review on dot and trus to detect prostate cancer

D. S. DIAS, ADVANCED MEDICAL IMAGING PROJECT, SPRING 2015 1

Recent Improvements on Prostate cancer imagingusing DOT , TRUS and their bi-modality, for early

detection and follow-upDiogo S. Dias, [email protected], UID U00777095, Advanced Medical Images, Wright

State University, April 10th, Spring 2015,Dayton,OH.Professor: Mr. Nasser Kashou

AbstractProstate Cancer is one of the most commoncancer among men. Trans-rectal ultrasound Guided-biopsyis used to confirm the prostate cancer, however it still failswhen we have hypo-echoic cancer or multifocal tumors,early detection of prostate cancer cant be achieved withthis method.This review intends to verify what proceduresare being made with the imaging techniques interstitialdiffuse tomography, Trans-Rectal Ultrasound and theircombination in order to improve prostate cancer detection.It was found that the bimodal imaging technique couldobserve earlier prostate cancer than the conventionalmethod, and that the algorithms used by these techniquesmust be improved.

Index TermsProstate Cancer, TRUS, DOT, early de-tection.

I. INTRODUCTION

PROSTATE cancer(PCa) is the most commonone among men, with about 200,000 new casesdiagnosed every year [1],[2] and it is the secondone that most leads american men to death[1],[3]bringing death to 28,000 American men every year.Even though the number has been decling over thelast decade[4], its claimed that there is a need ofimproved methods and techniques for diagnosingand treating PCa.

A. Diagnosing and treating Procedures

The procedure of diagnosing PCa is showed onfigure 1. Its generally recommended that the proce-dure starts for 50-year-old men or 40-year-old menwith family history of the disease, and this have tobe done yearly[4]. The first part of the procedure canbe the digital rectal examination (DRE) which canoften distinguish normal from cancer tissue despitesthat more than half of the PCa are not palpable,or through the prostate-specific antigen (PSA) thatonly if it shows a very high value( bigger than 20

Fig. 1. Block diagram to summarize the nowadays procedure usedfor PCa Diagnosing[4]

ng/ml) there is a high probability of a detected PCa,for lower levels(4-10 ng/ml)its a gray zone.[4],[5]. When DRE or PSA shows a abnormal results,a prostate biopsy follows to try to confirm theexistence of the PCa, this procedure is performedaround 1 million times a year in American men[4].

The Treatment of PCa is usually prostate removalfor high-grade cases [4] and using interstitial photodynamic therapy(PDT) for optimal treatment forpreserving non pathological surrounding structures[4]-[9].

B. TRUS-guided PCa biopsy

Trans-rectal ultrasound(TRUS) guided biopsy isconsidered the gold standard for diagnosing PCa,it consists usually on retrieving 12 cores samples[2], [3], [4], [10], [11] with of 1 - 2mm longcores.Theoretically these cores are taken around


of the entire gland but the cores are preferablyretrieved from peripheral regions where most ofcancers are usually found [4],this amount of coresare taken in order to increase the chance to retrievea cancer sample, however it can be unnecessarilypainful and risky for the patients [10],[12]. Thestandard technique ranges from 20-30% of positiverate, this low positive rate can lead to false negativein a lot of cases [4], additionally Prostate biopsytechnique has 30% of false negative for PCa dueto poor visibility of cancers [3],[10].Other impor-tant fact is that Multifocal PCa are 85% of thecases of PCa and this technique is not so sensitiveto them[4],[13]. Early stage PCa are difficult todistinguish from normal tissue, what can lead toboth misdiagnose and unnecessary biopsies [14],It is said that 60% of PCa are hypoechoic , inother words , they cant be much differentiated fromnormal tissue in ultrasound images, additionallya considerable amount of cancer are iso-echoicwith respect to the surrounding parenchyma.If thoseearly stage PCa were detected the cancer treatmentswould have a greater chance of success[5]. TRUSby itself is generally considered to be insufficientfor diagnosing or staging PCa, it has low sen-sitivity and specificity and its generally limitedto guidance for biopsy, prostate volume measure-ment and brachyterapy seed placement[14].There isalso Speckle noise and boundaries errors in TRUSprostate imaging [15],[3],[16] , it also have artifactsdue movement of the prostate and movements ofpatient due discomfort from the procedure, andthe pressed prostate also has a different imageduring the procedure , what claims for a real timeimage to reduce misalignments and wrong biop-sies [3],[16]. The good aspects of TRUS is thatit can provide real-time imaging [15],[4],low costcompared to other modalities, slightly invasive, andnon-ionizing procedure [15], TRUS is consideredto be the best modality for reveling morphologyof the structures, this feature is because of its7MHz Ultrasound used to delineate boundaries ofthe prostate with sufficient resolution. It also canevaluate blood flow(through doppler capability) andthere is a purposed designed probe that can lead tothe intrapelvic prostates position, for better imageof the organ.[4].In order to improve even more theTRUS the user of computed methods or the use ofthe contrast can do it[14].

