Advances in oncologic imaging: update on 5 common cancers

Machine learning and new insights for breast cancer diagnosis

Breast cancer (BC) is the most prominent form of cancer among females all over the world. The current methods of BC detection include X-ray mammography, ultrasound, computed tomography, magnetic resonance imaging, positron emission tomography and breast thermographic techniques. More recently, machine learning (ML) tools have been increasingly employed in diagnostic medicine for its high efficiency in detection and intervention. The subsequent imaging features and mathematical analyses can then be used to generate ML models, which stratify, differentiate and detect benign and malignant breast lesions. Given its marked advantages, radiomics is a frequently used tool in recent research and clinics. Artificial neural networks and deep learning (DL) are novel forms of ML that evaluate data using computer simulation of the human brain. DL directly processes unstructured information, such as images, sounds and language, and performs precise clinical image stratification, medical record analyses and tumour diagnosis. Herein, this review thoroughly summarizes prior investigations on the application of medical images for the detection and intervention of BC using radiomics, namely DL and ML. The aim was to provide guidance to scientists regarding the use of artificial intelligence and ML in research and the clinic.

Artificial Intelligence (AI) in Breast Imaging: A Scientometric Umbrella Review

Artificial intelligence (AI), a rousing advancement disrupting a wide spectrum of applications with remarkable betterment, has continued to gain momentum over the past decades. Within breast imaging, AI, especially machine learning and deep learning, honed with unlimited cross-data/case referencing, has found great utility encompassing four facets: screening and detection, diagnosis, disease monitoring, and data management as a whole. Over the years, breast cancer has been the apex of the cancer cumulative risk ranking for women across the six continents, existing in variegated forms and offering a complicated context in medical decisions. Realizing the ever-increasing demand for quality healthcare, contemporary AI has been envisioned to make great strides in clinical data management and perception, with the capability to detect indeterminate significance, predict prognostication, and correlate available data into a meaningful clinical endpoint. Here, the authors captured the review works over the past decades, focusing on AI in breast imaging, and systematized the included works into one usable document, which is termed an umbrella review. The present study aims to provide a panoramic view of how AI is poised to enhance breast imaging procedures. Evidence-based scientometric analysis was performed in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guideline, resulting in 71 included review works. This study aims to synthesize, collate, and correlate the included review works, thereby identifying the patterns, trends, quality, and types of the included works, captured by the structured search strategy. The present study is intended to serve as a "one-stop center" synthesis and provide a holistic bird's eye view to readers, ranging from newcomers to existing researchers and relevant stakeholders, on the topic of interest.

A meta-analysis of the value of circulating tumor cells in monitoring postoperative recurrence and metastasis of colorectal cancer

Objective

Circulating tumor cells (CTCs) as novel biomarkers are widely investigated in various cancers, although most of the literature shows that CTCs have predictive value for recurrence, metastasis, and prognosis after CRC surgery, results remain controversial. We aimed to systematically evaluate the value of CTCs in monitoring of colorectal cancer (CRC) recurrence and metastasis after surgery.

Method

The PubMed, Cochrane Library, Embase, and other databases were searched from the establishment of the database to May 27, 2021. Relevant literature searches and data extraction were performed independently by two reviewers. The quality assessment was performed using the QUADAS2 scale developed by the Cochrane collaboration. The heterogeneity was checked using the Spearman correlation coefficient and the Cochran-Q test in the Meta-Disc1.4 software. Subgroup analysis was used to explore the source of heterogeneity. Considering that all the included papers were clinical studies with clinical heterogeneity, random effect model was adopted for analysis. And the sensitivity (Sen), specificity (Spe), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and summary receiver operating characteristic (SROC) curves of CTCs, in monitoring recurrence and metastasis after CRC, were calculated. The publication bias of the included studies was assessed using Deek’s funnel figure.

Result

The literature included a total of 13 articles, comprising 1788 cases, and the overall quality of the literature was high. After summing up the indicators, the sensitivity pooled-value of the peripheral blood CTCs to monitor the recurrence and metastasis value of CRC after CRC was 0.67 [95%CI (0.62, 0.71)], specificity pooled-value was 0.71 [95%CI (0.67, 0.72)], PLR pooled-value was 2.37 [95%CI [1.52, 3.71]), NLR pooled into 0.53 [95%CI (0.36, 0.78)], DOR pooled into 4.97 [95%CI (2.11, 11.72)], AUC was 0.7395.

Conclusion

Peripheral blood CTCs have a moderate monitoring value for recurrence and metastasis after CRC; CTCs detected one week after surgery may be more correlated with recurrence and metastasis.

Novel parameter based on lipid indicators ratio improves prognostic value of plasma lipid levels in resectable colorectal cancer patients

BACKGROUND

At present, the value of lipid indicators in evaluating the prognosis of colorectal cancer is still relatively limited.

AIM

To evaluate the value of a novel parameter for colorectal cancer (CRC) prognosis scoring based on preoperative serum lipid levels.

METHODS

Four key serum lipid factors, namely, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), and apolipoprotein B (ApoB), were detected. Two representative ratios, HDL-C-LDL-C ratio (HLR) and ApoA1-ApoB ratio (ABR) were calculated. The relationship of these parameters with the prognosis of CRC patients including progression-free survival (PFS) and overall survival (OS) was analyzed by Kaplan-Meier plot and Cox proportional hazards regression. A novel lipoprotein cholesterol-apolipoprotein (LA) score based on HLR and ABR was established and its value in prognosis evaluation for CRC patients was explored.

RESULTS

Multivariate Cox proportional hazards regression analysis of PFS and OS showed that HDL-C, ApoA1, HLR, and ABR were positively associated with the prognosis of CRC patients. LA score was independently associated with a good prognosis in resectable CRC patients. Data processing of a dummy variable showed that the prognosis of patients with higher LA scores is better than that with lower LA scores.

CONCLUSION

The newly established LA score might serve as a better predictor of the prognosis of resectable CRC patients.

