lesions for each imaging modality are unknown.

METHODS

Cases undergoing hepatectomy for CRLM following a preoperative evaluation with both CECT and Gd-EOB-MRI between July 2008 and December 2016 were reviewed. The false-positive and false-negative rates were assessed for each modality, and the characteristics of false-positive lesions were evaluated.

RESULTS

We evaluated 275 partial hepatectomies in 242 patients without preoperative chemotherapy. Among the 275 hepatectomies, 546 lesions were recognized by CECT and/or Gd-EOB-MRI. The false-positive rates for CECT and Gd-EOB-MRI were 4% (18/422) and 7% (37/536), respectively. The size of false-positive lesions was significantly smaller than that of correctly diagnosed lesions (median: 28 mm [3-120 mm] vs 7.6 mm [320 mm], P  < 0.001). Compared with the 233 correctly diagnosed lesions ≤ 20 mm in diameter, false-positive lesions were more frequently located near the liver surface or vasculobiliary structures than true lesions (33/37 [89%] vs 149/233 [64%], respectively; P  = 0.0021).

CONCLUSION

Gd-EOB-MRI had a 7% false-positive rate. A small size and tumor location near the surface or near vasculobiliary structures were associated with false positivity.

RBIO-03. INITIAL RESULT OF DEVELOP ROBUST DEEP LEARNING MODEL FOR DETECTING GENOMIC STATUS IN GLIOMAS AGAINST IMAGE DIFFERENCES AMONG FACILITIES

BACKGROUND

The importance of detecting the genomic status of gliomas is increasingly recognized and IDH (isocitrate dehydrogenase) mutation and TERT (telomerase reverse transcriptase) promoter mutation have a significant impact on treatment decisions. Noninvasive prediction of these genomic statuses in gliomas is a challenging problem; however, a deep learning model using magnetic resonance imaging (MRI) can be a solution. The image differences among facilities causing performance degradation, called domain shift, have also been reported in other tasks such as brain tumor segmentation. We investigated whether a deep learning model could predict the gene status, and if so, to what extent it would be affected by domain shift.

METHOD

We used the Multimodal Brain Tumor Segmentation Challenge (BraTS) data and the Japanese cohort (JC) dataset consisted of brain tumor images collected from 544 patients in 10 facilities in Japan. We focused on IDH mutation and TERT promoter mutation. The deep learning models to predict the statuses of these genes were trained by the BraTS dataset or the training portion of the JC dataset, and the test portion of the JC dataset evaluated the accuracy of the models.

RESULTS

The IDH mutation predicting model trained by the BraTS dataset showed 80.0% accuracy for the validation portion of the BraTS dataset; however, only 67.3% for the test portion of the JC dataset. The TERT promoter mutation predicting model trained by the training portion of the JC dataset showed only 49% accuracy for the test portion of the JC dataset.

CONCLUSION

IDH mutation can be predicted by deep learning models using MRI, but the performance degeneration by domain shift was significant. On the other hand, TERT promoter mutation could not be predicted accurately enough by current deep learning techniques. In both mutations, further studies are needed.

Observing deep radiomics for the classification of glioma grades

Deep learning is a promising method for medical image analysis because it can automatically acquire meaningful representations from raw data. However, a technical challenge lies in the difficulty of determining which types of internal representation are associated with a specific task, because feature vectors can vary dynamically according to individual inputs. Here, based on the magnetic resonance imaging (MRI) of gliomas, we propose a novel method to extract a shareable set of feature vectors that encode various parts in tumor imaging phenotypes. By applying vector quantization to latent representations, features extracted by an encoder are replaced with a fixed set of feature vectors. Hence, the set of feature vectors can be used in downstream tasks as imaging markers, which we call deep radiomics. Using deep radiomics, a classifier is established using logistic regression to predict the glioma grade with 90% accuracy. We also devise an algorithm to visualize the image region encoded by each feature vector, and demonstrate that the classification model preferentially relies on feature vectors associated with the presence or absence of contrast enhancement in tumor regions. Our proposal provides a data-driven approach to enhance the understanding of the imaging appearance of gliomas.

Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine

In recent years, advances in artificial intelligence (AI) technology have led to the rapid clinical implementation of devices with AI technology in the medical field. More than 60 AI-equipped medical devices have already been approved by the Food and Drug Administration (FDA) in the United States, and the active introduction of AI technology is considered to be an inevitable trend in the future of medicine. In the field of oncology, clinical applications of medical devices using AI technology are already underway, mainly in radiology, and AI technology is expected to be positioned as an important core technology. In particular, "precision medicine," a medical treatment that selects the most appropriate treatment for each patient based on a vast amount of medical data such as genome information, has become a worldwide trend; AI technology is expected to be utilized in the process of extracting truly useful information from a large amount of medical data and applying it to diagnosis and treatment. In this review, we would like to introduce the history of AI technology and the current state of medical AI, especially in the oncology field, as well as discuss the possibilities and challenges of AI technology in the medical field.

