CT colonography: computer-assisted detection of colorectal cancer

Signaling pathways involved in colorectal cancer: pathogenesis and targeted therapy

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Its complexity is influenced by various signal transduction networks that govern cellular proliferation, survival, differentiation, and apoptosis. The pathogenesis of CRC is a testament to the dysregulation of these signaling cascades, which culminates in the malignant transformation of colonic epithelium. This review aims to dissect the foundational signaling mechanisms implicated in CRC, to elucidate the generalized principles underpinning neoplastic evolution and progression. We discuss the molecular hallmarks of CRC, including the genomic, epigenomic and microbial features of CRC to highlight the role of signal transduction in the orchestration of the tumorigenic process. Concurrently, we review the advent of targeted and immune therapies in CRC, assessing their impact on the current clinical landscape. The development of these therapies has been informed by a deepening understanding of oncogenic signaling, leading to the identification of key nodes within these networks that can be exploited pharmacologically. Furthermore, we explore the potential of integrating AI to enhance the precision of therapeutic targeting and patient stratification, emphasizing their role in personalized medicine. In summary, our review captures the dynamic interplay between aberrant signaling in CRC pathogenesis and the concerted efforts to counteract these changes through targeted therapeutic strategies, ultimately aiming to pave the way for improved prognosis and personalized treatment modalities in colorectal cancer.

Emerging methods for prostate cancer imaging: evaluating cancer structure and metabolic alterations more clearly

Imaging plays a fundamental role in all aspects of the cancer management pathway. However, conventional imaging techniques are largely reliant on morphological and size descriptors that have well-known limitations, particularly when considering targeted-therapy response monitoring. Thus, new imaging methods have been developed to characterise cancer and are now routinely implemented, such as diffusion-weighted imaging, dynamic contrast enhancement, positron emission technology (PET) and magnetic resonance spectroscopy. However, despite the improvement these techniques have enabled, limitations still remain. Novel imaging methods are now emerging, intent on further interrogating cancers. These techniques are at different stages of maturity along the biomarker pathway and aim to further evaluate the cancer microstructure (vascular, extracellular and restricted diffusion for cytometry in tumours) magnetic resonance imaging (MRI), luminal water fraction imaging] as well as the metabolic alterations associated with cancers (novel PET tracers, hyperpolarised MRI). Finally, the use of machine learning has shown powerful potential applications. By using prostate cancer as an exemplar, this Review aims to showcase these potentially potent imaging techniques and what stage we are at in their application to conventional clinical practice.

Advanced Imaging Techniques in Evaluation of Colorectal Cancer

Imaging techniques are clinical decision-making tools in the evaluation of patients with colorectal cancer (CRC). The aim of this article is to discuss the potential of recent advances in imaging for diagnosis, prognosis, therapy planning, and assessment of response to treatment of CRC. Recent developments and new clinical applications of conventional imaging techniques such as virtual colonoscopy, dual-energy spectral computed tomography, elastography, advanced computing techniques (including volumetric rendering techniques and machine learning), magnetic resonance (MR) imaging-based magnetization transfer, and new liver imaging techniques, which may offer additional clinical information in patients with CRC, are summarized. In addition, the clinical value of functional and molecular imaging techniques such as diffusion-weighted MR imaging, dynamic contrast material-enhanced imaging, blood oxygen level-dependent imaging, lymphography with contrast agents, positron emission tomography with different radiotracers, and MR spectroscopy is reviewed, and the advantages and disadvantages of these modalities are evaluated. Finally, the future role of imaging-based analysis of tumor heterogeneity and multiparametric imaging, the development of radiomics and radiogenomics, and future challenges for imaging of patients with CRC are discussed. Online supplemental material is available for this article. ^©RSNA, 2018.

A comparison of computer-assisted detection (CAD) programs for the identification of colorectal polyps: performance and sensitivity analysis, current limitations and practical tips for radiologists

AIM

To directly compare the accuracy and speed of analysis of two commercially available computer-assisted detection (CAD) programs in detecting colorectal polyps.