Classification of Mammographic Breast Microcalcifications Using a Deep Convolutional Neural Network: A BI-RADS-Based Approach

MATERIALS AND METHODS

Over 56,000 images of 268 mammograms from 94 patients were labeled to 3 classes according to the BI-RADS standard: "no microcalcifications" (BI-RADS 1), "probably benign microcalcifications" (BI-RADS 2/3), and "suspicious microcalcifications" (BI-RADS 4/5). Using the preprocessed images, a dCNN was trained and validated, generating 3 types of models: BI-RADS 4 cohort, BI-RADS 5 cohort, and BI-RADS 4 + 5 cohort. For the final validation of the trained dCNN models, a test data set consisting of 141 images of 51 mammograms from 26 patients labeled according to the corresponding BI-RADS classification from the radiological reports was applied. The performances of the dCNN models were evaluated, classifying each of the mammograms and computing the accuracy in comparison to the classification from the radiological reports. For visualization, probability maps of the classification were generated.

RESULTS

The accuracy on the validation set after 130 epochs was 99.5% for the BI-RADS 4 cohort, 99.6% for the BI-RADS 5 cohort, and 98.1% for the BI-RADS 4 + 5 cohort. Confusion matrices of the "real-world" test data set for the 3 cohorts were generated where the radiological reports served as ground truth. The resulting accuracy was 39.0% for the BI-RADS 4 cohort, 80.9% for BI-RADS 5 cohort, and 76.6% for BI-RADS 4 + 5 cohort. The probability maps exhibited excellent image quality with correct classification of microcalcification distribution.

CONCLUSIONS

The dCNNs can be trained to successfully classify microcalcifications on mammograms according to the BI-RADS classification system in order to act as a standardized quality control tool providing the expertise of a team of radiologists.

Characteristic Blood-Perfusion Reduction of Walker 256 Tumor Induced by Diagnostic Ultrasound and Microbubbles

Tumor angiogenesis is characterized by a defective, leaky and fragile microvascular construction, and microbubble-enhanced ultrasound (MEUS) with high-pressure amplitude is capable of disrupting tumor microvasculature and arresting blood perfusion. In this study, we tried to investigate whether the blood perfusion of a malignant tumor can be characteristically interrupted by combining microbubbles and diagnostic ultrasound (US). Twenty-nine Sprague-Dawley (SD) rats with subcutaneous Walker 256 tumors and seven healthy SD rats were included. Fifteen tumors were treated by MEUS, which combined constant microbubble injection and 20 episodes of irradiation by diagnostic US (i.e., acoustic radiation force impulse [ARFI] imaging). The other 14 tumors were treated by ARFI or sham US only. Seven skeleton muscles from healthy SD rats were also treated with MEUS, serving as the control. Contrast-enhanced ultrasound (CEUS) was performed before and after all treatments. The blood perfusion of the tumor MEUS group showed a significant drop immediately after treatment, followed by a quick, incomplete perfusion recovery within 10-20 min. The visual perfusion scoring result was consistent with the quantitative analysis by CEUS peak intensity. However, there were no significant perfusion changes in the tumor control groups or the muscle control group. Histologic examination found severe microvascular disruption and hemorrhage in the MEUS-treated tumors but not in the control groups. Therefore, the treatment combining diagnostic US and microbubbles can specifically decrease or interrupt the blood perfusion of Walker 256 tumors, which could be a potential new imaging method for diagnosing malignant tumors.

20(S)-Protopanaxadiol inhibits epithelial-mesenchymal transition by promoting retinoid X receptor alpha in human colorectal carcinoma cells

Colorectal carcinoma (CRC) recurrence is often accompanied by metastasis. Most metastasis undergo through epithelial‐mesenchymal transition (EMT). Studies showed that retinol X receptor alpha (RXRα) and 20(S)‐Protopanaxadiol (PPD) have anti‐tumour effects. However, the anti‐metastasis effect of 20(S)‐PPD and the effect of RXRα on EMT‐induced metastasis are few studies on. Therefore, the role of RXRα and 20(S)‐PPD in CRC cell metastasis remains to be fully elucidated. RXRα with clinicopathological characteristics and EMT‐related expression in clinical samples were examined. Then, RXRα and EMT level in SW480 and SW620 cells, overexpressed and silenced RXRα in SW620 cells and SW480 cells, respectively, were evaluated. Finally, 20(S)‐PPD effect on SW620 and SW480 cells was evaluated. The results showed that a lower RXRα expression in cancer tissues, and a moderate negative correlation between RXRα and N stage, and tended to higher level of EMT. SW480 and SW620 cells had the highest and lowest RXRα expression among four CRC cell lines. SW480 had lower EMT level than SW620. Furthermore, 20(S)‐PPD increased RXRα and inhibited EMT level in SW620 cell. Finally, 20(S)‐PPD cannot restore SW480 cells EMT level to normal when RXRα silencing. These findings suggest that 20(S)‐PPD may inhibit EMT process in CRC cells by regulating RXRα expression.

Whole mammographic mass segmentation using attention mechanism and multiscale pooling adversarial network

Purpose: Since breast mass is a clear sign of breast cancer, its precise segmentation is of great significance for the diagnosis of breast cancer. However, the current diagnosis relies mainly on radiologists who spend time extracting features manually, which inevitably reduces the efficiency of diagnosis. Therefore, designing an automatic segmentation method is urgently necessary for the accurate segmentation of breast masses. Approach: We propose an effective attention mechanism and multiscale pooling conditional generative adversarial network (AM-MSP-cGAN), which accurately achieves mass automatic segmentation in whole mammograms. In AM-MSP-cGAN, U-Net is utilized as a generator network by incorporating attention mechanism (AM) into it, which allows U-Net to pay more attention to the target mass regions without additional cost. As a discriminator network, a convolutional neural network with multiscale pooling module is used to learn more meticulous features from the masses with rough and fuzzy boundaries. The proposed model is trained and tested on two public datasets: CBIS-DDSM and INbreast. Results: Compared with other state-of-the-art methods, the AM-MSP-cGAN can achieve better segmentation results in terms of the dice similarity coefficient (Dice) and Hausdorff distance metrics, achieving top scores of 84.49% and 5.01 on CBIS-DDSM, and 83.92% and 5.81 on INbreast, respectively. Therefore, qualitative and quantitative experiments illustrate that the proposed model is effective and robust for the mass segmentation in whole mammograms. Conclusions: The proposed deep learning model is suitable for the automatic segmentation of breast masses, which provides technical assistance for subsequent pathological structure analysis.

