Detection Of Cancer Tumors Research Articles

Segmentation and Classification of Breast Cancer Tumour

Breast cancer is cancer that forms in the cells of the breasts. Breast cancer is the most common cancer diagnosed in women in the world. Breast cancer can occur in both men and women, but it's far more common in women. Early detection of breast cancer tumours is crucial in the treatment. In this study, we presented a computer aided diagnosis expectation maximization segmentation and co-occurrence texture features from wavelet approximation tumour image of each slice and evaluated the performance of SVM Algorithm. We tested the model on 50 patients, among them, 25 are benign and 25 malign. The 80% of the images are allocated for training and 20% of images reserved for testing. The proposed model classified 2 patients correctly with success rate of 80% in case of 5 Fold Cross-Validation 
 Keywords: Breast Cancer, Computer-Aided Diagnosis (CAD), Magnetic Resonance Imaging (MRI);

Design of I-shaped dual C-slotted rectangular microstrip patch antenna (I-DCSRMPA) for breast cancer tumor detection

Cancer is the uncontrolled growth of abnormal cells; if not detected and treated at the early stage cancer would become fatal. Breast cancer remains the second leading cause of cancer induced deaths, despite the advances taken place in treatment methods. The incidence of breast cancer in India is on the rise that one in 22 women in India is likely to suffer from breast cancer during her lifetime. One in eight women is affected by this dangerous disease in America. Cancer always a major problem to the world however various methods are available. Some of methods for breast cancer detection are X-ray mammography, MRI and ultrasound. However, they have some limitations to detect the breast cancer but microwave imaging is a safer method as compared to the X-ray. In this Paper cancer tumour in the breast is detected by I-shaped dual C-slotted microstrip patch antenna is designed for 10 GHz. The proposed antenna has a bandwidth of 7.51 dB covering the frequency range 4.9–7.89 GHz, the return loss below − 37 dB and antenna gain of 2.45 dB. The flexible this patch antenna holds good efficiency of 87.1%.

Privacy Preserving with M-SVM Classifier of Tumor Classification in Mammography Images Using Multiple Otsu'S Thresholding Technique

Breast Cancer is formed by an abnormal development of cells in breast. The cells of body separate in an incessant method and occupy to surrounding tissues. It is the important reason of death amongst women and after lung cancer breast cancer is second cause of women deaths. Early breast cancer detection can lead to death rate decrease. The mammography is executed to discover the breast cancer tumor at earlier stages. Early breast cancer tumors detection based on the both the radiologists capability to read mammogram images and image quality. The tumors classification is a medical application that set a huge issue for in the breast cancer recognition area. Therefore, in this paper, a multiple otsu's thresholding method is presented with Mutlti-class SVM (M-SVM) classifier to enhance the tumor classification in mammogram images for cancer tumor detection. In this process, elimination of artifacts, noise and surplus parts that are presented in mammogram images by employing preprocessing tasks and after that it improves the mammogram image contrast utilizing CLAHE (Contrast Limited Adaptive Histrogram Equalization) technique for simpler recognition of tumors in breast. We segment the images using Multiple Otsu's thresholding technique to identify the region of interest in mammogram image after preprocessing and image enhancement. The GLDM (Gray Level Difference Method) is exploited to extract the features from the mammogram image. Feature extraction has been employed to with hindsight examine screening mammograms in use prior to the malignant mass discovery for early breast cancer tumor detection. The extracted features can be given to the M-SVM Classifier to classify the tumor in mammogram image into malignant, benign or normal based on the features. The classification accurateness based on the stage of feature extraction. Results of mammogram image is planned by classification and lastly image categorized into Normal, malignant or Benign. Experimental results of proposed method can show that this presented technique executes well with the accurateness of classification reaching almost 84% in evaluation with existing algorithms.

Development of Halofluorochromic Polymer Nanoassemblies for the Potential Detection of Liver Metastatic Colorectal Cancer Tumors Using Experimental and Computational Approaches.