C. Alternative Methods for imaging PCa

Among the alternatives that try to increase theaccuracy or reduce the number of samples taken,there are established imaging modalities as MRIand CT. However they are high costed, and cannotdisplay real-time imaging during prostate biopsy[4].

One good option for imaging PCa is opticalTomography based on NIRS(Near Infraredspectrocopy), as known as Diffuse OpticalTomography(DOT)[5],[17], specifically becauseNIR imaging is based on optical contrastsof chromophores, such as oxygenated andnon-oxygenated hemoglobin, and there is analteration of vascularity in the tumor what canhelp to distinguish optical tumor and benigntissues[5],[12],[13]. Another important feature isthe possibility of using multispectral NIRS lookingonly for cancer tissue. Although this importantfeature there are some limitations in NIR imaging,like low penetration for imaging because lo thereis small spacing for the detectors in trans rectalapplication and consequently low possibility to gethigh resolution and NIRS imaging is generally notgood in spatial resolution aspect[5].

DOT is a non-ionizing imaging method [17],[18]which illuminates tissue with a near-infrared light(650-1000nm) coming from a array of sources , afterinteractions some emerging light coming from theirradiated tissue is measured either by a detectorarray or optical fibers[19], its said that a minimumof 10 sources and detectors are required for aminimum spatial resolution [5]. The measured datais called boundary data [19] it then can be repre-sented in Maps of oxygenation or concentration,absorption, reduce scatter among other optical dataof chromophores present in tissue [17],[18].

There are two ways the boundary data can bereconstructed, the first is the forward model thatconsists in creating a spatial map of optical param-eters such as scattering and absorption coefficientsof tissues[18]. The second one is the inverse model,which is used for retrieving other optical parametersas blood volume, oxygen concentration or otherchromophores concentration[17],[18]. there is alsotwo more ways to reconstruct the images linearlyor non-linearly, the linear one reconstruct changesin optical properties through time its faster butlacks in giving accurate information, because thesechanges are usually small, and the problem of recon-


struction is indeed nonlinear [17]. Using nonlinearlyreconstruction are generally used in more powerfulapplications using better sources and detectors, aswell solving more complex applications like 3Dreconstruction[20]. For more detailed informationand deeper thoughts about DOT physics and theoryconsult the papers[17],[18],[19].

Combinations of TRUS with other modalities likeMRI shows promising results [2], as well TRUS-DOT that is going to be discussed in this review.There is also not so less popular imaging PCamethods like bioimpedance and mechanical imagingof the prostate commented by Piao et al [4].

D. Purpose of the study

This paper intends to present a review among al-ternative techniques for improving PCa early detec-tion and following-up treatment as computed TRUStechniques, iDOT and DOT and the bimodality ofTRUS+DOT, in order to verify which technique(s)are showing to be more promissing.

II. METHODS

A. Review Procedure

The papers used in this review range from2008 to 2015(until March), The data base re-search sites used were wright states universitylibraries ,scholar.google.com and pubmed.com TheKey terms used for the research were prostatecancer DOT,Prostate cancer TRUS, and Prostatecancer DOT TRUS.Then Ive filtered by the rangeof dates Ive said above, and by their relevance tothe purpose of the study. Finally Ive separeted thepapers in 3 categories :

1) iDOT2) Computed TRUS3) bi-modal TRUS+DOTA summarize of the methods used by each cate-

gory follows

B. iDOT

Most of papers using iDOT, used COMSOL 3D tobuild their finite element mathematical models andtheir mesh models with 3D real slices of TRUS.They have also used NIRFAST for reconstructing2D or 3D images and retrieve optical properties.Andthe reconstructions were performed genearally in

desktop computers with 2.4Ghz of Processor and2GB of RAM [6],[7], [8],[9].