Novel Methylated DNA Markers in the Surveillance of Colorectal Cancer Recurrence

PURPOSE

We aimed to assess the concordance of colorectal cancer-associated methylated DNA markers (MDM) in primary and metastatic colorectal cancer for feasibility in detection of distantly recurrent/metastatic colorectal cancer in plasma.

EXPERIMENTAL DESIGN

A panel of previously discovered colorectal cancer-associated MDMs was selected. MDMs from primary and paired metastatic colorectal cancer tissue were assayed with quantitative methylation-specific PCR. Plasma MDMs were measured blindly by target enrichment long-probe quantitative-amplified signal assays. Random forest modeling was used to derive a prediction algorithm of MDMs in archival plasma samples from primary colorectal cancer cases. This algorithm was validated in prospectively collected plasma samples from recurrent colorectal cancer cases. The accuracy of the algorithm was summarized as sensitivity, specificity, and area under the curve (AUC).

RESULTS

Of the 14 selected MDMs, the concordance between primary and metastatic tissue was considered moderate or higher for 12 MDMs (86%). At a preset specificity of 95% (91%-98%), a panel of 13 MDMs, in plasma from 97 colorectal cancer cases and 200 controls, detected stage IV colorectal cancer with 100% (80%-100%) sensitivity and all stages of colorectal cancer with an AUC of 0.91 (0.87-0.95), significantly higher than carcinoembryonic antigen [AUC, 0.72 (0.65-0.79)]. This panel, in plasma from 40 cases and 60 healthy controls, detected recurrent/metastatic colorectal cancer with 90% (76%-97%) sensitivity, 90% (79%-96%) specificity, and an AUC of 0.96 (0.92-1.00). The panel was positive in 0.30 (0.19-0.43) of 60 patients with no evidence of disease in post-operative patients with colorectal cancer.

CONCLUSIONS

Plasma assay of novel colorectal cancer-associated MDMs can reliably detect both primary colorectal cancer and distantly recurrent colorectal cancer with promising accuracy.

Evaluating the performance of convolutional neural networks with direct acyclic graph architectures in automatic segmentation of breast lesion in US images

Background

Outlining lesion contours in Ultra Sound (US) breast images is an important step in breast cancer diagnosis. Malignant lesions infiltrate the surrounding tissue, generating irregular contours, with spiculation and angulated margins, whereas benign lesions produce contours with a smooth outline and elliptical shape. In breast imaging, the majority of the existing publications in the literature focus on using Convolutional Neural Networks (CNNs) for segmentation and classification of lesions in mammographic images. In this study our main objective is to assess the ability of CNNs in detecting contour irregularities in breast lesions in US images.

Methods

In this study we compare the performance of two CNNs with Direct Acyclic Graph (DAG) architecture and one CNN with a series architecture for breast lesion segmentation in US images. DAG and series architectures are both feedforward networks. The difference is that a DAG architecture could have more than one path between the first layer and end layer, whereas a series architecture has only one path from the beginning layer to the end layer. The CNN architectures were evaluated with two datasets.

Results

With the more complex DAG architecture, the following mean values were obtained for the metrics used to evaluate the segmented contours: global accuracy: 0.956; IOU: 0.876; F measure: 68.77%; Dice coefficient: 0.892.

Conclusion

The CNN DAG architecture shows the best metric values used for quantitatively evaluating the segmented contours compared with the gold-standard contours. The segmented contours obtained with this architecture also have more details and irregularities, like the gold-standard contours.

Sugar alcohol provides imaging contrast in cancer detection

Clinical imaging is widely used to detect, characterize and stage cancers in addition to monitoring the therapeutic progress. Magnetic resonance imaging (MRI) aided by contrast agents utilizes the differential relaxivity property of water to distinguish between tumorous and normal tissue. Here, we describe an MRI contrast method for the detection of cancer using a sugar alcohol, maltitol, a common low caloric sugar substitute that exploits the chemical exchange saturation transfer (CEST) property of the labile hydroxyl group protons on maltitol (malCEST). In vitro studies pointed toward concentration and pH-dependent CEST effect peaking at 1 ppm downfield to the water resonance. Studies with control rats showed that intravenously injected maltitol does not cross the intact blood-brain barrier (BBB). In glioma carrying rats, administration of maltitol resulted in the elevation of CEST contrast in the tumor region only owing to permeable BBB. These preliminary results show that this method may lead to the development of maltitol and other sugar alcohol derivatives as MRI contrast agents for a variety of preclinical imaging applications.

Automatic classification of ultrasound breast lesions using a deep convolutional neural network mimicking human decision-making

OBJECTIVES

To evaluate a deep convolutional neural network (dCNN) for detection, highlighting, and classification of ultrasound (US) breast lesions mimicking human decision-making according to the Breast Imaging Reporting and Data System (BI-RADS).

METHODS AND MATERIALS

One thousand nineteen breast ultrasound images from 582 patients (age 56.3 ± 11.5 years) were linked to the corresponding radiological report. Lesions were categorized into the following classes: no tissue, normal breast tissue, BI-RADS 2 (cysts, lymph nodes), BI-RADS 3 (non-cystic mass), and BI-RADS 4-5 (suspicious). To test the accuracy of the dCNN, one internal dataset (101 images) and one external test dataset (43 images) were evaluated by the dCNN and two independent readers. Radiological reports, histopathological results, and follow-up examinations served as reference. The performances of the dCNN and the humans were quantified in terms of classification accuracies and receiver operating characteristic (ROC) curves.

RESULTS

In the internal test dataset, the classification accuracy of the dCNN differentiating BI-RADS 2 from BI-RADS 3-5 lesions was 87.1% (external 93.0%) compared with that of human readers with 79.2 ± 1.9% (external 95.3 ± 2.3%). For the classification of BI-RADS 2-3 versus BI-RADS 4-5, the dCNN reached a classification accuracy of 93.1% (external 95.3%), whereas the classification accuracy of humans yielded 91.6 ± 5.4% (external 94.1 ± 1.2%). The AUC on the internal dataset was 83.8 (external 96.7) for the dCNN and 84.6 ± 2.3 (external 90.9 ± 2.9) for the humans.