NIMG-29. DEVELOPING AUTOMATIC SEGMENTATION METHOD FOR BRAIN TUMOR MR IMAGES THAT CAN BE USED AT MULTIPLE FACILITIES

BACKGROUND

Manual segmentation of brain tumor images from a large volume of MR images generated in clinical routines is difficult and time-consuming. Hence, it is imperative to develop a machine learning model for automated segmentation of brain tumor images.

PURPOSE

Machine learning models for automated MR image segmentation of gliomas may be useful. However, the image differences among facilities cause performance degradation and impede successful automatic segmentation. In this study, we proposed a method to solve this issue.

METHODS

We used the data from the Multimodal Brain Tumor Image Segmentation Benchmark (BraTS) and the Japanese cohort (JC) datasets collected from 10 facilities. Three models for tumor segmentation were developed. The BraTS model was trained on the BraTS dataset, and the JC model was trained on the JC dataset; whereas, the Fine-tuning model was a fine-tuned BraTS model using the JC dataset.

RESULTS

MR images of 544 patients were obtained for the JC dataset. Half of the JC dataset was used for independent testing. The Dice coefficient score of the JC model for the JC dataset was 0.779± 0.137, whereas that of the BraTS model was remarkably lower (0.717 ± 0.207). The mean of the Fine-tuning models for the JC dataset was 0.769 ± 0.138. There was a significant difference between the BraTS and JC models (P &lt; 0.0001) and the BraTS and Fine-tuning models (P = 0.002); however, no significant difference was observed between the JC and Fine-tuning models (P = 0.673).

CONCLUSIONS

Application of the BraTS model to heterogeneous datasets can significantly reduce its performance; however, fine-tuning can solve this issue. Since our fine-tuning method only requires less than 20 cases, this methodology is particularly useful for a facility where there are a few glioma cases.

A comparative effectiveness pilot study of teriparatide for medication-related osteonecrosis of the jaw: daily versus weekly administration

We studied the effectiveness of teriparatide (TPTD) for treating medication-related osteonecrosis of the jaw (MRONJ) in patients with osteoporosis and examined differences in the clinical outcomes following daily versus weekly TPTD. The outcomes were significantly improved in the entire patient series and the daily group.

PURPOSE

Teriparatide (TPTD) treatment for Stage II-III medication-related osteonecrosis of the jaw (MRONJ) in osteoporotic patients has yielded promising results in uncontrolled studies. The daily administration and the weekly administration of TPTD have been reported to improve outcomes in MRONJ. Herein, we sought to identify differences in the clinical outcomes of MRONJ patients treated with daily TPTD versus weekly TPTD.

METHODS

We enrolled 13 patients and randomly assigned them to receive either of two treatments: 1×/week 56.5-μg TPTD injection for 6 months (weekly group; n = 6 patients after 1 dropout), or 20-μg TPTD injection daily for 6 months (daily group; n = 6 patients). Patients in both groups received conventional therapy plus intensive antibiotic therapy as necessary. We compared the changes in the patients' clinical stage of MRONJ, bone metabolism, percentage of bone formation, and bone turnover markers between the weekly and daily groups.

RESULTS

TPTD treatment with MRONJ led to partial remission or complete remission in 5 daily-group patients and 3 weekly-group patients. The MRONJ stage was significantly improved from baseline to 6 months of treatment in the entire series of 12 patients (p = 0.008); the weekly group did not show significant improvement, but the daily group did (p = 0.01).

CONCLUSIONS

This study provides the first comparison of clinical outcomes between MRONJ patients who received daily or weekly TPTD injections. Six months of treatment with TPTD realized a significant improvement of MRONJ stage in both the entire patient series and the daily group.

P1444 Occurrence and predictors of right ventricular dysfunction after pericardiocentesis

Background—The changes in cardiac function that occur after pericardiocentesis are unclear.Purpose—This study was performed to assess right ventricular (RV) and left ventricular (LV) function with echocardiography before and after pericardiocentesis.

Method and Results—In total, 19 consecutive patients who underwent pericardiocentesis for more than moderate pericardial effusion were prospectively enrolled from August 2015 to October 2017. Comprehensive transthoracic echocardiography was performed before, immediately after (within 3 hours), and 1 day after pericardiocentesis to investigate the changes in RV and LV function. RV dysfunction is defined as meeting three of the four criteria: a TAPSE of &lt;17 mm, an S’ of &lt;9.5 cm, an FAC of &lt;35%, and an RV free wall longitudinal strain &gt;−20%. The mean age of all patients was 72.6 ± 12.2 years. The changes of echocardiographic parameters related to RV function are shown in Table. After pericardiocentesis, RV inflow and outflow diameters increased and the parameters of RV function significantly decreased. These abnormal values or RV dysfunction remained at 1 day after pericardiocentesis. Conversely, no parameters of LV function parameters changed after pericardiocentesis. Of 19 patients, 13 patients showed RV dysfunction immediately after pericardiocentesis and 6 patients did not. RV free wall longitudinal strain before pericardiocentesis was higher in patients with post-procedural RV dysfunction (−18.9 ± 3.6%) than in those without (−28.4 ± 6.3%). ROC analysis revealed that a RV free wall longitudinal strain cut-off value of −23.0% had a sensitivity of 100% and a specificity of 83.3% for predicting the occurrence of RV dysfunction after pericardiocentesis (AUC = 0.910).