NIRFAST is a MATLABs toolbox for multi-modal Near infrared imaging , bioiluminesce andfluorescence imaging processing.Its available forfree for academic research.[17],[19] A summarizeof the algorithm with flowcharts[?] are showed onthe appendix A.

Most of papers use iDOT isotropic detectorssurrounding or in the prostate, this configuration isshowed in Fig 2.

Fig. 2. Isotropic configuration with 12 isotropic detectors and 5sources, the sources are the red Xs and the blue stacks are thedetectors(adapted from Wang and Zhu [8])

Liang et al [6] used 12 detectors surrounding6 sources placed in parallel inserted cathethers, ina pattern that 4 detectors surrounding isotropicallyeach source in a solid sphere model with 3 anoma-lies mimicking a prostate optical properties, thelight sources and detectors were controlled by amotorized system with visual basic code that wasresponsible for scanning and recording the data.After building a finite model and reconstructing theimage, a MATLAB function determined the relativesource positions. The NIRFAST used in this studywas a modified version to use for continuous waveproblems. When there were misalignment errors orincorrectly recorded occurs data were excluded.

Liang et al [7] used a mathematical model to buildtheir model from the contours of a real TRUS of aprostate image, in this model two anomaly blobswere inserted. A similar solid model from Lianget al 2012 with a difference that the sources weremade by 12 cylindrical diffusing fibers placed withvarying distances 2,3 and 4cm, the sources wereilluminated by a laser(15W,732nm).


Wang and Zhu [8] used a patients data with re-current prostate that was receiving a PDT, the 5 lightsources(laser diode, wavelength: 735nm,Power:150mW) were positioned 1 cm apart each otherand 12 detectors surrounding the sources(inside andoutside the prostate) were used for light fluencemeasurements. TRUS recorded slices were usedfor the spatial resolution of the prostate model,a mathematical model was also used .At last thismethod was compared to a point-to-point method.

Wang and Zhu 2009-3 [9] used two mathematicalmodels , a sphere and a cylindrical shape in orderto evaluate the accuracy of their forward methodfor reconstruction. It was compared the capabilityof the algorithm both in 2D and 3D.

Zhou and Zhu [8]compared endoscopic and in-terstitial DOT, in the sense of quality.His modelwas a cylindrical 3D model, with rectum walls.They evaluated in plane and off-plane measurementsand single-layer and three-layer configurations. Theendoscopic DOT had 3 sources and 4 detectors,while the iDOT had 12 detectors and 6 sources.

An example of a reconstructed image of a iDOTis showed in Fig. 3

C. Computed TRUS

Thanganel and Manavalan [24] made a studyto evaluate soft computing feature selection algo-rithms, used to detect PCa , a set of 5500 imageswere analyzed. First the normal from abnormalimages were divided. The procedure of processingthe images was then followed by the first the seg-mentation of the prostate in the images, a featurevector is calculated for each image and its usedas an input to the feature selection algorithms,these algorithms are used then to highlight the mostwanted or dominating features of the images, at lastthe prostate cancer is detected with a trained patternrecognition method.

Qiu et al [21] used a 5-9MHz TRUS transducerand the resolution of 448x448x350 cubic voxels ofthe size of 19mm3, 5 patient images were used tooptimize parameter values and 30 to validate theirmethod. Their semi-automatic method consisted infour steps: 2 boundary points are chosen manuallyon the tranverse axis; The 3D TRUS is resliced in 30equal angular spacing about the rotational scanningaxis resulting in a 3d volume; The initial contouris estimated using cardinal spline interpolation. The

Fig. 3. Example of reconstructed image from Near infrared , A1 andA2 represent the phantoms for absorption and scattering reconstruc-tion images respectively.B1 and B2 are the absorption and scatteringreconstructed images respectively(adapted from Wang and Zhu [8]

slices are then propagated to its adjacent slices inboth the clockwise and counterclockwise until allslices are segmented. This method was compared toother rotational-slice methods regarding sensitivity,accuracy, mean surface area and volume differenceobtained by the method compared to a manualmeasurement from professionals.