CONCLUSION

dCNNs may be used to mimic human decision-making in the evaluation of single US images of breast lesion according to the BI-RADS catalog. The technique reaches high accuracies and may serve for standardization of highly observer-dependent US assessment.

KEY POINTS

• Deep convolutional neural networks could be used to classify US breast lesions. • The implemented dCNN with its sliding window approach reaches high accuracies in the classification of US breast lesions. • Deep convolutional neural networks may serve for standardization in US BI-RADS classification.

Anti-tumor effects and mechanism of GA-13315, a novel gibberellin derivative, in human lung adenocarcinoma: an in vitro and in vivo study

Objective

To investigate the anti-tumor effects and the mechanism of the compound 13-chlorine-3, 15-dioxy-gibberellic acid methyl ester (GA-13315) in lung adenocarcinoma in vitro and in vivo.

Methods

The antiproliferative effect of GA-13313 on the A549 cell line was determined by MTT (3-[4, 5-dimethylthiazol-2-yl]-2, 5 diphenyl tetrazolium bromide) assay. A xenograft model of A549 was established to evaluate the anti-tumor effect and histopathological examination was performed to assess the toxicity of GA-13315. Apoptosis was detected by TUNEL staining in tissues and flow cytometry in cells; activation of caspase-3, caspase-8 and caspase-9 was evaluated by immunohistochemical analysis; protein levels of Bcl-2-associated X protein (Bax), B-cell lymphoma-2 (Bcl-2), caspase-4, activating transcription factor 4 (ATF4), glucose-regulated protein 78 (GRP78) and growth arrest and DNA damage-inducible gene 153 (GADD153) were determined by western blotting. Mitochondrial membrane potential (MMP) was measured by the JC-1 fluorescence probe.

Results

Our results showed that GA-13315 exhibited potent, dose- and time-dependent anti-proliferative activity, and the IC50 values were 37.43 ± 2.73, 28.08 ± 7.76 and 19.29 ± 7.61 μM at 24, 48, and 72 h, respectively. The xenograft experiment revealed that tumor weight and volume were significantly decreased after GA-13315 3 mg/kg and 9 mg/kg (P < 0.05) treatment, and GA-13315 had low toxicity in bone marrow, kidney and colon tissues. GA-13315 triggered remarkable apoptosis in A549 cells at the concentration of 25.6 μM and 32 μM (P < 0.05) and activated caspase-3, − 8 and − 9. Moreover, GA-13315 induced apoptosis through the mitochondrial apoptosis pathway by elevating the Bax/Bcl-2 ratio, releasing cytochrome c and activating caspase-9 in A549 cells. In the endoplasmic reticulum apoptosis pathway, the levels of caspase-4, ATF4, GRP78 and GADD153 were markedly upregulated.

Conclusions

This study suggests that GA-13315 can be considered as a promising chemotherapeutic agent with anticancer activity in treatment of lung cancer in future.

Down-regulated of PCDH10 predicts poor prognosis in hepatocellular carcinoma patients

Protocadherin10 (PCDH10), a member of the nonclustered protocadherin family, functions as a tumor suppressor in many cancers. The aim of this study was to evaluate the expression level and prognostic value of PCDH10 in hepatocellular carcinoma (HCC) patients.Quantitative real-time polymerase chain reaction was used to analyze the expression level of PCDH10 in HCC tissues and adjacent nontumor tissues. The association of PCDH10 expression with clinicopathological features of patients was evaluated by chi-squared test. Overall survival was estimated using the Kaplan-Meier method. Besides, the patient prognosis was also evaluated by Cox regression analysis.PCDH10 expression was significantly lower in HCC tissues than that in adjacent nontumor tissues (P = .000). Kaplan-Meier curves showed that patients with lower PCDH10 expression had a worse overall survival. Moreover, PCDH10 expression level was associated tumor size (P = .005), tumor node metastasis stage (P = .002), smoking status (P = .000), and drinking status (P = .005). Multivariate analysis showed that the expression of PCDH10 (P = .000; hazard ratio = 4.784; 95% confidence interval: 2.550-8.977) was an independently associated with poor overall survival rates, as well as smoking status and drinking status.Our findings indicated that the decreased expression of PCDH10 was closely associated with poor prognosis of HCC patients. It might be considered as a valuable biomarker for HCC.

A predicting model of bone marrow malignant infiltration in 18F-FDG PET/CT images with increased diffuse bone marrow FDG uptake

Purpose: To demonstrate the relationship between the etiologies of increased diffuse bone marrow (BM) ¹⁸F-FDG uptake and PET/CT imaging/clinical features, as well as to explore a predicting model of BM malignant infiltration (MI) based on decision tree. Methods: 84 patients with increased diffuse BM uptake were retrospectively enrolled. Their complete case record and PET/CT images were reviewed, with the maximal standardized uptake values of bone marrow (SUVmaxBM) and other imaging/clinical features were noted. At the same time, the differences in imaging/clinical features between bone marrow MI and non-MI groups were compared. The decision tree for predicting MI was established by C5.0 component of SPSS Clementine. Results: In patients with homogenously increased BM uptake, 21 patients had MI resulted from leukemia, lymphoma and small cell lung cancer (SCLC). MI group had higher SUVmaxBM than non-MI group (6.7±3.1 vs 4.2±0.9, p=0.001). However, a considerable proportion of MI patients had similar SUVmaxBM to non-MI patients, which were mainly seen in lymphoplasmacytic lymphoma/Waldenström macroglobulinemia (LPL/WM), chronic myeloid leukemia (CML) and multiple myeloma (MM). There were significant differences in other factors between the two groups. MI patients were highly associated with SUVmaxAP/AX≥1 (the ratio of SUVmaxBM of appendicular skeleton to that of axial skeleton), hepatosplenomegaly, older age and lower rate of fever. The decision tree combining SUVmaxBM, SUVmaxAP/AX, fever and hepatosplenomegaly achieved a sensitivity of 81.0%, a specificity of 98.4% and an accuracy of 94.0% for predicting MI. Conclusion: Increased diffuse BM ¹⁸F-FDG uptake can be attributed to both bone marrow MI and benign etiologies. A decision tree based on C5.0 algorithm, combining PET/CT imaging and clinical features, is of potential use in discriminating BM malignant infiltration from patients with increased diffuse BM uptake.