Conclusions—The occurrence of RV dysfunction after pericardiocentesis should be given more attention. Pre-existing RV dysfunction maybe related to the occurrence of RV dysfunction after pericardiocentesis.

Changes in RV function before and after Before Immediately after One day after P−value Basal right ventricular linear dimension (mm) 32.8 ± 5.0 37.1 ± 4.4† 33.6 ± 5.4 0.028 Mid-cavity right ventricular linear dimension (mm) 34.5 ± 4.6 38.8 ± 5.3† 37.0 ± 5.6 0.0504 Proximal right ventricular outflow diameter (mm) 30.2 ± 4.0 33.9 ± 3.5† 31.4 ± 3.9 0.014 TAPSE (mm) 20.0 ± 4.2 13.6 ± 4.3* 14.7 ± 3.9 &lt;0.001 S" (cm/s) 12.6 ± 3.3 8.7 ± 2.4* 9.1 ± 2.4 &lt;0.001 Fractional area change (%) 48.3 ± 5.9 37.8 ± 8.0* 40.0 ± 9.0 &lt;0.001 Right ventricular free wall strain (%) −21.3 ± 6.3 −15.8 ± 6.7* −16.9 ± 5.2 0.036 Tricuspid regurgitation velocity peak (m/s) 2.41 ± 0.29 2.43 ± 0.25 2.34 ± 0.32 0.37

NIMG-67. DEVELOPMENT OF VERSATILE MACHINE-LEARNING APPROACHES FOR RADIOGENOMICS OF GLIOMA IN DIFFERENT COHORTS

BACKGROUND

Radiogenomics aims to analyze clinical images and information, and to predict key molecular profiles of tumors. However, imaging protocol is usually different in facilities, and it has been rarely examined whether the performance of developed methods in a dataset is robustly sustained even in other independent datasets. We explored machine learning and matrix decomposition methods using preoperative magnetic resonance images (MRIs) of glioma patients to establish versatile platform regardless of the heterogeneity of the datasets.

METHODS

Preoperative glioma MRIs and clinical information were obtained from public dataset of The Cancer Imaging Archive (TCIA, N=159) and National Cancer Center Hospital (NCC, N=166). More than 16,000 radiomic features were applied for the prediction of tumor grading and IDH mutation status. Accuracy of prediction was evaluated by AUROC (area under the receiver operating characteristic curves).

RESULTS

The performances were comparable between the image features regardless of dimension reduction methods (the best accuracy for tumor grading and IDH status prediction was 0.91 and 0.88, respectively), but they were drastically decreased in the transfer learning (0.70 and 0.69). On the other hand, they were successfully improved by applying matrix decomposition and brain embedding (0.86 and 0.79).

CONCLUSION

Our result and pipeline can be a global benchmark for future studies in heterogeneous datasets. Further evaluation in larger cohorts are planned.

Preoperative T staging of colon cancer using CT colonography with multiplanar reconstruction: new diagnostic criteria based on "bordering vessels"

PURPOSE

Preoperative T staging of colon cancer, in particular, for distinguishing T3 from T2 and T4, has been a challenge. The aim of this study was to evaluate newly developed criteria for preoperative T staging of colorectal cancer using computed tomography colonography (CTC) with multiplanar reconstruction (MPR), based on the spatial relationship of tumors and "bordering vessels," that is, marginal vessels that are detectable by multi-detector row CT with MPR.

METHODS

A total of 172 patients with colon and upper rectal cancer who underwent preoperative CTC and surgery between August 2011 and September 2013 were included. Preoperative T staging using the new criteria was performed prospectively and compared with pathologic results.

RESULTS

Sensitivity, specificity, and accuracy of T staging by CTC using the new criteria were 63%, 80%, and 77% for T2 (n = 30); 72%, 94%, and 81% for T3 (n = 95); and 79%, 99%, and 97% for T4a (n = 14), respectively. Positive predictive value for T3 was 93%, indicating that a T3 diagnosis by CTC is precise. In addition, negative predictive value for pathological T4a was 98%, indicating that a "not T4a" diagnosis by CTC is also precise.

CONCLUSIONS

Our newly developed criteria are useful for preoperative T staging, particularly for distinguishing T3 from T2 and T4.

