Multi-parametric (mp) MRI of prostatic ductal adenocarcinoma

Interpreting Prostate Multiparametric MRI: Beyond Adenocarcinoma - Anatomical Variations, Mimickers, and Post-Intervention Changes

Prostate magnetic resonance imaging (MRI) is an essential tool in the diagnostic pathway for prostate cancer. However, its accuracy can be confounded by a spectrum of noncancerous entities with similar radiological features, posing a challenge for definitive diagnosis. This review synthesizes current knowledge on the MRI phenotypes of both common and rare benign prostate conditions that may be mistaken for malignancy. The narrative encompasses anatomical variants, other neoplastic processes, inflammatory conditions, and alterations secondary to medical interventions. Furthermore, this review underscores the critical role of MRI quality in diagnostic accuracy and explores the emerging contributions of artificial intelligence in enhancing image interpretation.

68Ga-PSMA PET/CT and 18F-FDG PET/CT in the diagnosis of prostatic ductal cancer

PURPOSES

To explore the characteristics of PSMA PET/CT and FDG PET/CT images in prostatic ductal adenocarcinoma (DA) patients.

METHODS

We retrospectively enrolled prostatic DA patients with PET/CT scans at Tongji Hospital from 2018 to 2022. Patients with prostatic acinar adenocarcinoma (AA) and benign pathology (BP) were enrolled by 1:1 matching. Differences in the uptake of primary and metastatic foci on PET among the groups were analyzed.

RESULTS

A total of 42 patients were enrolled: 14 in each group. In primary foci, the mean PSMA uptake in the DA group was lower than that in the AA group (14.2 ± 9.6 vs. 27.1 ± 14.3, P = 0.009) and greater than that in the BP group (14.2 ± 9.6 vs. 4.7 ± 1.3, P = 0.003). The AUCs of the DA-AA ROC curve and DA-BP ROC curve were 0.781 and 0.872, respectively. The median PSMA uptake of metastatic lymph nodes in the DA group was lower than that in the AA group (5.6 vs. 14.2, P = 0.033), with no significant difference in metastatic bone lesions (9.5 vs 19.1, P = 0.485). No significant difference was found in the FDG uptake of primary and metastatic foci between the DA and AA groups (P > 0.05).

CONCLUSION

Prostatic DA has greater PSMA uptake than BP diseases, but lower uptake in both primary foci and metastatic lymph nodes than AA on PSMA PET/CT, aiding in the differential diagnosis of DA, AA and BP diseases. Clinicians should combine traditional imaging with PSMA PET/CT to avoid underestimating the clinical stage of DA patients.

Pure ductal adenocarcinoma of the prostate protruding into the prostatic urethra: A case report of MRI findings and literature review

Ductal adenocarcinoma of the prostate (DCa) is the histological variant of prostatic carcinoma. The macroscopic finding of DCa arising from primary duct by urethroscopy is papillary excrescences in the prostatic urethra. But the finding of MRI remains poorly understood, since there is no coherent report on the MRI finding of DCa arising from primary duct. We herein report a case of DCa arising from primary duct and forming papillary excrescences in the prostatic urethra. The patient was a male in his 70s and presented with gross hematuria a few days ago. Blood test showed elevated prostate specific antigen (PSA). Prostate MRI was performed. There were two lesions in the prostatic urethra and the right transition zone (TZ). On T₂-weighted image (T2WI), the lesion in the prostatic urethra was identifiable, but the lesion in the right TZ was difficult to identify. On diffusion-weighted image (DWI), both lesions showed hyperintense signal and could be identified, and there was continuity between them. Urethroscopy was performed, there was the lesion with papillary excrescences developing from the right dorsal side of prostatic urethra. Transurethral resection of the prostate was performed. The pathological diagnosis was DCa (pure type). A review of previous literature showed that DCa had a slightly hypointense signal on T2WI. It may be difficult to identify DCa in the TZ because DCa and the TZ show similar signals on T2WI. DWI may be useful to accurately assess DCa arising from primary duct.

Magnetic resonance imaging findings of pure prostatic ductal adenocarcinomas: a case series

PURPOSE

This study aimed to investigate the characteristics of magnetic resonance imaging (MRI) findings in pure prostatic ductal adenocarcinoma.

METHODS

From January 2009 to February 2020, seven patients who were diagnosed with pure prostatic ductal adenocarcinoma and had a referable preoperative MRI scan were included in the study. We evaluated the following MRI findings for each tumor: size, location, presence of multi-cystic component, and apparent diffusion coefficient (ADC) value.