Prognostic Value of Bone Marrow FDG Uptake Pattern of PET/CT in Newly Diagnosed Diffuse Large B-cell Lymphoma

Purpose: The value of ¹⁸F-fluorodeoxyglucose positron emission tomography /computed tomography (¹⁸F-FDG PET/CT) in assessing bone marrow involvement (BMI) of lymphoma remains controversial. The present study aims to evaluate the prognostic meaning of bone marrow FDG uptake pattern in PET/CT of newly diagnosed diffuse large B-cell lymphoma (DLBCL) patients.

Materials and Methods: 193 newly diagnosed DLBCL patients were retrospectively analyzed. All patients received 6-8 cycles of rituximab plus cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP). The type of BM FDG uptake pattern was recorded by two blinded reviewers independently. The relationship between clinicopathologic features and BM patterns was analyzed. The prognostic value of different BM patterns was evaluated by Log-rank test and Cox-regression analysis.

Results: Out of 193 patients, 28 (15%) patients had focal BM FDG uptake higher than liver (fPET+), 18 (9%) patients showed diffuse BM uptake higher than liver (dPET+) and 147 (76%) patients had normal BM uptake (lower than liver) (nPET). BMB positive was found in 35.7% (10/28) of fPET+ patients, in 16.7% (3/18) of dPET+ patients and in 0.7% (1/147) of nPET patients. Diffuse BM pattern was associated with lower hemoglobin level and a trend of higher erythrocyte sedimentation rate (ESR). dPET+ patients had similar 3y-progression-free survival (3y-PFS) and 3y-overall survival (3y-OS) compared with nPET patients (80.5% vs 81.5%, p=0.701; 94.1% vs 90.6%, p=0.809, respectively), while fPET+ patients had worse 3y-PFS and 3y-OS compared with fPET- patients (32.7% vs 81.4%, p<0.001; 69.4% vs 90.9%, p=0.003, respectively). Multivariate analysis showed fPET+ (HR=2.270, p=0.025) and stage III/IV (HR=4.909, p=0.026) were independent predictors for PFS, but no factors were independently predictive for OS.

Conclusion: PET/CT-directed BM patterns are meaningful in predicting prognosis of newly diagnosed DLBCL patients. Focal BM pattern is an independent predictor for PFS.

An eight-year prospective controlled study about the safety and diagnostic value of cardiac and non-cardiac 1.5-T MRI in patients with a conventional pacemaker or a conventional implantable cardioverter defibrillator

OBJECTIVES

To investigate safety and diagnostic value of 1.5-T MRI in carriers of conventional pacemaker (cPM) or conventional implantable defibrillator (cICD).

METHODS

We prospectively compared cPM/cICD-carriers undergoing MRI (study group, SG), excluding those device-dependent or implanted <6 weeks before enrolment or prior to 01/01/2000, with cPM/cICD-carriers undergoing chest x-ray, CT or follow-up (reference group, RG).

RESULTS

142 MRI (55 cardiac) were performed in 120 patients with cPM (n=71) or cICD (n=71). In the RG 98 measurements were performed in 95 patients with cPM (n=40) or cICD (n=58). No adverse events were observed. No MRI prolonged/interrupted. All cPM/cICD were correctly reprogrammed after MRI without malfunctions. One temporary communication failure was observed in one cPM-carrier. Immediately after MRI, 12/14 device interrogation parameters did not change significantly (clinically negligible changes of battery voltage and cICD charging time), without significant variations for SG versus RG. Three-12 months after MRI, 9/11 device interrogation parameters did not change significantly (clinically negligible changes of battery impedance/voltage). Non-significant changes of three markers of myocardial necrosis. Non-cardiac MRI: 82/87 diagnostic without artefacts; 4/87 diagnostic with artefacts; 1/87 partially diagnostic. Cardiac MRI: in cPM-carriers, 14/15 diagnostic with artefacts, 1/15 partially diagnostic; in cICD-carriers, 9/40 diagnostic with artefacts, 22 partially diagnostic, nine non-diagnostic.

CONCLUSIONS

A favourable risk-benefit ratio of 1.5-T MRI in cPM/cICD carriers was reported.

KEY POINTS

• Cooperation between radiologists and cardiac electrophysiologists allowed safe 1.5-T MRI in cPM/cICD-carriers. • No adverse events for 142 MRI in 71 cPM-carriers and 71 cICD-carriers. • Ninety-nine per cent (86/87) of non-cardiac MRI in cPM/cICD-carriers were diagnostic. • All cPM-carrier cardiac MRIs had artefacts, 14 examinations diagnostic, 1 partially diagnostic. • Twenty-three per cent (9/40) of cardiac MRI in cICD-carriers were non-diagnostic.

Dual Modality Imaging of Promoter Activity as a Surrogate for Gene Expression and Function

Molecular functional imaging with optical reporter genes (both bioluminescence and fluorescence) is a rapidly evolving method that allows noninvasive, sensitive, real-time monitoring of many cellular events in live cells and whole organisms. These reporter genes with optical signatures when expressed from gene-specific promoters or Cis/Trans elements mimic the endogenous expression pattern without perturbing cellular physiology. With advanced recombinant molecular biology techniques, several strategies for optimal expression from constitutive or inducible, tissue-specific and weak promoters have been developed and used for dynamic and functional imaging. In this chapter, we provide an overview of the applications of this powerful technology for imaging gene expression in living cells and rodent models.