Computed tomographic colonography with a reduced dose of laxative using a novel barium sulfate contrast agent in Japan

PURPOSE

To test the tagging efficacy, patient acceptability, and accuracy of computed tomographic colonography (CTC) with a reduced dose of laxative using a novel barium sulfate (BaSO₄) contrast agent.

MATERIALS AND METHODS

CTC followed by optical colonoscopy (OC) was performed on 73 patients with positive results in fecal occult blood tests. They were administrated a BaSO₄ suspension and a magnesium citrate solution for bowel preparation. Patients completed a questionnaire about the acceptability of bowel preparation. Tagging efficacy was estimated using a novel categorization system, which classified all segments into 8 categories. The accuracy of detecting protruded lesions ≥ 6 mm was calculated from the comparison of CTC and OC results, using the latter as a reference standard.

RESULTS

Tagging efficacy was good in 77.3% of colonic segments where residue was observed. The acceptability of bowel preparation for CTC was significantly higher than that for OC. The sensitivity, specificity, and positive and negative predictive values were 0.778, 0.945, 0.824, and 0.929, respectively. All lesions ≥ 7 mm were successfully detected by CTC.

CONCLUSION

CTC with a reduced dose of laxative using a novel BaSO₄ contrast agent has a favorable tagging efficacy, patient acceptability, and accuracy.

Efficacy and Safety of Pazopanib for Recurrent or Metastatic Solitary Fibrous Tumor

OBJECTIVE

To investigate the efficacy and safety of pazopanib for recurrent or metastatic solitary fibrous tumor (SFT) in first- and second-line settings.

METHODS

Patients histologically diagnosed with SFT at our hospital who received pazopanib monotherapy for inoperable disease between January 2013 and November 2016 were eligible. We retrospectively investigated treatment outcomes according to the treatment lines and assessed adverse events.

RESULTS

Nine patients were eligible. The median age was 67 years (range 42-81), and 6 patients (66.7%) were male. Four patients (50%) received pazopanib as second-line treatment. According to the RECIST and Choi criteria, the respective response rates were 0 and 50%, while the respective disease control rates were 88.9 and 75%. The median progression-free survival (PFS) was 6.2 months (95% confidence interval 3.2-8.8). Treatment line and high frequency of mitosis were not predictive of PFS (p = 0.67, 0.92). Two patients (22.2%) experienced elevated liver enzymes of grade 3 or higher.

CONCLUSION

Pazopanib is an effective treatment option for recurrent or metastatic SFT in first- and second-line settings. Liver injury is a major adverse event and adequate treatment withdrawal and dose reduction should be considered when necessary.

Minute mesenchymal chondrosarcoma within osteochondroma: an unexpected diagnosis confirmed by HEY1-NCOA2 fusion

Mesenchymal chondrosarcoma is rare and can be challenging to diagnose. Herein, we report a minute mesenchymal chondrosarcoma within an osteochondroma. A 12-year-old girl presented with an asymptomatic exophytic lesion of the rib. The tumor was clinically diagnosed as osteochondroma and was excised after observation for 3 years. The resected specimen revealed an unexpected minute (0.9 cm) "monophasic" mesenchymal chondrosarcoma in the apex of the lesion. The sarcoma consisted of monomorphic spindle cells without hyaline cartilage. Fluorescence in situ hybridization detected NCOA2 rearrangement, and reverse-transcription polymerase chain reaction and sequencing detected a HEY1 (exon 4)-NCOA2 (exon 13) fusion transcript. The patient did not receive adjuvant therapy and is alive with no recurrence 6 years after surgery. The present case highlights the value of careful pathological examination of specimens submitted as osteochondroma and emphasizes the usefulness of molecular assays in the diagnosis of mesenchymal chondrosarcoma in an atypical setting.

Preoperative T staging using CT colonography with multiplanar reconstruction for very low rectal cancer

Background

Preoperative T staging of lower rectal cancer is an important criterion for selecting intersphincteric resection (ISR) or abdominoperineal resection (APR) as well as selecting neoadjuvant therapy. The aim of this study was to evaluate the accuracy of preoperative T staging using CT colonography (CTC) with multiplanar reconstruction (MPR), in which with the newest workstation the images can be analyzed with a slice thickness of 0.5 mm.

Methods

Between 2011 and 2013, 45 consecutive patients with very low rectal adenocarcinoma underwent CTC with MPR. The accuracy of preoperative T staging using CTC with MPR was evaluated. The accuracy of preoperative T staging using MRI in the same patient population (34 of 45 patients) was also examined.

Results

Overall accuracy of T staging was 89% (41/45) for CTC with MPR and 71% (24/34) for MRI. CTC with MPR was particularly sensitive for pT2 tumors (82%; 14/17), whereas MRI tended to overstage pT2 tumors and its sensitivity for pT2 was 53% (8/15).