RESULTS

The median maximum diameter of the tumors was 22 mm (range 19-70 mm). Regarding transverse distribution, five tumors were located in the periurethral area and two were located peripherally apart from the urethra. Two of the seven tumors had cystic components. The median ADC value of the tumors was 0.754 × 10^-3 mm²/s (range 0.570-0.963 × 10^-3 mm²/s). Based on the transverse distribution and components of the tumors on MRI, ductal adenocarcinomas were classified into three types: type I as a non-cystic tumor located peripherally apart from the urethra (29%, two cases); type II as a non-cystic tumor located in the periurethral area (43%, three cases); and type III as a tumor with a multi-cystic component (29%, two cases).

CONCLUSION

The non-cystic mass with periurethral distribution (type II) and multi-cystic mass (type III) may be characteristic features that differentiate pure ductal adenocarcinoma from ordinary acinar adenocarcinoma on MRI.

Defining Diagnostic Criteria for Prostatic Ductal Adenocarcinoma at Multiparametric MRI

Background Prostatic ductal adenocarcinoma (DAC) is an aggressive histologic variant of prostate cancer that often warrants multimodal therapy and poses a significant diagnostic challenge clinically and at imaging. Purpose To develop multiparametric MRI criteria to define DAC and to assess their diagnostic performance in differentiating DAC from prostatic acinar adenocarcinoma (PAC). Materials and Methods Men with histologically proven DAC who had multiparametric MRI before radical prostatectomy were retrospectively identified from January 2011 through November 2018. MRI features were predefined using a subset of nine DACs and then compared for men with peripheral-zone DACs 1 cm or greater in size and men with matched biopsy-confirmed International Society of Urological Pathology grade group 4-5 PAC, by four independent radiologists blinded to the pathologic diagnosis. Diagnostic performance was determined by consensus read. Patient and tumor characteristics were compared by using the Fisher test, t-tests, and Mann-Whitney U test. Agreement (Cohen κ) and sensitivity analyses were also performed. Results There were 59 men with DAC (median age, 63 years [interquartile range, 56, 67 years]) and 59 men with PAC (median age, 64 years [interquartile range, 59, 69 years]). Predefined MRI features, including intermediate T2 signal, well-defined margin, lobulation, and hypointense rim, were detected in a higher proportion of DACs than PACs (76% [45 of 59] vs 5% [three of 59]; P < .001). On consensus reading, the presence of three or more features demonstrated 76% sensitivity, 94% specificity, 94% positive predictive value [PPV], and 80% negative predictive value [NPV] for all DACs and 100% sensitivity, 95% specificity, 81% PPV, and 100% NPV for pure DACs. The DACs and PACs showed no difference in contrast enhancement (100% vs 100%; P >.99, median T2 signal intensity (254 vs 230; P = .99), or apparent diffusion coefficient (median, 677 10^-6 mm²/sec vs 685 10^-6 mm²/sec; P = .73). Conclusion The presence of intermediate T2 signal, well-defined margin, lobulation, and/or hypointense rim, together with restricted diffusion and contrast enhancement at multiparametric MRI of the prostate, suggests prostatic ductal adenocarcinoma rather than prostatic acinar adenocarcinoma. © RSNA, 2022 Online supplemental material is available for this article.

Differential diagnosis of uncommon prostate diseases: combining mpMRI and clinical information

The differential diagnosis of abnormalities in the prostate is broad, covering common (acinar adenocarcinoma, benign prostatic hyperplasia, chronic prostatitis, hemorrhage, cysts, calcifications, atrophy and fibrosis) and less common conditions (tumors other than acinar adenocarcinoma, granulomatous prostatitis containing tuberculosis, abscesses and other conditions, and idiopathic disorders such as amyloidosis and exophytic benign prostatic hyperplasia). Recent advances in magnetic resonance imaging (MRI) of the prostate gland and imaging guidelines, such as the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1), have dramatically improved the ability to distinguish common abnormalities, especially the ability to detect clinically significant prostate cancer (csPCa). Overlap can exist in the clinical history and imaging features associated with various common/uncommon prostate abnormalities, and biopsy is often required but is invasive. Prostate abnormalities can be divided into two categories: category 1, diseases for which PI-RADS scores are suitable for use, and category 2, diseases for which PI-RADS scores are unsuitable for use. Radiologists must have an intimate knowledge of other diseases, especially uncommon conditions. Past relevant history, symptoms, age, serum prostate-specific antigen (PSA) levels, MRI manifestations, and the applicability of the PI-RADS assessment should be considered when diagnosing prostate abnormalities.

The visibility of prostate cancer concerning underlying histopathological variances: A single-center multiparametric magnetic resonance imaging study

PURPOSE

To investigate whether prostate cancer (PCa) lesions regarding histopathological composition exhibit different morphological features on multiparametric prostate MRI (mpMRI).