MATERIALS AND METHOD

In this retrospective single-centre study, patients who had colorectal polyps identified on computed tomography colonography (CTC) and subsequent lower gastrointestinal endoscopy, were analysed using two commercially available CAD programs (CAD1 and CAD2). Results were compared against endoscopy to ascertain sensitivity and positive predictive value (PPV) for colorectal polyps. Time taken for CAD analysis was also calculated.

RESULTS

CAD1 demonstrated a sensitivity of 89.8%, PPV of 17.6% and mean analysis time of 125.8 seconds. CAD2 demonstrated a sensitivity of 75.5%, PPV of 44.0% and mean analysis time of 84.6 seconds.

CONCLUSION

The sensitivity and PPV for colorectal polyps and CAD analysis times can vary widely between current commercially available CAD programs. There is still room for improvement. Generally, there is a trade-off between sensitivity and PPV, and so further developments should aim to optimise both. Information on these factors should be made routinely available, so that an informed choice on their use can be made. This information could also potentially influence the radiologist's use of CAD results.

Appearances of screen-detected versus symptomatic colorectal cancers at CT colonography

OBJECTIVES

The aim of this study was to compare the morphology, radiological stage, conspicuity, and computer-assisted detection (CAD) characteristics of colorectal cancers (CRC) detected by computed tomographic colonography (CTC) in screening and symptomatic populations.

METHODS

Two radiologists independently analyzed CTC images from 133 patients diagnosed with CRC in (a) two randomized trials of symptomatic patients (35 patients with 36 tumours) and (b) a screening program using fecal occult blood testing (FOBt; 98 patients with 100 tumours), measuring tumour length, volume, morphology, radiological stage, and subjective conspicuity. A commercial CAD package was applied to both datasets. We compared CTC characteristics between screening and symptomatic populations with multivariable regression.

RESULTS

Screen-detected CRC were significantly smaller (mean 3.0 vs 4.3 cm, p < 0.001), of lower volume (median 9.1 vs 23.2 cm3, p < 0.001) and more frequently polypoid (34/100, 34 % vs. 5/36, 13.9 %, p = 0.02) than symptomatic CRC. They were of earlier stage than symptomatic tumours (OR = 0.17, 95 %CI 0.07-0.41, p < 0.001), and were judged as significantly less conspicuous (mean conspicuity 54.1/100 vs. 72.8/100, p < 0.001). CAD detection was significantly lower for screen-detected (77.4 %; 95 %CI 67.9-84.7 %) than symptomatic CRC (96.9 %; 95 %CI 83.8-99.4 %, p = 0.02).

CONCLUSIONS

Screen-detected CRC are significantly smaller, more frequently polypoid, subjectively less conspicuous, and less likely to be identified by CAD than those in symptomatic patients.

KEY POINTS

• Screen-detected colorectal cancers (CRC) are significantly smaller than symptomatic CRC. • Screening cases are significantly less conspicuous to radiologists than symptomatic tumours. • Screen-detected CRC have different morphology compared to symptomatic tumours (more polypoid, fewer annular). • A commercial computer-aided detection (CAD) system was significantly less likely to note screen-detected CRC.

Logistic regression model for diagnosis of transition zone prostate cancer on multi-parametric MRI

OBJECTIVES

We aimed to develop logistic regression (LR) models for classifying prostate cancer within the transition zone on multi-parametric magnetic resonance imaging (mp-MRI).

METHODS

One hundred and fifty-five patients (training cohort, 70 patients; temporal validation cohort, 85 patients) underwent mp-MRI and transperineal-template-prostate-mapping (TPM) biopsy. Positive cores were classified by cancer definitions: (1) any-cancer; (2) definition-1 [≥Gleason 4 + 3 or ≥ 6 mm cancer core length (CCL)] [high risk significant]; and (3) definition-2 (≥Gleason 3 + 4 or ≥ 4 mm CCL) cancer [intermediate-high risk significant]. For each, logistic-regression mp-MRI models were derived from the training cohort and validated internally and with the temporal cohort. Sensitivity/specificity and the area under the receiver operating characteristic (ROC-AUC) curve were calculated. LR model performance was compared to radiologists' performance.