Conclusions

CTC with MPR, with an arbitrary selection, could be aligned to the tumor axis and better demonstrated tumor margins consecutively including the deepest section of the tumor. The accuracy of T2 and T3 staging using CTC with MPR seemed to surpass that of MRI, suggesting a potential role of CTC with MPR in preoperative T staging for very low rectal cancer.

Feasibility of Routine Application of Gadoxetic Acid-Enhanced MRI in Combination with Diffusion-Weighted MRI for the Preoperative Evaluation of Colorectal Liver Metastases

BACKGROUND

Gadoxetic acid-enhanced magnetic resonance imaging (MRI) in combination with diffusion-weighted MRI (Gd-EOB-MRI/DWI) has become popular for evaluating colorectal liver metastases (CRLM). This retrospective observational study aimed to determine whether this procedure should be indicated prior to hepatectomy in all patients with CRLM.

METHODS

A retrospective survey of relevant data of patients who had undergone hepatectomy for CRLM from 2008 to 2014 was performed. The rates of detection by contrast-enhanced computed tomography (CE-CT) and Gd-EOB-MRI/DWI were evaluated. In addition, relapse-free and overall survivals after primary hepatectomy were compared between patients who had undergone only CE-CT versus those who had undergone both CE-CT and Gd-EOB-MRI/DWI.

RESULTS

In all, 419 pathologically confirmed CRLM were resected in 202 hepatectomies in 177 patients. The sensitivity of detection of CRLM was 77 % for CE-CT and 93 % for Gd-EOB-MRI/DWI (P < 0.01). The sensitivity of detection of 1-5, 6-10, and 11-15 mm CRLM by CE-CT was 9.6 % (5/52), 47 % (26/55), and 76 % (57/75), respectively, whereas that by Gd-EOB-MRI/DWI was 54 % (28/52), 91 % (50/55), and 99 % (74/75), respectively; these differences are significant (P < 0.01 for all three groups). Relapse-free (P = 0.99) and overall survival (P = 0.79) did not differ significantly between 37 patients evaluated preoperatively by only CE-CT and 168 patients evaluated by both CE-CT and Gd-EOB-MRI/DWI.

CONCLUSION

Gd-EOB-MRI/DWI detects small CRLM (≤15 mm) with higher sensitivity than CE-CT. However, whether Gd-EOB-MRI/DWI should be a routine component of preoperative evaluation remains unclear in terms of survival benefit.

Myostatin alters glucose transporter-4 (GLUT4) expression in bovine skeletal muscles and myoblasts isolated from double-muscled (DM) and normal-muscled (NM) Japanese shorthorn cattle

The purpose of this study was to determine whether myostatin alters glucose transporter-4 (GLUT4) expression in bovine skeletal muscles and myoblasts isolated from double-muscled (DM) and normal-muscled (NM) Japanese Shorthorn cattle. Plasma concentrations of glucose were lower in DM cattle than in NM cattle (P < 0.01). The expression of GLUT4 messenger RNA (mRNA) in the skeletal muscle ex vivo and in myoblasts at 72 h after differentiation in vitro was higher in DM cattle than in NM cattle (P < 0.01). In contrast, the NM and DM cattle did not differ with respect to skeletal muscle expression of GLUT1 and myocyte enhancer factor-2c (MEF2c), a transcription factor of GLUT4. In differentiated myoblasts, the expression of GLUT1, GLUT4, and MEF2c mRNAs was greater in DM cattle than in NM cattle (P < 0.01). In the presence and absence of insulin, glucose uptake in myoblasts was increased in DM cattle relative to that of NM cattle (P < 0.01). The addition of myostatin decreased the expression of GLUT4 and MEF2c mRNAs in DM myoblasts (P < 0.05). Results of the present study suggest that myostatin inhibits the expression of GLUT4 mRNA possibly via MEF2c and that the greater ability of the DM cattle to produce muscle relative to the NM cattle may be due to their greater sensitivity to insulin and greater use of glucose.

Ability of preoperative 3.0-Tesla magnetic resonance imaging to predict the absence of side-specific extracapsular extension of prostate cancer

OBJECTIVE

Recent studies have shown an improvement in prostate cancer diagnosis with the use of 3.0-Tesla magnetic resonance imaging. We retrospectively assessed the ability of this imaging technique to predict side-specific extracapsular extension of prostate cancer.

METHODS

From October 2007 to August 2011, prostatectomy was carried out in 396 patients after preoperative 3.0-Tesla magnetic resonance imaging. Among these, 132 (primary sample) and 134 patients (validation sample) underwent 12-core prostate biopsy at the National Cancer Center Hospital of Tokyo, Japan, and at other institutions, respectively. In the primary dataset, univariate and multivariate analyses were carried out to predict side-specific extracapsular extension using variables determined preoperatively, including 3.0-Tesla magnetic resonance imaging findings (T2-weighted and diffusion-weighted imaging). A prediction model was then constructed and applied to the validation study sample.