Cell-surface marker discovery for lung cancer

Lung cancer is the leading cause of cancer deaths in the United States. Novel lung cancer targeted therapeutic and molecular imaging agents are needed to improve outcomes and enable personalized care. Since these agents typically cannot cross the plasma membrane while carrying cytotoxic payload or imaging contrast, discovery of cell-surface targets is a necessary initial step. Herein, we report the discovery and characterization of lung cancer cell-surface markers for use in development of targeted agents. To identify putative cell-surface markers, existing microarray gene expression data from patient specimens were analyzed to select markers with differential expression in lung cancer compared to normal lung. Greater than 200 putative cell-surface markers were identified as being overexpressed in lung cancers. Ten cell-surface markers (CA9, CA12, CXorf61, DSG3, FAT2, GPR87, KISS1R, LYPD3, SLC7A11 and TMPRSS4) were selected based on differential mRNA expression in lung tumors vs. non-neoplastic lung samples and other normal tissues, and other considerations involving known biology and targeting moieties. Protein expression was confirmed by immunohistochemistry (IHC) staining and scoring of patient tumor and normal tissue samples. As further validation, marker expression was determined in lung cancer cell lines using microarray data and Kaplan–Meier survival analyses were performed for each of the markers using patient clinical data. High expression for six of the markers (CA9, CA12, CXorf61, GPR87, LYPD3, and SLC7A11) was significantly associated with worse survival. These markers should be useful for the development of novel targeted imaging probes or therapeutics for use in personalized care of lung cancer patients.

Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks

Breast lesion detection using ultrasound imaging is considered an important step of computer-aided diagnosis systems. Over the past decade, researchers have demonstrated the possibilities to automate the initial lesion detection. However, the lack of a common dataset impedes research when comparing the performance of such algorithms. This paper proposes the use of deep learning approaches for breast ultrasound lesion detection and investigates three different methods: a Patch-based LeNet, a U-Net, and a transfer learning approach with a pretrained FCN-AlexNet. Their performance is compared against four state-of-the-art lesion detection algorithms (i.e., Radial Gradient Index, Multifractal Filtering, Rule-based Region Ranking, and Deformable Part Models). In addition, this paper compares and contrasts two conventional ultrasound image datasets acquired from two different ultrasound systems. Dataset A comprises 306 (60 malignant and 246 benign) images and Dataset B comprises 163 (53 malignant and 110 benign) images. To overcome the lack of public datasets in this domain, Dataset B will be made available for research purposes. The results demonstrate an overall improvement by the deep learning approaches when assessed on both datasets in terms of True Positive Fraction, False Positives per image, and F-measure.

SWCNTs as novel theranostic nanocarriers for cancer diagnosis and therapy: towards safe translation to the clinics

With their unique physicochemical properties, single walled carbon nanotubes (SWCNTs) hold great promise for applications as drug delivery systems (DDS) for early and better diagnosis and therapy of cancer. While several in vitro and in vivo studies have validated their potential benefit, no SWCNT-based formulation has yet reached clinical trials. Towards prospective safe clinical applications, the main properties that were adopted to enhance the biocompatibility of SWCNTs were highlighted. Then, the recent progresses in the in vivo applications of SWCNTs as diagnostic nanoprobes using multimodality imaging techniques and as therapeutic nanocarriers delivering wide range of anticancer efficient drugs to tumors were reviewed. Finally, the efforts required for safe clinical applications of SWCNTs as DDS for cancer diagnosis and therapy were discussed.

Overexpression of BIRC6 Is a Predictor of Prognosis for Colorectal Cancer

BACKGROUND AND OBJECTIVE

Inhibitors of apoptosis proteins (IAPs) have been well investigated in human cancers, where they are frequently overexpressed and associated with poor prognosis. Here we explored the role of baculoviral IAP repeat containing 6 (BIRC6), a member of IAPs, in human colorectal cancer (CRC).

METHODS

We used Western blotting and immunohistochemistry to examine BIRC6 expression in 7 CRC cell lines and 126 CRC clinical samples. We determined the biological significance of BIRC6 in CRC cell lines by a lentivirus-mediated silencing method.

RESULTS

We reported that BIRC6 was overexpressed in CRC cell lines and clinical CRC tissues. BIRC6 overexpression was correlated with tumor size and invasion depth of CRC. BIRC6 overexpression is associated with worse overall survival (OS) (P = 0.001) and shorter disease-free survival (DFS) (P = 0.010). BIRC6 knockdown inhibited cell proliferation, arrested cell cycle at S phase, downregulated cyclin A2, B1, D1 and E1 levels, and sensitized CRC cells to chemotherapy in vitro and in vivo.

CONCLUSIONS

Taken together, these data suggests that BIRC6 overexpression is a predictor of poor prognosis in colorectal cancer and BIRC6 could be a potential target of CRC therapy.

Computerized detection of breast lesions using deformable part models in ultrasound images

Ultrasound imaging is considered an important complementary technique for the screening of dense breasts. Detection of lesions at an early stage is a key step in which computerized lesion detection systems could play an important role in the analysis of US images. In this article, we propose adaptation of a generic object detection technique, deformable part models, to detect lesions in breast US images. The data set used in this study included 326 images, all from different patients (54 malignant lesions, 109 benign lesions and 163 healthy breasts). In terms of lesion detection, our proposal outperformed some of the most relevant approaches described in the literature; we obtained a sensitivity of 86% with 0.28 false-positive detection per image and an Az value of 0.975. In the detection of malignant lesions, our proposed approached had an Az value of 0.93 and a sensitivity of 78% at a 1.15 false-positive detections per image.

In vitro and in vivo anti-tumour effects of MPT0B014, a novel derivative aroylquinoline, and in combination with erlotinib in human non-small-cell lung cancer cells

BACKGROUND AND PURPOSE

The purpose of the current study was to assess a novel anti-cancer drug, MPT0B014, which is not a substrate for the P-glycoprotein (P-gp) transporter, alone and in combination with erlotinib, against human non-small cell lung cancer (NSCLC).

EXPERIMENTAL APPROACH

Cytotoxicity in human NSCLC cell lines was assessed by sulforhodamine B and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assays. Cell cycle phase distributions were estimated with FACScan flow cytometry. Protein expression was detected by Western blotting analysis. Efflux of rhodamine 123 or calcein-acetoxymethylester was used to study the P-gp profile. The A549 xenograft model in mice was used to assess in vivo anti-tumour activity.