RESULTS

Twenty-eight of 70 patients from the training cohort, and 25/85 patients from the temporal validation cohort had significant cancer on TPM. The ROC-AUC of the LR model for classification of cancer was 0.73/0.67 at internal/temporal validation. The radiologist A/B ROC-AUC was 0.65/0.74 (temporal cohort). For patients scored by radiologists as Prostate Imaging Reporting and Data System (Pi-RADS) score 3, sensitivity/specificity of radiologist A 'best guess' and LR model was 0.14/0.54 and 0.71/0.61, respectively; and radiologist B 'best guess' and LR model was 0.40/0.34 and 0.50/0.76, respectively.

CONCLUSIONS

LR models can improve classification of Pi-RADS score 3 lesions similar to experienced radiologists.

KEY POINTS

• MRI helps find prostate cancer in the anterior of the gland • Logistic regression models based on mp-MRI can classify prostate cancer • Computers can help confirm cancer in areas doctors are uncertain about.

Model-based vs hybrid iterative reconstruction technique in ultralow-dose submillisievert CT colonography

OBJECTIVE

To compare image quality of different reconstruction techniques in submillisievert ultralow-dose CT colonography (CTC) and to correlate colonic findings with subsequent optical colonoscopy.

METHODS

58 patients underwent ultralow-dose CTC. The images were reconstructed with filtered back projection (FBP), hybrid iterative reconstruction (HIR) or model-based iterative reconstruction (MBIR) techniques. In each segment, endoluminal noise (expressed as standard deviation of endoluminal density) was measured and image quality was rated on a five-point Likert scale by two independent readers. Colonic lesions were evaluated in consensus and correlated with subsequent optical colonoscopy where possible.

RESULTS

The estimated radiation dose was 0.41 ± 0.05 mSv for the supine and 0.42 ± 0.04 mSv for the prone acquisitions. In the endoluminal view, the image quality was rated better in HIR, whereas better scores were obtained in MBIR in the cross-sectional view, where the endoluminal noise was the lowest (p < 0.0001). Five (26%) polyps were not identified using both computer-aided detection and endoluminal inspection in FBP images vs only one (5%) in MBIR and none in HIR images.

CONCLUSION

This study showed that in submillisievert ultralow-dose CTC, the image quality for the endoluminal view is better when HIR is used, whereas MBIR yields superior images for the cross-sectional view. The inferior quality of images reconstructed with FBP may result in decreased detection of colonic lesions.

ADVANCES IN KNOWLEDGE

Radiation dose from CTC can be safely reduced <1 mSv for both positions when iterative reconstruction is used. MBIR provides better image quality in the cross-sectional view and HIR in the endoluminal view.

Colonic distention at screening CT colonography: role of spasmolytic agents and body habitus

Sufficient colonic dilation is important when using CT colonography (CTC) for colorectal cancer screening. We investigated the effect of antispasmodic agents and the patient body habitus on the degree of colonic dilation in screening CTC.We assessed the effect of clinical characteristics [age, gender, body mass index (BMI), and the presence of diverticula] and the use of antispasmodics on colonic distention in 140 patients who underwent CTC for colorectal cancer screening. The CTC was performed in both the supine- and prone positions. Seventy patients received antispasmodics prior to CT examination and the other 70 did not. Colonic distention was scored using a 5-point scale: 1=collapsed, 2=poorly visualized, 3=visualized but underdistended, 4=acceptable, and 5=excellent. Images scored as 4 or 5 were considered to be of diagnostic quality. The mean visual evaluation score was significantly higher in the supine- than the prone position (4.2±0.5 vs. 4.0±0.5, p<0.01). For the supine position, only the use of antispasmodic was statistically associated with sufficient colonic dilation by univariate logistic analysis (odds ratio=2.365, p=0.03). For the prone position, age, BMI, and the use of antispasmodic were statistically associated with sufficient colonic dilation by multivariate analysis. The odds ratio of these parameters was 0.955 (p=0.02), 0.874 (p=0.03), and 2.391 (p=0.02), respectively.We obtained sufficient colonic dilation with an antispasmodic for CTC in both positions. Younger age and a lower BMI were also associated with better colonic dilation in the prone position.

Guideline for referral of patients with suspected colorectal cancer by family physicians and other primary care providers

OBJECTIVE

The aim of this guideline is to assist FPs and other primary care providers with recognizing features that should raise their suspicions about the presence of colorectal cancer (CRC) in their patients.