RESULTS

Multivariate analysis identified four significant independent predictors (P < 0.05), including a biopsy Gleason score of ≥8, positive 3.0-Tesla diffusion-weighted magnetic resonance imaging findings, ≥2 positive biopsy cores on each side and a maximum percentage of positive cores ≥31% on each side. The negative predictive value was 93.9% in the combination model with these four predictors, meanwhile the positive predictive value was 33.8%. Good reproducibility of these four significant predictors and the combination model was observed in the validation study sample.

CONCLUSIONS

The side-specific extracapsular extension prediction by the biopsy Gleason score and factors associated with tumor location, including a positive 3.0-Tesla diffusion-weighted magnetic resonance imaging finding, have a high negative predictive value, but a low positive predictive value.

An in vitro chemosensitivity test for solid human tumors using collagen gel droplet embedded cultures

In vitro chemosensitivity testing using a collagen gel droplet embedded culture drug sensitivity test (CD-DST), was conducted with several types of solid cancer. The overall evaluable rate was 80% (443/554), including 76% for lung (n=243), 78% for breast (n=110), 87% for gastric (n=62), 83% for colorectal (n=107) cancers and 88% for 32 metastatic brain tumors. The in vitro sensitivity of breast, gastric and colorectal cancers to mitomycin C (MMC), cisplatin (CDDP), 5-fluorouracil (5-FU) and doxorubicin (DXR) was similar to the efficacy rates reported for each drug. This was also observed with lung cancer, the sensitivity of which to MMC, CDDP, vindesine (VDS) and etoposide (VP-16) was similar to the clinical efficacy. The clinical response to chemotherapy was compared with the results of in vitro chemosensitivity testing in Il patients: the clinical correlation was 91%, with a 80% true positive and 100% true negative rate. These results suggest that the CD-DST may be clinically useful by allowing the prediction of clinical response in various solid cancers.

A circulating heat-resistant mucin-like antigen in patients with lung-cancer detected by a new murine monoclonal-antibody

We discovered a circulating mucin-like antigen designated as CAM-14 detected by a new murine monoclonal antibody KL-14 (IgM). We found different heat resistant properties between serum CAM- 14 from normal individuals and from lung cancer patients. Heat treatment had less effect on the levels of CAM-14 in sera from lung cancer patients, whereas CAM-14 levels in sera from normal individuals were markedly decreased after heat treatment at tempratures > 65-degrees-C. As a serum tumor marker, CAM- 14 had only very low levels of false-positive values with a high specificity and effectively increased the positive rate for lung cancer patients when used together with carcinoembryonic antigen.

MRP-1/CD9 and KAI1/CD82 expression in normal and various cancer tissues

As part of our evaluation of MRP-1/CD9 and KAI1/CD82 as prognostic predictors among patients with cancer, we have extended our studies to solid tumors of a variety of anatomical sites. Normal tissues were included for comparison. Immunohistochemical techniques were used throughout. Our results indicate that MRP-1/CD9 was strongly expressed by many normal tissues, including the epithelium of the gastrointestinal tract, alveolar epithelium of the lung, urothelium and smooth muscle. Expression was weak in the pituitary gland, spleen and hepatocytes, and absent in testes and spinal cord. KAI1/CD82 was also expressed by many normal tissues, but was absent in some MRP-1/CD9-positive tissues (e.g., smooth muscle, adrenal cortex, urothelium, myelin of peripheral nerves, epithelium of amnion). On the other hand, KAI1/CD82 was strongly expressed in spinal cord gray matter, which was MRP-1/CD9-negative. Expression of these glycoproteins was detected in almost all types of tumors examined. In certain cancers, MRP-1/CD9 and KAI1/CD82 positivity was inversely related to lymph node involvement. Whereas lymph node metastases were present in 22.2% of lung cancer patients whose tumors were MRP-1/CD9 and KAI1/CD82-positive, 65.5% of patients with MRP-1/CD9 and KAI1/CD82-reduced/negative tumors had lymph node metastases. A similar inverse relationship was seen in colon cancer and breast cancer patients with respect to MRP-1/CD9 expression. The present data, together with our previous results suggest that evaluating the MRP1/CD9 and KAI1/CD82 status of cancers of the lung, breast and colon may provide useful information on the metastatic potential of the tumors.

Prediction of treatment outcomes in patients with chest wall sarcoma: evaluation with PET/CT

OBJECTIVE

The aim of this study was to investigate the prognostic implications of (18)F-2-fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography in patients with chest wall sarcoma.