Qiu et al 2015[2] tried to improve their algorithmfrom 2013 , the difference from the previous code isthat when choosing two manually chosen points incoronal view, A convex optimization method drivenby histogram matching is then used to segmentthe prostate contour in this slice with a nonlinearstatistical shape prior learned by the statistical shapeof the kernel principle component analysis.The res-olution and TRUS transducer were also the sameas the 2013 study and it was used 25 patientsfor training the algorithm, and 30 for testing thealgorithm.

Pummer et al [14] made a review of several tech-niques to improve PCa diagnosis but only computedTRUS and contrast enhanced TRUS are techniques


that match with the scope of this review.Dehgan and Salimi[15]used an automatic 2D

prostate segmentation algorithm method that con-sisted in using a sticks filter in order to removespeckle noise, and the images are also smoothedenhancing the contrast of the prostates edges, Sec-ondly a neural network is employed to find a pointin the prostate and then determine the thresholdsof the prostate to be segmented, from this point.At last an active gradient vector flow is used toextract the prostate boundaries. In order to validatethis algorithm 23 TRUS images were used , 15 forvalidation, 8 for neural network.

De Silva et al [3] proposed an automatic algo-rithm in order to reduce errors in TRUS-guidedbiopsy due to movement artifacts and deformationof the prostate during the procedure. In order to do ittheir algorithm use an intensity-based image regis-tration technique to compensate prostate movementand displacement. The imaging was made by a 5-9MHz TRUS probe to acquire 3D-TRUS before thebiopsy procedure starts with 8 patients , and thenrecording 2-D images from the same slice, at livetime. In the second protocol 3D TRUS of 10 patientswere acquired by applying centrally, low, mediumand high pressure from the probe to the prostate, inorder to evaluate the deformed prostate images. Theaccuracy of the algorithm images was measured byusing a target registration error.

De Silva et al 2014 [16]used a different procedurein this new study, it was acquired 7 3D-TRUSimages each one corresponding to a prostate sextantin 29 patients, while the 3D images were beingreconstructed 2D planes images were acquired inthe position of each sextant. the 3D images had aresolution of 224x224x175 with 0.37mm isotropicvoxels, it took around 10s for each reconstruction.Registration accuracy was also measured in thisstudy.

Segmenting the prostate is a recurrent from somepapers cited above, an example of a segmentationof the prostate is showed below.

D. Bi-modal TRUS+DOT

Piao et al 2010 [4]used a TRUS probe withlongitudinal array of sources(840nm) and detectorson the same probe, the TRUS provides a betterspatial resolution and compensate the reconstructiontime of the NIR image. The resolution obtained for

Fig. 4. Example of Segmented Prostate, on the left a preprocessedimage and on the right the segmented area of the prostate(fromThangavel and Manavalan [24]

of the Near infrared image was a volume of 80mmx 70mm x 60mm . The model used was a 4-year-old dog with induced PCa with TVT cells in itsprostate and it was monitored. After the 8th weekof the cancer induction the dog was euthanized andthen necropsy and histological analysis were doneon the prostate.

Bernhart et al [10] used a 2D endorectalsensor with 10 optical fibers inserted on it,where six of them emit light through a laserbeam(770nm,80MHz and 10mW).The measure-ments were made in a phantom with fluorescentmarkers, representing tumors in the prostate withfluorescent contrast. Two different probes were usedin the same phantom.

Boutet et al [12] used a Titanium-Saphire Laser(50 ns, 730nm, 80 MHz), the detector is a high rateimager intensifier system with filters, multichannelplate and a CCD camera. The Ultrasound systemused was a commercial US system in a translationalsystem moving in steps of 1mm in order to get the3D image, the frequency of the ultrasound used was6.7MHz. To validate the system a phantom mimick-ing the prostate optical properties, a inclusion of afluorescent glass was made in a 1cm depth in thephantom.

Jiang et al [26] proposed a triple wavelength(705nm/50mW,785nm/100mW,808nm/200mW)system where the 7 sources and 7 detectors wereplaced laterally the TRUS probe. A 7-year-olddog was used as a model. The system to measureHemoglobin concentration and oxygen saturationwas calibrated with oxygenated and non oxygenatedbovine blood in a mimicking tissue tube. The modelused was a 7-year old dog with injected neoplasticTVT cells, the dog was monitored weekly throughthe TRUS, ultrasound doppler and the opticalimaging.