COMPOSITION OF THE COMMITTEE

Committee members were selected from among the regional primary care leads from the Cancer Care Ontario Provincial Primary Care and Cancer Network, the members of the Ontario Colorectal Cancer Screening Advisory Committee, and the members of the Cancer Care Ontario Gastrointestinal Cancer Disease Site Group.

METHODS

This guideline was developed through systematic review of the evidence base, synthesis of the evidence, and formal external review involving Canadian stakeholders to validate the relevance of recommendations.

REPORT

Evidence-based guidelines were developed to improve the management of patients presenting with clinical features of CRC within the Canadian context.

CONCLUSION

The judicious balancing of suspicion of CRC and level of risk of CRC should encourage timely referral by FPs and primary care providers. This guideline might also inform indications for referral to CRC diagnostic assessment programs.

Population screening for colorectal cancer by flexible sigmoidoscopy or CT colonography: study protocol for a multicenter randomized trial

BACKGROUND

Colorectal cancer (CRC) is the second most prevalent type of cancer in Europe. A single flexible sigmoidoscopy (FS) screening at around the age of 60 years prevents about one-third of CRC cases. However, FS screens only the distal colon, and thus mortality from proximal CRC is unaffected. Computed tomography colonography (CTC) is a highly accurate examination that allows assessment of the entire colon. However, the benefit of CTC testing as a CRC screening test is uncertain. We designed a randomized trial to compare participation rate, detection rates, and costs between CTC (with computer-aided detection) and FS as primary tests for population-based screening.

METHODS/DESIGN

An invitation letter to participate in a randomized screening trial comparing CTC versus FS will be mailed to a sample of 20,000 people aged 58 or 60 years, living in the Piedmont region and the Verona district of Italy. Individuals with a history of CRC, adenomas, inflammatory bowel disease, or recent colonoscopy, or with two first-degree relatives with CRC will be excluded from the study by their general practitioners. Individuals responding positively to the invitation letter will be then randomized to the intervention group (CTC) or control group (FS), and scheduled for the screening procedure. The primary outcome parameter of this part of the trial is the difference in advanced neoplasia detection between the two screening tests. Secondary outcomes are cost-effectiveness analysis, referral rates for colonoscopy induced by CTC versus FS, and the expected and perceived burden of the procedures. To compare participation rates for CTC versus FS, 2,000 additional eligible subjects will be randomly assigned to receive an invitation for screening with CTC or FS. In the CTC arm, non-responders will be offered fecal occult blood test (FOBT) as alternative screening test, while in the FS arm, non-responders will receive an invitation letter to undergo screening with either FOBT or CTC. Data on reasons for participation and non-participation will also be collected.

DISCUSSION

This study will provide reliable information concerning benefits and risks of the adoption of CTC as a mass screening intervention in comparison with FS. The trial will also evaluate the role of computer-aided detection in a screening setting.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT01739608.

CT colonography: preliminary assessment of a double-read paradigm that uses computer-aided detection as the first reader

PURPOSE

To compare diagnostic performance and time efficiency of double-reading first-reader computer-aided detection (CAD) (DR FR CAD) followed by radiologist interpretation with that of an unassisted read using segmentally unblinded colonoscopy as reference standard.

MATERIALS AND METHODS

The local ethical committee approved this study. Written consent to use examinations was obtained from patients. Three experienced radiologists searched for polyps 6 mm or larger in 155 computed tomographic (CT) colonographic studies (57 containing 10 masses and 79 polyps ≥ 6 mm). Reading was randomized to either unassisted read or DR FR CAD. Data sets were reread 6 weeks later by using the opposite paradigm. DR FR CAD consists of evaluation of CAD prompts, followed by fast two-dimensional review for mass detection. CAD sensitivity was calculated. Readers' diagnoses and reviewing times with and without CAD were compared by using McNemar and Student t tests, respectively. Association between missed polyps and lesion characteristics was explored with multiple regression analysis.