To develop polymer nanoassemblies (PNAs) modified with halofluorochromic dyes to allow for the detection of liver metastatic colorectal cancer (CRC) to improve therapeutic outcomes. We combine experimental and computational approaches to evaluate macroscopic and microscopic PNA distributions in patient-derived xenograft primary and orthotropic liver metastatic CRC tumors. Halofluorochromic and non-halofluorochromic PNAs (hfPNAs and n-hfPNAs) were prepared from poly(ethylene glycol), fluorescent dyes (Nile blue, Alexa546, and IR820), and hydrophobic groups (palmitate), all of which were covalently tethered to a cationic polymer scaffold [poly(ethylene imine) or poly(lysine)] forming particles with an average diameter<30nm. Dye-conjugated PNAs showed no aggregation under opsonizing conditions for 24h and displayed low tissue diffusion and cellular uptake. Both hfPNAs and n-hfPNAs accumulated in primary and liver metastatic CRC tumors within 12h post intravenous injection. In comparison to n-hfPNAs, hfPNAs fluoresced strongly only in the acidic tumor microenvironment (pH<7.0) and distinguished small metastatic CRC tumors from healthy liver stroma. Computational simulations revealed that PNAs would steadily accumulate mainly in acidic (hypoxic) interstitium of metastatic tumors, independently of the vascularization degree of the tissue surrounding the lesions. The combined experimental and computational data confirms that hfPNAs detecting acidic tumor tissue can be used to identify small liver metastatic CRC tumors with improved accuracy.

CdS quantum dot-chitosan-anti SP17 nanohybrid as a potential cancer biomarker

Sperm protein 17 (SP17) is selectively overexpressed in several human malignancies including ovarian carcinoma, but is absent or expressed at low levels in most normal tissues. In this research, a nanohybrid of cadmium sulphide (CdS)-chitosan-anti SP17 was developed for the first time. Chitosan was covalently conjugated with CdS-anti SP17 by using the 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) and sulfo-(N-hydroxysulfosuccinimide) (sulfo-NHS). The nanostructures were characterized by Fourier transform infrared spectroscopy (FIIR) and transmission electron microscopy (TEM). FTIR results demonstrated successful conjugation of chitosan to cadmium sulphide (CdS) quantum dots. The TEM images indicated formation of ultra-small nanocrystals with average diameters in the range of 3nm. Moreover, ELISA result showed relatively high binding ability of QDs to the Sp17 recombinant antigen, which could be potentially used for detection and imaging of cancer tumors.

Dual nano-sized contrast agents in PET/MRI: a systematic review.

Nowadays molecular imaging plays a vital role in achieving a successful targeted and personalized treatment. Hence, the approach of combining two or more medical imaging modalities was developed. The objective of this review is to systematically compare recent dual contrast agents in Positron Emission Tomography (PET)/Magnetic Resonance Imaging (MRI) and in some cases Single photon emission computed tomography (SPECT)/MRI in terms of some their characteristics, such as tumor uptake, and reticuloendothelial system uptake (especially liver) and their relaxivity rates for early detection of primary cancer tumor. To the best of our knowledge, this is the first systematic and integrated overview of this field. Two reviewers individually directed the systematic review search using PubMed, MEDLINE and Google Scholar. Two other reviewers directed quality assessment, using the criteria checklist from the CAMARADES (Collaborative Approach to Meta-Analysis and Review of Animal Data from Experimental Studies) tool, and differences were resolved by consensus. After reviewing all 49 studies, we concluded that a size range of 20-200 nm can be used for molecular imaging, although it is better to try to achieve as small a size as it is possible. Also, small nanoparticles with a hydrophilic coating and positive charge are suitable as a T2 contrast agent. According to our selected data, the most successful dual probes in terms of high targeting were with an average size of 40 nm, PEGylated using peptides as a biomarker and radiolabeled with copper 64 and gallium 68. Copyright © 2017 John Wiley & Sons, Ltd.

Applying a modified version of Lyapunov exponent for cancer diagnosis in biomedical images: the case of breast mammograms

Recently, there has been a great interest in the application of Lyapunov exponents for calculation of chaos levels in dynamical systems. Accordingly, this study aims at presenting two new methods for utilizing Lyapunov exponents to evaluate the spatiotemporal chaos in various images. Further, early detection of cancerous tumors could be obtained by measuring the chaotic indices in biomedical images. Unlike the available systems described by partial differential equations, the proposed method employs a number of interactive dynamic variables for image modeling. Since the Lyapunov exponents cannot be applied to such systems, the image model should be modified. The mean Lyapunov exponent is defined as a chaotic index for measuring the contour borders irregularities in images to detect benign or malignant tumors. Moreover, a two-dimensional mean Lyapunov exponent is incorporated to identify irregularities existing in each axis of the targeted images. Experiments on a set of region of interest in breast mammogram images yielded a sensitivity of 95 % and a specificity of 97.3 % and verified the remarkable precision of the proposed methods in classifying of breast lesions obtained from breast mammogram images.