Jiang et al [13] used a similar method andmaterials used by their other study,2011 with thedifference that only 2 sources of different wave-lengths(785 nm and 830 nm) were used, and onlythe Hemoglobin concentration is calculated. Themodel was also different, for this study a 6 year-old dog was used.

Kavuri and Liu [27] use a cluster hierarchicalmethod to look for prostate cancer, this methodconsists in making a region of interest partiallyheterogeneous and then its possible to search itand then reconstruct the potential cancer lesions.This method is then validated by simulation, anda phantom model. In the simulation a 16 detec-tor/sources simulating probe was designed as wella prostate phantom using a finite element model, ananomaly was created 1-cm deep in the prostate. InThe phantom model measurements, A broad-bandpulsed laser source (740nm, 40mW ) , and an arrayof photodetectors were used each source was spacedby 1 cm as well the detectors, and the distancessource-detector were 2cm, the phantom is made ofa liquid tissue material mimicking optical propertiesof the prostate with a 1.5-cm absorber to mimic acancer.

Piao et al [25] show their design of a NIR/TRUSprobe , that is built from a commercial bi-planeTRUS transducer, with 5Mhz transverse imagingtransducer and a 7.5 MHz sagital imaging trans-ducer. A source and a detector array are placedon the sagital part along the probe, each arrayhad 7 channels, each detector-detector and source-source were equally spaced by 1cm, and the source-detector distances were 2cm. The system was val-idate by simulation, analyze of its sensitivity andin a experimental setup to detect a blob in a liquidmean.The probe is showed in the figure 5.

Xu et al [5] used the probe designed by Piao etal [25] to make some more tests to validate this de-signed probe, more simulations are done in order todo it, a prostate was reconstructed using COMSOL

Fig. 5. Bimodal TRUS+DOT probe designed by Piao et al 2008with source array indicated by the red pointers, and the detector arrayindicated by the yellow ones(Adapted from Piao et al [25]

and 3dMax from a real prostate ultrasound image,with a hierarchical algorithm for the reconstructionby using the idea that an initial-guess and thenmitigate the local minimize the problem commonto the reconstruction.

III. RESULTS

A. iDOT

Liang et al [6] said that the accuracy of the codegave a satisfactory result for both absorption andreduce scattering coefficient, in order to find theanomalies. Removing the misaligned and incorrectlycollected data manually, the data is even improvedin the reconstruction to find the anomalies. TheiDOT reconstruction algorithm took 58 minutes torun 23 iterations.

Liang et al 2013 [7]using a simple geometry,the method was validated to provide reasonableaccuracy could be achieved with this method. Ittook 18 minutes for the mathematical phantomto be reconstructed 58 for the solid model. Thefinal projection errors of the last iteration of thereconstruction were 0.9 for the mathematical modelto 6.2 for the solid model.Thus the accuracy of thesolid model is not so good as the mathematical ones.Theyve said that the algorithm must be improvedfor near-future applications.

Wang and Zhu 2009 [8]showed that their methodin a mathematical model for retrieving the opticalproperties were pretty close of the optical propertiesof absorbing and scattering, however cross-talk inthe image was observed. Their algorithm took 30min to run when using the patients data for recon-struction, they got inconsistency in their results, andthen they have discovered that moving the detectorsaway by 0.1cm got them better results for recon-structing the image, but they still didnt got goodresults, however not only the moved detectors givethem closer results for both reconstruction methods,but also gave better results for the other unmoveddetectors. In the end of the paper they suggested totake the heterogeneity of the prostate into accountand make a system that can have parameter changeslike power, lengths and position. They also intendto work with regional base algorithm.

Wang and Zhu [9]showed that for 2D slices ittook 15 s for the algorithm to reconstruct the im-ages, and the scatter coefficient was 14% lower thanthe real one. While for the 3D models it took 2 hours


for the reconstruction and the scatter coefficientis closer to the real values than the 2D models,however the absorption coefficients are lower thanin the 2D model, and not so accurate as the 2Dmodel for absorption coefficient true values. Theysaid that their code speed needs to be improved,and in real patients, closer detectors give a bettersignal-to-noise ratio.