METHODS

Positron emission tomography/computed tomography scans of 42 patients (mean age: 46 years) with chest wall sarcomas were analyzed. Pathologic confirmation was obtained by surgical specimens in all patients. Tumor grade assessed by Ki-67 (MIB-1) immunohistochemical analysis and expression of glucose transporter protein 1 were compared with a maximum standardized uptake value. Univariate and multivariate analyses were conducted for estimates of overall and event-free survivals.

RESULTS

The median maximum standardized uptake value of the tumor was 10.2 and the median MIB-1 index of the tumor was 32.5%. Glucose transporter protein 1 expression was found in 29 patients (69%). Univariate analyses revealed that surgery, chemotherapy, MIB-1 labeling index (cut-off 32.5%), MIB-1 grade, glucose transporter protein 1 expression and maximum standardized uptake value were possible predictors for overall and event-free survival. Multivariate analysis revealed that surgery (hazard ratio, 4.852; P = 0.017), maximum standardized uptake value (hazard ratio, 3.077; P = 0.037) and MIB-1 labeling index (hazard ratio, 6.549; P = 0.003) were independent predictors of event-free survival. In addition, surgery (hazard ratio, 4.092; P = 0.021) and maximum standardized uptake value (hazard ratio, 2.968; P = 0.027) were independent predictors of overall survival.

CONCLUSIONS

(18)F-2-fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography allows the prediction of prognosis after treatment in patients with chest wall sarcoma and may be useful in selecting high-risk patients for more risk-adapted treatments.

Neoadjuvant chemotherapy in breast cancer: prediction of pathologic response with PET/CT and dynamic contrast-enhanced MR imaging--prospective assessment

PURPOSE

To clarify whether fluorine 18 ((18)F) fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) and dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging performed after two cycles of neoadjuvant chemotherapy (NAC) can be used to predict pathologic response in breast cancer.

MATERIALS AND METHODS

Institutional human research committee approval and written informed consent were obtained. Accuracy after two cycles of NAC for predicting pathologic complete response (pCR) was examined in 142 women (mean age, 57 years: range, 43-72 years) with histologically proved breast cancer between December 2005 and February 2009. Quantitative PET/CT and DCE MR imaging were performed at baseline and after two cycles of NAC. Parameters of PET/CT and of blood flow and microvascular permeability at DCE MR were compared with pathologic response. Patients were also evaluated after NAC by using Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 based on DCE MR measurements and European Organization for Research and Treatment of Cancer (EORTC) criteria and PET Response Criteria in Solid Tumors (PERCIST) 1.0 based on PET/CT measurements. Multiple logistic regression analyses were performed to examine continuous variables at PET/CT and DCE MR to predict pCR, and diagnostic accuracies were compared with the McNemar test.

RESULTS

Significant decrease from baseline of all parameters at PET/CT and DCE MR was observed after NAC. Therapeutic response was obtained in 24 patients (17%) with pCR and 118 (83%) without pCR. Sensitivity, specificity, and accuracy to predict pCR were 45.5%, 85.5%, and 82.4%, respectively, with RECIST and 70.4%, 95.7%, and 90.8%, respectively, with EORTC and PERCIST. Multiple logistic regression revealed three significant independent predictors of pCR: percentage maximum standardized uptake value (%SUV(max)) (odds ratio [OR], 1.22; 95% confidence interval [CI]: 1.11, 1.34; P < .0001), percentage rate constant (%k(ep)) (OR, 1.07; CI: 1.03, 1.12; P = .002), and percentage area under the time-intensity curve over 90 seconds (%AUC(90)) (OR, 1.04; CI: 1.01, 1.07; P = .048). When diagnostic accuracies are compared, PET/CT is superior to DCE MR for the prediction of pCR (%SUV(max) [90.1%] vs %κ(ep) [83.8%] or %AUC(90) [76.8%]; P < .05).

CONCLUSION

The sensitivities of %SUV(max) (66.7%), %k(ep) (51.7%), and %AUC(90) (50.0%) at (18)F-FDG PET/CT and DCE MR after two cycles of NAC are not acceptable, but the specificities (96.4%, 92.0%, and 95.2%, respectively) are high for stratification of pCR cases in breast cancer.

[Lung cancer accompanied by active pulmonary tuberculosis]

We report 2 patients with lung cancer accompanied by active pulmonary tuberculosis. Case1 was a 82-year-old woman with stage I A bronchioloalveolar carcinoma and tuberculosis in right upper lobe. Right upper lobectomy was performed after the histological diagnosis of lung cancer by intraoperative frozen section. Case2 was a 69-year-old man with papillary adenocarcinoma in right lower lobe and tuberculosis in bilateral upper lobe. Partial resection in right lower lobe was performed for diagnosis of lung cancer. Smear-positive tuberculosis was diagnosed by sputum examination after the operation. Post-operative anti-tuberculosis chemotherapy was added in both patients.