(Invited) Spectral Triangulation: A Novel 3D Method for Locating Single-Walled Carbon Nanotubes In Vivo

Nanomaterials with luminescence in the short-wave infrared (SWIR) region are of special interest for biological research and medical diagnostics because of relatively favorable tissue transparency in that region. Single-walled carbon nanotubes (SWCNTs) show sharp SWIR spectral signatures and therefore have the potential for noninvasive detection and imaging of cancerous tumors when linked to selective targeting agents such as antibodies. However, such applications face the challenge of detecting and localizing the source of light emission from inside tissues. We present here a new method, called spectral triangulation, for sensitively locating SWCNT emission sources in three dimensions using only optical measurements at the specimen surface. SWCNTs inside tissue phantoms are excited by an LED array, and resulting SWIR emission is captured by a scanning fiber optic probe coupled to an InGaAs spectrometer or avalanche photodiode detector. Because of water absorption, attenuation of the SWCNT fluorescence in tissues is strongly wavelength-dependent. We can therefore gauge the distance between SWCNTs and probe by analyzing differential changes in the measured SWCNT emission spectra. SWCNT fluorescence is clearly detected though as much as 22.5 mm of tissue phantom, and the three-dimensional locations of SWCNT samples are deduced with sub-millimeter accuracy at depths up to 10 mm. Our method can also distinguish and locate dual SWCNT sources within tissues.

Increased precision of orthotopic and metastatic breast cancer surgery guided by matrix metalloproteinase-activatable near-infrared fluorescence probes.

Advanced medical imaging technology has allowed the use of fluorescence molecular imaging-guided breast cancer surgery (FMI-guided BCS) to specifically label tumour cells and to precisely distinguish tumour margins from normal tissues intra-operatively, a major challenge in the medical field. Here, we developed a surgical navigation system for real-time FMI-guided BCS. Tumours derived from highly metastatic 4T1-luc breast cancer cells, which exhibit high expression of matrix metalloproteinase (MMP) and human epidermal growth factor receptor 2 (HER2), were established in nude mice; these mice were injected with smart MMP-targeting and “always-on” HER2-targeting near-infrared (NIR) fluorescent probes. The fluorescence signal was imaged to assess in vivo binding of the probes to the tumour and metastatic sites. Then, orthotopic and metastatic breast tumours were precisely removed under the guidance of our system. The post-operative survival rate of mice was improved by 50% with the new method. Hematoxylin and eosin staining and immunohistochemical staining for MMP2 and CD11b further confirmed the precision of tumour dissection. Our method facilitated the accurate detection and complete removal of breast cancer tumours and provided a method for defining the molecular classification of breast cancer during surgery, thereby improving prognoses and survival rates.

Semi-automated breast cancer tumor detection with thermographic video imaging.

Screening for breast cancer enables early detection by which curative treatment can be possible. While mammography is the current gold standard for screening, it has low sensitivity in younger women and its harmful X-rays in frequent screening can increase the risk of cancer. Incidence rates are rising in younger women, causing a relook at thermography for low cost and non-harmful screening. In this paper, thermography is compared to mammography correlated with sono-mammography in 65 FNAC/biopsy proven cancer subjects in India. Thermography is comparable to mammography correlated with sono-mammography, having 94% and 95% sensitivity, respectively. A novel semi-automated thermographic tumor detection and location algorithm used in this paper also provides 97% sensitivity. This shows the promise of automated thermographic screening for reaching large populations in a cost effective manner in low resource settings in countries like India. Further studies in a large scale need to be done to evaluate the specificity to enable such solutions.