METHODS

We investigated men with PCa with available mpMRI and whole-mount specimens between June 2015 to December 2020.The acquisition protocol consistent with the Prostate Imaging Reporting and Data System (PI-RADS). Two observers evaluated the images following the PI-RADS v2.1. guideline before biopsy and radical prostatectomy. The discrepancies were resolved in a joint meeting. A genitourinary pathologist reviewed the whole-digitalized mount specimens, and the lesions with Gleason score of 7 and above (3 + 4 and above), and/or cancers with a maximum diameter of 6 mm and more, and/or extraprostatic extension were accepted as clinically significant PCa. The PI-RADS scores and the diameter of the clinically significant PCa on mpMRI concerning histopathological components (i.e., cribriform component, intraductal pattern, or without cribriform component or intraductal pattern) were investigated. The clinically significant PCa foci with PI-RADS score <3 was accepted as an invisible lesion on mpMRI.

RESULTS

In all, 58 men with a total of 112 clinically significant PCa foci, were enrolled in the study. The intraductal pattern, cribriform pattern, or none of these patterns were observed in 28/112 (25 %), 43/112 (38.05 %), and 41/112 (36.60 %) tumor foci. Six out of 28 (21.42 %), 17/43 (39.53 %), and 18/41 (42.8 %) foci with an intraductal pattern, cribriform component, or without any of them, respectively, were invisible on mpMRI (P = 0.111).

CONCLUSION

Though it was not reached a statistical significance, clinically significant PCa with the cribriform component and without any intraductal or cribriform component are more likely to manifests mpMRI invisible foci than the intraductal pattern. Further multi-center studies are warranted to precisely elucidate mpMRI features of PCa regarding histopathological composition.

Optimizing the diagnosis and management of ductal prostate cancer

Ductal adenocarcinoma (DAC) is the most common variant histological subtype of prostate carcinoma and has an aggressive clinical course. DAC is usually characterized and treated as high-risk prostatic acinar adenocarcinoma (PAC). However, DAC has a different biology to that of acinar disease, which often poses a challenge for both diagnosis and management. DAC can be difficult to identify using conventional diagnostic modalities such as serum PSA levels and multiparametric MRI, and the optimal management for localized DAC is unknown owing to the rarity of the disease. Following definitive therapy for localized disease with radical prostatectomy or radiotherapy, the majority of DACs recur with visceral metastases at low PSA levels. Various systemic therapies that have been shown to be effective in high-risk PAC have limited use in treating DAC. Although current understanding of the biology of DAC is limited, genomic analyses have provided insights into the pathology behind its aggressive behaviour and potential future therapeutic targets.

Value of MRI texture analysis for predicting high-grade prostate cancer

PURPOSE

To explore the potential value of MRI texture analysis (TA) combined with prostate-related biomarkers to predict high-grade prostate cancer (HGPCa).

MATERIALS AND METHODS

Eighty-five patients who underwent MRI scanning, including T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) prior to trans-rectal ultrasound (TRUS)-guided core prostate biopsy, were retrospectively enrolled. TA parameters derived from T2WI and DWI, prostate-specific antigen (PSA), and free PSA (fPSA) were compared between the HGPCa and non-high-grade prostate cancer (NHGPCa) groups using independent Student's t-test and the Mann-Whitney U test. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the predictive value for HGPCa.

RESULTS

Univariate analysis showed that PSA and entropy based on apparent diffusion coefficient (ADC) map differed significantly between the HGPCa and NHGPCa groups and showed higher diagnostic values for HGPCa (area under the curve (AUC) = 82.0% and 80.0%, respectively). Logistic regression and ROC curve analyses revealed that kurtosis, skewness and entropy derived from ADC maps had diagnostic power to predict HGPCa; when the three texture parameters were combined, the area under the ROC curve reached the maximum (AUC = 84.6%; 95% confidence interval (CI): 0.758, 0.935; P = 0.000).

CONCLUSION

TA parameters derived from ADC may be a valuable tool in predicting HGPCa. The combination of specific textural parameters extracted from ADC map may be additional tools to predict HGPCa.