Pharmacokinetic parameters from 3-Tesla DCE-MRI as surrogate biomarkers of antitumor effects of bevacizumab plus FOLFIRI in colorectal cancer with liver metastasis

Bevacizumab (BV) is an antivascular endothelial growth factor antibody. When administered with other chemotherapeutic drugs, BV-combined regimens prolong survival of colorectal cancer patients. We conducted a phase II trial to confirm the pharmacokinetic parameters from 3-Tesla dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as surrogate biomarkers of BV + FOLFIRI regimen efficacy in colorectal cancer with liver metastases. DCE-MRI was performed before treatment, on the seventh day after first treatment and every 8 weeks thereafter using a 3-Tesla MRI system. DCE-MRI parameters-area under the contrast concentration versus time curve at 90 and 180 s (AUC90 and AUC180, respectively) after contrast injection, and volume transfer constant of contrast agents (K(trans) and K(ep) ) were calculated from liver metastases. Fifty-eight liver metastases were analyzed. Univariate analysis revealed that a decrease in K(trans) ratios (ΔK(trans) ), K(ep) ratios (ΔK(ep) ), AUC90 ratios (ΔAUC90) and AUC180 ratios (ΔAUC180) correlated with higher response (all p < 0.0001) and longer time to progression (TTP) (ΔK(trans) : p = 0.001; ΔK(ep) : p = 0.004; ΔAUC90: p = 0.006; ΔAUC180: p < 0.0001). Multivariate analysis showed that ΔAUC180 was correlated with higher response (p = 0.009), and ΔK(trans) and ΔAUC180 were correlated with longer TTP (ΔK(trans) : p = 0.001; ΔAUC180: p = 0.024). ΔK(trans) and ΔAUC180 are pharmacodynamic biomarkers of the blood perfusion of BV + FOLFIRI. Our data suggest that ΔK(trans) and ΔK(ep) can predict response to chemotherapy at 1 week. Changes in 3-Tesla DCE-MRI parameters confirmed the potential of these biomarkers of blood perfusion as surrogate predictors of response and TTP.

Heterogeneity of colorectal cancers and extraction of discriminator gene signatures for personalized prediction of prognosis

Dissected specimens of colorectal cancer (CRC) have been intensively studied using molecular sketches (gene signatures) to obtain a set of discriminator gene signatures for accurate prognosis prediction in individual patients. The discriminators obtained so far are not universally applicable, as the gene sets reflect the method and site of the study. In this study, we show that dissected stage II and III CRC samples are significantly heterogeneous in molecular sketches, and are not appropriate sources for discriminator extraction unless handled individually. To search for an accurate discriminator gene set for prediction of metastases, we need to start with less heterogeneous stage II CRC. We examined 198 (92 stage II and 106 stage III) CRC dissected samples for the predictability of discriminator gene signatures by analyzing stage II CRC alone, stage III alone, or in combination. The best predictive power of discriminator genes was obtained only when these genes were extracted and validated with stage II CRC samples. An accurate discriminator gene set for the prediction of CRC metastases can be obtained by focusing on stage II CRC samples.

New analysis of the hypertension mechanism in bevacizumab-treated patients using 3-tesla dynamic contrast-enhanced magnetic resonance imaging

450

Background: Vascular endothelial growth factor (VEGF) signaling inhibitors, such as bevacizumab (BV), leads to endothelial dysfunction and microvascular rarefaction in noncancer tissue. Angiotensin II has been reported to induce VEGF production by inhibiting VEGF, but the reasons for activation of angiotensin II are unclear. We conducted a study to examine the relationship between renin-angiotensin axis and renal blood perfusion using dynamic contrast magnetic resonance imaging (DCE-MRI) in colorectal cancer patients.

Methods: Sixteen patients with colorectal cancer were enrolled. They received BV+FOLFIRI regimen as second line. DCE-MRI was performed before the treatment and after 12th courses. Renin, angiotensin I, angiotensin II and aldosterone were examined before treatment and at 3, 5, 8, 12th courses. DCE-MRI parameters, Area under the time-intensity curve over the first 90 seconds after injection of contrast material (AUC90) and volume transfer constant of contrast material (Ktrans, Kep) were calculated in the normal kidney and examine the correlation with renin-angiotensin axis.

Results: All DCE-MRI parameters decreased significantly after 12th courses compared with before treatment (Variables median: Ktrans -1.51, Kep -2.30, AUC90 -26.0, P < 0.001, all). A decrease in Kep correlated with higher renin, angiotensin I and angiotensin II (renin: P =0.001, angiotensin I: P =0.003, angiotensin II: P =0.002, respectively). A decrease in AUC90 correlated with higher aldosterone (P =0.005). Blood pressure did not correlate with each DCE-MRI parameters.

Conclusions: VEGF inhibition decreases vessel permeability and raises interstitial pressure in normal kidney. Our data suggest that renin-angiotensin axis is also one mechanism of hypertension caused by BV.

No significant financial relationships to disclose.