Promises and challenges of fluorescence cystoscopy

IntroductionFluorescence based photodynamic diagnostic (PDD) techniques have been developed to improve detection and treatment of non-muscle invasive bladder cancer. The goal of this article is to evaluate the promises and challenges of blue light cystoscopy. MethodsThe literature was reviewed regarding articles pertaining to fluorescent cystoscopy and blue light cystoscopy (BLC). ResultsBlue light cystoscopy improves detection of bladder cancer tumors especially CIS. Randomized trials have demonstrated a reduction of recurrences. BLC has been demonstrated to be safe and effective in treatment of NMIBC of varying risk. The main obstacle to BLC will be adoption by urologists. Purchase cost of capital equipment may impact usage especially if adopted for outpatient clinics. ConclusionsBLC has been demonstrated to be safe and effective in treatment of NMIBC of varying risk. The reduction of recurrences and yet unproven but potential reduction in progression should be viewed favorably by urologists and patients. The main obstacle to BLC will be adoption by urologists who can put pressure on hospitals to acquire the capital equipment and who will seek the training to become proficient in using the technology. Patient demand for the technology may also help increase availability. Finally, the companies involved with BLC need to support trials that will demonstrate reduction in progression and that will answer the practical issues regarding usage in proximity to BCG and repeated usage.

Microstrip patch antenna for breast cancer tumour detection: a survey

In early days breast cancer detection is of crucial importance. Breast cancer is a serious threat worldwide and is the number two killer of women in the USA. Microstrip patch antenna, due to its various advantages i.e. small size, light weight, low profile, and low manufacturing cost, is finding increasing applications in the medical industry. In this paper, we elaborate microstrip patch antenna with technical specification and its application for breast cancer tumour detection. The key to successful management is screening and early detection. What follow is a description of the state of the art in screening and detection for breast cancer as well as a discussion of new and emerging technologies. The only way today to find out for sure if a breast lump or abnormal tissue is cancer is by having a biopsy: a suspicious tissue is removed by a surgical excision or needle biopsy and is examined under a microscope by a pathologist who makes the diagnosis. Imaging techniques of the breast are therefore vital since they will allow early detection of cancer and localisation of the suspicious lesion in the breast for a biopsy procedure.

Inorganic-bimolecular hybrids based on polyoxometalates: Intrinsic oxidase catalytic activity and their application to cancer immunoassay

A series of inorganic-biomolecular hybrids FAnPMo12−nVnO40 (n=1, 2, and 3, abbreviated as FAPMoVn, FA represents folic acid) had been synthesized through self-assembly of bioactive molecules folic acids and phosphovanadomolybdates. These folate-functionalized hybrids had been proved to possess unique oxidase-like activity in the oxidation of dyes, which can catalyze oxidation of the peroxidase substrate 3,3′,5,5′-tetramethylbenzidine (TMB) by air to form a blue color in aqueous solution. Among all hybrids, FAPMoV3 performed best. Based on their oxidase property, an approach instead of traditional horseradish peroxidase (HRP)-labeled assay for the visual detection of cancer tumors by FAPMoV3 had been built up. FAPMoV3 exhibited fast response and high efficiency in colorimetric immunoassay of cancer cells at a neutral pH condition.

LAT-1 based primary breast cancer detection by [99m]Tc-labeled DTPA-bis-methionine scintimammography: first results using indigenously developed single vial kit preparation.

To evaluate the diagnostic utility of a single vial ready to label with [99m]Tc kit preparation of DTPA-bis-methionine (DTPA-bis-MET) for the detection of primary breast cancer. The conjugate (DTPA-bis-MET) was synthesized by covalently conjugating two molecules of methionine to DTPA and formulated as a single vial ready to label with [99m]Tc lyophilized kit preparations. Thirty female patients (mean age=47.5±11.8 years; range=21-69 years) with radiological/clinical evidence of having primary breast carcinoma were subjected to [99m]Tc-methionine scintigraphy. The whole body (anterior and posterior) imaging was performed on all the patients at 5 minutes, 10 minutes, 1 hour, 2 hours, and 4 hours following an intravenous administration of 555-740 MBq radioactivity of [99m]Tc-methionine. In addition, scintimammography (static images; 256×256 matrix) at 1, 2, and 4 hours was also performed on all the patients. The resultant radiolabel, that is, [99m]Tc-DTPA-bis-MET, yielded high radiolabeling efficiency (>97.0%), radiochemical purity (166-296 MBq/μmol), and shelf life (>3 months). The radiotracer primarily gets excreted through the kidneys and localizes in the breast cancer lesions with high target-to-nontarget ratios. The mean±SD ratios on the scan-positive lesions acquired at 1, 2, and 4 hours postinjection were 3.6±0.48, 3.10±0.24, and 2.5±0.4, respectively. [99m]Tc-methionine scintimammography demonstrated an excellent sensitivity and positive predictive value of 96.0% each for the detection of primary breast cancer. Ready to label single vial kit formulations of DTPA-bis-MET can be easily synthesized as in-house production and conveniently used for the scintigraphic detection of breast cancer and other methionine-dependent tumors expressing the L-type amino acid transporter-1 receptor. The imaging technique thus could be a potential substitute for the conventional single-photon emission computed tomography (SPECT)-based tumor imaging agents, especially for tracers with nonspecific mitochondrial uptake. However, the diagnostic efficacy of [99m]Tc-methionine needs to be evaluated in a large cohort of patients through further multicentric trials.