Zhou and Zhu [22]found that they needed 8detectors and [8]sources to reconstruct a 2D imagewith the endoscopic DOT, and the 6 sources and 12detectors were enough for the iDOT. It was foundalso that the iDOT is considerably better to detectdeeper anomalies. Other founding is that iDOT isbetter for 3D reconstruction when not using off-plane configurations.

B. Computed TRUS

Thanganel et al [24] result was that the anycolony optimization based feature selection in com-bination with a quick reduction method showedto be the feature selection algorithm to give thebetter results in a view of specificity, accuracyand sensitivity. However the other methods showedoptimum results for accuracy and specificity as well.The proposed method by Qiu [21] for segmentationof the prostate showed a better sensitivity( 93%), and a shorter volume difference from manualmeasurements(2.6cm3. The code is relatively fast,it takes around a minute for doing one prostatesegmentation, and 30 seconds for the initializationof the code in MATLAB, in a computer with a2.6GHz computer.

The improved Qiu [2] algorithm showed similarresults in the segmentation performance regardingsensitivity and accuracy but its speed was consid-erably improved , the segmentation took around14s and the initialization took 5s.However theyvepointed that their code has some limitations asaccumulation of errors during segmentation.

In Pummer et al review [14] is said that theenhanced contrast TRUS techniques improve 10-26% to look for PCa, but some studies says thatthere is no difference et al from conventional tech-niques, it is said also that most of contrast enhancedTRUS are based on the injection on microbubblesand the idea that prostate tissue has hypervascularityand in some cases like benign prostatic hyperplasiaand prostatitis there is the possibility of a false-

positive result. Regarding the computer-based an-alyzed TRUS, their review found that there is aimprovement in the Pca detection rate of 40-68%,and one good side is that there is no need of furtherrequired equipment.

Dehgani and Salimis [?]algorithm for segment-ing 2D TRUS prostate images, obtained a good re-sult for automating the segmentation process of theprostate presenting about 1-3% error in comparisonto a radiologist segmentation.

De Silva et al [3]movement compensation algo-rithm presented a measured accuracy of less than2mm and the registration took 1.1 seconds. as thisalgorithm is that fast the authors suggested thatthis algorithm could be used during TRUS-guidedbiopsy procedures.

De Silva et al [16] found in their study that asthe amount of the planes used in reconstruction isincreased the errors of the reconstruction is reducedbut on the other side the registration time is alsoincreased. The 3D images helped to improve con-siderably the accuracy and robustness in regions likethe apex and base of the prostate.

C. Bi-modal TRUS+DOT

Piao et al [4]found that it was possible to observethe growth of cancer in 2 weeks after the TVT cellsinjection, and it was before TRUS could see it. Andby combining DOT with TRUS and combining theit was possible to have more accurate findings oftumor growth than with TRUS alone. The probefound optimal sensitivity 1.5 cm away from theprobe.

Bernhart et al [10] showed that their reconstruc-tion had inconsistent results, it was accurate forone centered inclusion, being 4mm away from thereal distance. And with 2 off-centered incisionsthey are detected but with wrong reconstructionpositioning. They commented that their reconstruc-tion code should be refined and the fluorescencereconstruction with more than one incision getsmore complex.

Boutet et al [12] achieved success in their pro-posed system for detecting and localizing the flu-orescent object, a uncertainty of 0.4cm in theirproposed system, and the max depth that the systemcould achieve was 2.5cm. The images had a postprocessing in a computer. They proposed also thattheir reconstruction algorithm should be improved


to take the heterogeneities of the prostate intoaccount of the reconstruction, and to merge thereconstructed fluorescent image with the ultrasoundimage.

Jiang et al [26] showed that the measurements anddetections made by the optical imaging were con-sistent with both the Ultrasound Doppler as well thehistological analysis. Besides detecting tumors it thedetection of bleedings in peripheral regions of theprostate and a necrosis region could be found fromthe relation of oxygen saturation and Hemoglobinconcentration, both findings were confirmed by thehistological analysis.

Jiang et al [13] showed that as in their other studythe hemoglobin concentration was also achievedusing 2 different wave sources and the tumor growthwas observed both in the ultrasound doppler andin the deceased dogs prostate analysis. Theyvecommented that the method is limited to analyzedeeper tissue and their next step is going to intro-duce morphology data of the Ultrasound to try toimprove the spatial feature of the optical images.