KEY RESULTS

MPT0B014 showed potent anti-proliferative activity against A549, H1299 and H226 cells. It induced G2/M arrest with down-regulation of Cdc (Tyr15) and Cdc25C, and up-regulation of cyclin B1, phospho-Cdc2 (Thr161) and Aurora A/B. P-gp-overexpressing National Cancer Institute/Adriamycin-Resistant cells were also sensitive to B014. B014-induced loss of Mcl-1 was accompanied by activation of caspases-3, -7, -8 and -9, and initiation of apoptosis. B014 in combination with erlotinib caused significant tumour inhibition in vitro and in vivo.

CONCLUSIONS AND IMPLICATIONS

MPT0B014 exerted cytotoxicity against human NSCLC cell lines with little susceptibility to P-gp. Combined with the EGF receptor inhibitor, erlotinib, MPT0B014 exerted significant growth inhibition of A549 cells both in vitro and in vivo. B014 could be useful as an anti-cancer agent.

Update on pediatric leukemia and lymphoma imaging

Together, leukemia and lymphoma account for half of all childhood malignancies. Leukemia and lymphoma arise from similar cell lines and can have overlapping imaging features; however, the clinical presentation, imaging strategies, and treatment protocols can vary substantially based on the specific subtype. Although imaging does not play a central role in staging or monitoring disease in childhood leukemia, findings on imaging may be the first indication of the diagnosis. Advanced imaging, especially positron emission tomography/computed tomography, has moved to the forefront of staging and treatment response evaluation in Hodgkin's disease and non-Hodgkin's lymphoma. Imaging also plays a key role in evaluating the myriad of treatment complications that are commonly seen with chemotherapy and associated neutropenia. Future efforts will be largely focused on decreasing radiation exposure to these children, utilizing reduced or radiation-free modalities, such as positron emission tomography/magnetic resonance and diffusion-weighted whole-body imaging with background suppression, as well as refining surveillance imaging strategies. The purpose of this article is to briefly review the classification of pediatric leukemia and lymphoma, illustrate common imaging findings at presentation throughout the body, describe staging and therapeutic response evaluation, and show a spectrum of commonly encountered complications of treatment.

Meta-analysis of the association between COX-2 polymorphisms and risk of colorectal cancer based on case-control studies

OBJECTIVE

Cyclooxygenase-2 (COX-2) is an inducible enzyme converting arachidonic acid to prostaglandins and playing important roles in inflammatory diseases as well as tumor development. Previous studies investigating the association between COX-2 polymorphisms and colorectal cancer (CRC) risk reported conflicting results. We performed a meta-analysis of all available studies to explore this association.

METHODS

All studies published up to October 2013 on the association between COX-2 polymorphisms and CRC risk were identified by searching electronic databases PubMed, EMBASE, and Cochrane library. The association between COX-2 polymorphisms and CRC risk was assessed by odds ratios (ORs) together with their 95% confidence intervals (CIs).

RESULTS

Ten studies with 6,774 cases and 9,772 controls were included for -1195A>G polymorphism, 13 studies including 6,807 cases and 10,052 controls were available for -765G>C polymorphism, and 8 studies containing 5,121 cases and 7,487 controls were included for 8473T>C polymorphism. With respect to -765G>C polymorphism, we did not find a significant association with CRC risk when all eligible studies were pooled into the meta-analysis. However, in subgroup analyses by ethnicity and cancer location, with a Bonferroni corrected alpha of 0.05/2, statistical significant increased CRC risk was found in the Asian populations (dominant model CC+CG vs. GG: OR = 1.399, 95%CI: 1.113-1.760, P = 0.004) and rectum cancer patients (CC vs. GG: OR = 2.270, 95%CI: 1.295-3.980, P = 0.004; Recessive model CC vs. CG+GG: OR = 2.269, 95%CI: 1.297-3.970, P = 0.004). In subgroup analysis according to source of control, no significant association was detected. With respect to -1195A>G and 8473T>C polymorphisms, no significant association with CRC risk was demonstrated in the overall and subgroup analyses.

CONCLUSIONS

The present meta-analysis suggests that the COX-2 -765G>C polymorphism may be a risk factor for CRC in Asians and rectum cancer patients. Further large and well-designed studies are needed to confirm this association.

CASP8 -652 6N del polymorphism contributes to colorectal cancer susceptibility: evidence from a meta-analysis

Objective

Caspase-8 (CASP8) plays a central role in the apoptotic pathway and aberrant regulation of this pathway may cause cancers. Previous studies investigating the association between CASP8 -652 6N ins/del polymorphism and colorectal cancer (CRC) risk showed inconclusive results. We performed a meta-analysis of all available studies to investigate this association.

Methods

All studies published up to October 2013 on the association between CASP8 -652 6N ins/del polymorphism and CRC risk were identified by searching electronic databases PubMed, EMBASE, and Cochrane library. The association between CASP8 -652 6N ins/del polymorphism and CRC risk was assessed by odds ratios (ORs) together with their 95% confidence intervals (CIs).

Results

Six studies with 6,325 cases and 6,842 controls were included in the meta-analysis. We observed that the CASP8 -652 6N ins/del polymorphism was significantly correlated with CRC risk when all studies were pooled into the meta-analysis (ins/del vs. ins/ins: OR = 0.890, 95%CI 0.821–0.964, P = 0.004; del/del + ins/del vs. ins/ins: OR = 0.899, 95%CI 0.833–0.970, P = 0.006). In stratified analyses by ethnicity, source of control, and quality score, significant association was observed in Asians (ins/del vs. ins/ins: OR = 0.862, 95%CI 0.761–0.977, P = 0.020; del/del + ins/del vs. ins/ins: OR = 0.845, 95%CI 0.749–0.953, P = 0.006), population-based studies (ins/del vs. ins/ins: OR = 0.890, 95%CI 0.813–0.975, P = 0.012; del/del + ins/del vs. ins/ins: OR = 0.901, 95%CI 0.827–0.982, P = 0.018), and high quality studies. However, in subgroup analysis according to cancer location, no significant association was detected.