Fluorescent nanohybrids based on quantum dot-chitosan-antibody as potential cancer biomarkers.

Despite undeniable advances in medicine in recent decades, cancer is still one of the main challenges faced by scientists and professionals in the health sciences as it remains one of the world's most devastating diseases with millions of fatalities and new cases every year. Thus, in this work, we endeavored to synthesize and characterize novel multifunctional immunoconjugates composed of quantum dots (QDs) as the fluorescent inorganic core and antibody-modified polysaccharide as the organic shell, focusing on their potential applications for in vitro diagnosis of non-Hodgkin lymphoma (NHL) cancer tumors. Chitosan was covalently conjugated with anti-CD20 polyclonal antibody (pAbCD20) via formation of amide bonds between amines and carboxyl groups. In the sequence, these biopolymer-antibody immunoconjugates were utilized as direct capping ligands for biofunctionalization of CdS QDs (CdS/chitosan-pAbCD20) using a single-step process in aqueous medium at room temperature. The nanostructures were characterized by UV-vis spectroscopy, photoluminescence spectroscopy (PL), FTIR, and transmission electron microscopy (TEM) with selected area electron diffraction. The TEM images associated with the UV-vis optical absorption results indicated formation of ultrasmall nanocrystals with average diameters in the range of 2.5-3.0 nm. Also, the PL results demonstrated that the immunoconjugates exhibited "green" fluorescent activity under ultraviolet excitation. Moreover, using in vitro laser light scattering immunoassay (LIA), the QDs/immunoconjugates have shown binding affinity against antigen CD20 (aCD20) expressed by lymphocyte-B cancer cells. In summary, innovative fluorescent nanoimmunoconjugate templates were developed with promising perspectives to be used in the future for detection and imaging of cancer tumors.

In vivo photoacoustic imaging of breast cancer tumor with HER2-targeted nanodiamonds.

Radiation-damaged nanodiamonds (NDs) are ideal optical contrast agents for photoacoustic (PA) imaging in biological tissues due to their good biocompatibility and high optical absorbance in the near-infrared (NIR) range. Acid treated NDs are oxidized to form carboxyl groups on the surface, functionalized with polyethylene glycol (PEG) and human epidermal growth factor receptor 2 (HER2) targeting ligand for breast cancer tumor imaging. Because of the specific binding of the ligand conjugated NDs to the HER2-overexpressing murine breast cancer cells (4T1.2 neu), the tumor tissues are significantly delineated from the surrounding normal tissue at wavelength of 820 nm under the PA imaging modality. Moreover, HER2 targeted NDs (HER2-PEG-NDs) result in higher accumulation in HER2 positive breast tumors as compared to non-targeted NDs after intravenous injection (i.v.). Longer retention time of HER-PEG-NDs is observed in HER2 overexpressing tumor model than that in negative tumor model (4T1.2). This demonstrates that targeting moiety conjugated NDs have great potential for the sensitive detection of cancer tumors and provide an attractive delivery strategy for anti-cancer drugs.

Claudins overexpression in ovarian cancer: potential targets for Clostridium Perfringens Enterotoxin (CPE) based diagnosis and therapy.