RESULTS

With mean rate of 19 (standard deviation, 14; median, 15; range, 4-127) false-positive results per patient, CAD sensitivity was 90% for lesions 6 mm or larger. Readers' sensitivity and specificity for lesions 6 mm or larger were 74% (95% confidence interval [CI]: 65%, 84%) and 93% (95% CI: 89%, 97%), respectively, for the unassisted read and 77% (95% CI: 67%, 85%) and 90% (95% CI: 85%, 95%), respectively, for DR FR CAD (P = .343 and P = .189, respectively). Overall unassisted and DR FR CAD reviewing times were similar (243 vs 239 seconds; P = .623); DR FR CAD was faster when the number of CAD marks per patient was 20 or fewer (187 vs 220 seconds, P <01). Odds ratio of missing a polyp with CAD decreased as polyp size increased (0.6) and for polyps visible on both prone and supine scans (0.12); it increased for flat lesions (9.1).

CONCLUSION

DR FR CAD paradigm had similar performance compared with unassisted interpretation but better time efficiency when 20 or fewer CAD prompts per patient were generated.

CAD-associated reader error in CT colonography

RATIONALE AND OBJECTIVES

Computed tomographic colonographic interpretation with computer-aided detection (CAD) may be superior to unaided viewing, although polyp characteristics may influence accuracy. Reader error due to polyp characteristics was evaluated in a multiple-case, multiple-reader trial of computed tomographic colonography with CAD.

MATERIALS AND METHODS

Two experts retrospectively reviewed 52 positive cases (74 polyps) and categorized them as hard, moderate, or easy to detect. Each case was evaluated without and with CAD. Features that may influence a reader's ability to detect a polyp or to accept or reject a CAD mark were tabulated. The association between polyp characteristics and detection rates in the trial was assessed. The difference in detection rates (CAD vs unassisted) was calculated, and regression analysis was performed.

RESULTS

Of 64 polyps found by CAD, experts categorized 20 as hard, 28 as moderate, and 16 as easy to detect. Reader characterization errors predominated (47.3%) over other errors. Factors associated with lower detection rates included small size, flat morphology, and resemblance to a thickened fold. CAD was superior for polyps resembling lipomas compared to those that did not resemble lipomas (average increase in detection rate with CAD, 12.8% vs 5.5%; P < .05).

CONCLUSIONS

Polyp characteristic may impair computed tomographic colonographic interpretation augmented by CAD. Readers can avoid errors of measurement by evaluating diminutive polyp candidates with sample measurements. Caution should be taken when evaluating focally thick folds and when using visual impression to dismiss a polyp candidate as a lipoma when it is submerged in densely tagged fluid.

Automated image-based colon cleansing for laxative-free CT colonography computer-aided polyp detection

PURPOSE

To evaluate the performance of a computer-aided detection (CAD) system for detecting colonic polyps at noncathartic computed tomography colonography (CTC) in conjunction with an automated image-based colon cleansing algorithm.

METHODS

An automated colon cleansing algorithm was designed to detect and subtract tagged-stool, accounting for heterogeneity and poor tagging, to be used in conjunction with a colon CAD system. The method is locally adaptive and combines intensity, shape, and texture analysis with probabilistic optimization. CTC data from cathartic-free bowel preparation were acquired for testing and training the parameters. Patients underwent various colonic preparations with barium or Gastroview in divided doses over 48 h before scanning. No laxatives were administered and no dietary modifications were required. Cases were selected from a polyp-enriched cohort and included scans in which at least 90% of the solid stool was visually estimated to be tagged and each colonic segment was distended in either the prone or supine view. The CAD system was run comparatively with and without the stool subtraction algorithm.

RESULTS

The dataset comprised 38 CTC scans from prone and/or supine scans of 19 patients containing 44 polyps larger than 10 mm (22 unique polyps, if matched between prone and supine scans). The results are robust on fine details around folds, thin-stool linings on the colonic wall, near polyps and in large fluid/stool pools. The sensitivity of the CAD system is 70.5% per polyp at a rate of 5.75 false positives/scan without using the stool subtraction module. This detection improved significantly (p = 0.009) after automated colon cleansing on cathartic-free data to 86.4% true positive rate at 5.75 false positives/scan.

CONCLUSIONS

An automated image-based colon cleansing algorithm designed to overcome the challenges of the noncathartic colon significantly improves the sensitivity of colon CAD by approximately 15%.