Conclusions

The present meta-analysis suggests that the CASP8 is a candidate gene for CRC susceptibility. The CASP8 -652 6N ins/del polymorphism may play a protective role in CRC development especially among Asians. Further large and well-designed studies are needed to confirm this association.

Ultrasound-triggered phase transition sensitive magnetic fluorescent nanodroplets as a multimodal imaging contrast agent in rat and mouse model

Ultrasound-triggered phase transition sensitive nanodroplets with multimodal imaging functionality were prepared via premix Shirasu porous glass (SPG) membrane emulsification method. The nanodroplets with fluorescence dye DiR and SPIO nanoparticles (DiR-SPIO-NDs) had a polymer shell and a liquid perfluoropentane (PFP) core. The as-formed DiR-SPIO-NDs have a uniform size of 385±5.0 nm with PDI of 0.169±0.011. The TEM and microscopy imaging showed that the DiR-SPIO-NDs existed as core-shell spheres, and DiR and SPIO nanoparticles dispersed in the shell or core. The MTT and hemolysis studies demonstrated that the nanodroplets were biocompatible and safe. Moreover, the proposed nanodroplets exhibited significant ultrasound-triggered phase transition property under clinical diagnostic ultrasound irradiation due to the vaporization of PFP inside. Meanwhile, the high stability and R₂ relaxivity of the DiR-SPIO-NDs suggested its applicability in MRI. The in vivo T₂-weighted images of MRI and fluorescence images both showed that the image contrast in liver and spleen of rats and mice model were enhanced after the intravenous injection of DiR-SPIO-NDs. Furthermore, the ultrasound imaging (US) in mice tumor as well as MRI and fluorescence imaging in liver of rats and mice showed that the DiR-SPIO-NDs had long-lasting contrast ability in vivo. These in vitro and in vivo findings suggested that DiR-SPIO-NDs could potentially be a great MRI/US/fluorescence multimodal imaging contrast agent in the diagnosis of liver tissue diseases.

The Emerging Role of Elastography in Cancer

Real-time elastography is an emerging sonographic imaging technique that provides a noninvasive method of evaluating biomechanical properties of a lesion: specifically, the elasticity, or stiffness, of the cellular composition relative to surrounding tissue. Clinical studies have demonstrated the diagnostic capability of elastography to detect specific cancers with accuracy that may substantially affect patient care and improve outcome. This literature review examines the basics of elastography, the advantages and limitations of this technique, and the results of research centered on its role in cancer detection and evaluation of tissue response to cancer therapies.

Biomarker research with prospective study designs for the early detection of cancer

This article describes the principles of marker research with prospective studies along with examples for diagnostic tumor markers. A plethora of biomarkers have been claimed as useful for the early detection of cancer. However, disappointingly few biomarkers were approved for the detection of unrecognized disease, and even approved markers may lack a sound validation phase. Prospective studies aimed at the early detection of cancer are costly and long-lasting and therefore the bottleneck in marker research. They enroll a large number of clinically asymptomatic subjects and follow-up on incident cases. As invasive procedures cannot be applied to collect tissue samples from the target organ, biomarkers can only be determined in easily accessible body fluids. Marker levels increase during cancer development, with samples collected closer to the occurrence of symptoms or a clinical diagnosis being more informative than earlier samples. Only prospective designs allow the serial collection of pre-diagnostic samples. Their storage in a biobank upgrades cohort studies to serve for both, marker discovery and validation. Population-based cohort studies, which may collect a wealth of data, are commonly conducted with just one baseline investigation lacking serial samples. However, they can provide valuable information about factors that influence the marker level. Screening programs can be employed to archive serial samples but require significant efforts to collect samples and auxiliary data for marker research. Randomized controlled trials have the highest level of evidence in assessing a biomarker's benefit against usual care and present the most stringent design for the validation of promising markers as well as for the discovery of new markers. In summary, all kinds of prospective studies can benefit from a biobank as they can serve as a platform for biomarker research. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

Associations of CYP2E1 rs2031920 and rs3813867 polymorphisms with colorectal cancer risk: a systemic review and meta-analysis

Cytochrome P450 2E1 (CYP2E1) is a natural enzyme involved in the metabolic activation of many carcinogens, and the functional polymorphisms in the CYP2E1 gene might have impacts on colorectal cancer risk. Many studies were published to assess the associations of CYP2E1 rs2031920 and rs3813867 polymorphisms with colorectal cancer risk, but no consistent findings were reported. A systemic review and meta-analysis of eligible studies was performed to comprehensively assess the associations above. Odds ratios (ORs) with 95 % confidence interval (95 % CIs) were used to assess the strength of the associations. Seventeen studies from 15 publications with 17,082 individuals were finally included into this meta-analysis. Meta-analysis of the 13 studies on CYP2E1 rs2031920 polymorphism showed that there was a significant association between CYP2E1 rs2031920 polymorphism and colorectal cancer risk under two genetic models (c2 versus c1: OR = 1.19, 95 % CI 1.03-1.37, P = 0.022; c2c2/c2c1 versus c1c1: OR = 1.16, 95 % CI 1.00-1.35, P = 0.046). Meta-analysis of those four case-control studies on CYP2E1 rs3813867 polymorphism showed that there was no significant association between CYP2E1 rs3813867 polymorphism and colorectal cancer risk under all contrast models (c2 versus c1: OR = 0.96, 95 % CI 0.80-1.16, P = 0.672; c2c2 versus c1c1: OR = 1.26, 95 % CI 0.43-3.67, P = 0.672; c2c2/c1c2 versus c1c1: OR = 0.95, 95 % CI 0.78-1.16, P = 0.114; and c2c2 versus c1c2/c1c1: OR = 1.17, 95 % CI 0.41-3.36, P = 0.775). Therefore, the findings from this meta-analysis suggest that CYP2E1 rs2031920 polymorphism is associated with colorectal cancer risk, but CYP2E1 rs3813867 polymorphism is not associated with colorectal cancer risk. In addition, more well-designed studies with large sample size are needed to provide a more precise evaluation on the associations above.