Claudins are a family of tight junction proteins regulating paracellular permeability and cell polarity with different patterns of expression in benign and malignant human tissues. There are approximately 27 members of the claudin family identified to date with varying cell and tissue-specific expression. Claudins-3, -4 and -7 represent the most highly differentially expressed claudins in ovarian cancer. While their exact role in ovarian tumors is still being elucidated, these proteins are thought to be critical for ovarian cancer cell invasion/dissemination and resistance to chemotherapy. Claudin-3 and claudin-4 are the natural receptors for the Clostridium perfringens enterotoxin (CPE), a potent cytolytic toxin. These surface proteins may therefore represent attractive targets for the detection and treatment of chemotherapy-resistant ovarian cancer and other aggressive solid tumors overexpressing claudin-3 and -4 using CPE-based theranostic agents.

Gene selection for cancer tumor detection using a novel memetic algorithm with a multi-view fitness function

Cancer is one of the key research topics in the medical field. An accurate detection of different cancer tumor types has great value in providing better treatment facilities and risk minimization for patients. Recently, DNA microarray-based gene expression profiles have been employed to correlate the clinical behavior of cancers with the differential gene expression levels in cancerous and benign tumors. An accurate classifier with linguistic interpretability using a small number of relevant genes is beneficial to microarray data analysis and development of inexpensive diagnostic tests. Several well-known and frequently used techniques for designing classifiers from microarray data, such as a support vector machine, neural networks, k-nearest neighbor, and logistic regression model, suffer from low comprehensibility. This paper proposes a new memetic algorithm which is capable of extracting interpretable and accurate fuzzy if–then rules from cancer data. This paper is the first proposal of memetic algorithms with the Multi-View fitness function approach. The new presented Multi-View fitness function considers two kinds of evaluating procedures. The first procedure, which is located in the main evolutionary structure of the algorithm, evaluates each single fuzzy if–then rule according to the specified rule quality (the evaluating procedure does not consider other rules). However, the second procedure determines the quality of each fuzzy rule according to the whole fuzzy rule set performance. In comparison to classic memetic algorithms, these kinds of memetic algorithms enhance the rule discovery process significantly.

Analysis of a UWB Hemispherical Antenna Array in FDTD With a Time Domain Huygens Method

Electromagnetic modeling is needed in a wide variety of large and complex situations. Existing numerical techniques such as finite difference time domain (FDTD) can, in principle, solve any problem no matter how large or complicated given a sufficiently powerful computer. However, in practice, there remain problems which require more computer power than is available. Recently, the time-domain Huygens (TDH) approach has been shown to be effective for enabling large problems such as propagation on body area networks (BANs) to be modeled in FDTD. In this paper, it is shown that the much larger problem of the conformal antenna array, which is used in the MARIA breast cancer tumor detection system, is also very amenable to this technique with even greater savings in computer resources. Accurate results are obtained using less that a tenth of the resources needed to solve the same problem using existing advanced FDTD tools. The details of how this method is applied, and the choices which need to be made, are discussed.

Impact of delay after biopsy and post-biopsy haemorrhage on prostate cancer tumour detection using multi-parametric MRI: A multi-reader study

To assess impact of haemorrhage and delay after biopsy on prostate tumour detection using multi-parametric (MP) magnetic resonance imaging (MRI) assessment. Forty-four patients underwent prostate MRI at 1.5 T using a pelvic phased-array coil, including T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging, before prostatectomy. Three radiologists independently reviewed images during four sessions [T2WI, DWI, DCE, and all parameters combined (MP-MRI)] to assess for tumour in each sextant. In a separate session, readers reviewed T1WI to score the extent of haemorrhage per sextant. Accuracy was assessed using logistic regression for correlated data. There was no significant difference in accuracy between readers for any session (p ≥ 0.166), and results were averaged across the three readers for remaining comparisons. Accuracy was significantly greater for MP-MRI than for any parameter alone (p ≤ 0.020). For T2WI alone, there was a trend toward decreased sensitivity in sextants with extensive haemorrhage (p = 0.072). However, accuracy, sensitivity, and specificity were otherwise similar for sextants with and without extensive haemorrhage for all sessions (p = 0.192-0.934). No session showed a significant improvement in accuracy, sensitivity, or specificity in cases with delay after biopsy of over 4 weeks compared with shorter delay. Extensive haemorrhage and short delay after biopsy did not negatively impact accuracy for tumour detection using MP-MRI. Further studies using MP-MRI protocols and interpretation schemes from other institutions are required to confirm these observations.