Kavuri et al [27] showed that their method coulddetect 2-cm deep with their used configuration,theyve also observed that they successfully recon-struct the optical properties in simulation and inthe experiment. In Simulation a recover rate of95% was achieved, while 83% was obtained in theexperimental set. Even though their high recoverrates their code couldnt correctly point out thetargets shape.

Piao et al [4] showed good results in simulationwhen having prior location information but morestudies must be run to improve the optimum wayto image the prostate with the proposed system.They have proposed that in newer developmentssegmentation techniques could be used to improvetheir results.

Xu et al [23] the reconstructed images had sim-ilar values to the original values of the simulatedprostate, and theyve evaluated that by the methodused with the hierarchical reconstruction algorithmshowed itself as reliable, after that a number of arraydesigns is proposed and evaluated but only the PIaoet ao 2008 design was used.

IV. DISCUSSION

Making a general review of the papers cited inthe results sections we can get some similarities

most of them commented that their code neededto be improved, and all of them used at least onepart processed by a computer,what thats how wecan observe the significance of better algorithmsfor the techniques presented. Other thing in com-mon between the papers reviewed above, none ofthe DOT and TRUS+DOT made in-vivo tests withreal patients, its considerable that these methodsare is still in development as said by Bernhart etal [10],but the TRUS analysis had also a lot ofsimulation in the studies.And in-vivo measurementsin humans should be highly considerate, since thateven most of methods presented good accuracy andspecificity decay when using prostate phantoms ,and considering that the real prostate has severalheterogeneities [12] the tendency of specificity andaccuracy tends to decay even more.Other issue thatI would like to point out that each paper gives adifferent measurement way to evaluate and validatetheir methods, and in some cases they only give thequalitative result, but this must be involved to thisnovel techniques that has no standard for presentingits accuracy on detecting PCa.Further I will pointout some characteristics of the 3 imaging techniques.

iDOT has a bright future on helping to optimizePDT treatments of prostate cancer, however thespeed of the reconstruction image is still no goodranging from 30-58 min, the spatial resolutionis a problem of optical imaging modalities, andhere is no different with iDOT.A great ally foriDOT could be fluorescent markers, although cau-tion should be taken because the fluorescence canlead to a confusion between the marked cancer withbleeding areas [12] .A better algorithm could help,on spatial resolution, code time and optimal imagingfor fluorescent regions.

TRUS showed that for detecting PCa two meth-ods were proposed, ultrasound Doppler that showedgood results to find PCa, the second one is touse hierarchical algorithms to stand out the regionthe interest,or Neural Networks, both showed toimproved significantly the accuracy to look for PCain TRUS images.

TRUS+iDOT showed that they can potentially de-tect PCa earlier than conventional TRUS techniques, however Not enough large N in the experimentswere made to believe that this technique reallyimproves the sensitivity of the sensor. But one thingmust be observed in future studies whether the


practitioners preferred to look for the optical imagestogether with TRUS ones or if they want to usedmerged images. Another important point that mustbe analyzed is that even with limited size probes[5] more configurations of source detector mustbe studied to look for which configuration givesbetter results. One thing that havent been doneyet is to look if there is a wavelength just to beabsorbed/scattered by the tumors.

V. CONCLUSIONThis Review gives an idea of what is being

done to improve prostate cancer diagnostics, and itseems that efforts with computer algorithms are theones that are giving better accuracy and specificityto look for PCa, through Neural Networks andHierarchical algorithms in the TRUS images.

Regarding the iDOT and the TRUS+DOT, bothneed improvements in their algorithms in order toachieve better resolution and processing time, fea-tures like fluorescence can help both as well.Therewere two in-vivo experiments with dogs with in-duced PCa that had its early stages detected byoptical images.It will be important to keep inves-tigating the possibility of early detection of cancerin early stages, because in early stages cancer thereis a higher possibility of survival.

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APPENDIX ANIRFAST BLOCK DIAGRAMS

Fig. 6. Block Diagram to summarize to summarize how NIRFASTwork for reconstruction(Dehgani 2008)

..


Fig. 7. Block Diagram to summarize how NIRFAST work for theforward method(Dehgani 2008)

review on dot and trus to detect prostate cancer

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