Conspicuity of prostate cancer on multiparametric magnetic resonance imaging: A cross-disciplinary translational hypothesis

Pre-biopsy multiparametric magnetic resonance imaging (mpMRI) has transformed the risk stratification and diagnostic approach for suspected prostate cancer. The majority of clinically significant prostate cancers are visible on pre-biopsy mpMRI, however, there are a subset of significant tumors that are not detected by mpMRI. The radiobiological mechanisms underpinning mpMRI-visibility and invisibility of these cancers remain uncertain. Emerging evidence suggests that mpMRI-visible tumors are enriched with molecular features associated with increased disease aggressivity and poor clinical prognosis, which is supported by short-term endpoints, such as biochemical recurrence following surgery. Furthermore, at the histopathological level, mpMRI-visible tumors appear to exhibit increased architectural and vascular density compared to mpMRI-invisible disease. It seems probable that the genomic, pathological, radiological, and clinical features of mpMRI-visible and mpMRI-invisible prostate cancers are interrelated. Here, we propose a novel cross-disciplinary theory that links genomic and molecular evidence with cellular and histopathological appearances, elucidating both the mpMRI visibility and clinical status of significant prostate cancer.

Quantitative Prostate MRI

Prostate MRI is reported in clinical practice using the Prostate Imaging and Data Reporting System (PI-RADS). PI-RADS aims to standardize, as much as possible, the acquisition, interpretation, reporting, and ultimately the performance of prostate MRI. PI-RADS relies upon mainly subjective analysis of MR imaging findings, with very few incorporated quantitative features. The shortcomings of PI-RADS are mainly: low-to-moderate interobserver agreement and modest accuracy for detection of clinically significant tumors in the transition zone. The use of a more quantitative analysis of prostate MR imaging findings is therefore of interest. Quantitative MR imaging features including: tumor size and volume, tumor length of capsular contact, tumor apparent diffusion coefficient (ADC) metrics, tumor T₁ and T₂ relaxation times, tumor shape, and texture analyses have all shown value for improving characterization of observations detected on prostate MRI and for differentiating between tumors by their pathological grade and stage. Quantitative analysis may therefore improve diagnostic accuracy for detection of cancer and could be a noninvasive means to predict patient prognosis and guide management. Since quantitative analysis of prostate MRI is less dependent on an individual users' assessment, it could also improve interobserver agreement. Semi- and fully automated analysis of quantitative (radiomic) MRI features using artificial neural networks represent the next step in quantitative prostate MRI and are now being actively studied. Validation, through high-quality multicenter studies assessing diagnostic accuracy for clinically significant prostate cancer detection, in the domain of quantitative prostate MRI is needed. This article reviews advances in quantitative prostate MRI, highlighting the strengths and limitations of existing and emerging techniques, as well as discussing opportunities and challenges for evaluation of prostate MRI in clinical practice when using quantitative assessment. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

Effect of observation size and apparent diffusion coefficient (ADC) value in PI-RADS v2.1 assessment category 4 and 5 observations compared to adverse pathological outcomes

OBJECTIVE

To compare observation size and apparent diffusion coefficient (ADC) values in Prostate Imaging Reporting and Data System (PI-RADS) v2.1 category 4 and 5 observations to adverse pathological features.

MATERIALS AND METHODS

With institutional review board approval, 267 consecutive men with 3-T MRI before radical prostatectomy (RP) between 2012 and 2018 were evaluated by two blinded radiologists who assigned PI-RADS v2.1 scores. Discrepancies were resolved by consensus. A third blinded radiologist measured observation size and ADC (ADC.mean, ADC.min [lowest ADC within an observation], ADC.ratio [ADC.mean/ADC.peripheral zone {PZ}]). Size and ADC were compared to pathological stage and Gleason score (GS) using t tests, ANOVA, Pearson correlation, and receiver operating characteristic (ROC) analysis.

RESULTS

Consensus review identified 267 true positive category 4 and 5 observations representing 83.1% (222/267) PZ and 16.9% (45/267) transition zone (TZ) tumors. Inter-observer agreement for PI-RADS v2.1 scoring was moderate (K = 0.45). Size was associated with extra-prostatic extension (EPE) (19 ± 8 versus 14 ± 6 mm, p < 0.001) and seminal vesicle invasion (SVI) (24 ± 9 versus 16 ± 7 mm, p < 0.001). Size ≥ 15 mm optimized the accuracy for EPE with area under the ROC curve (AUC) and sensitivity/specificity of 0.68 (CI 0.62-0.75) and 63.2%/65.6%. Size ≥ 19 mm optimized the accuracy for SVI with AUC/sensitivity/specificity of 0.75 (CI 0.66-0.83)/69.4%/70.6%. ADC metrics were not associated with pathological stage. Larger observation size (p = 0.032), lower ADC.min (p = 0.010), and lower ADC.ratio (p = 0.010) were associated with higher GS. Size correlated better to higher Gleason scores (p = 0.002) compared to ADC metrics (p = 0.09-0.11).

CONCLUSION

Among PI-RADS v2.1 category 4 and 5 observations, size was associated with higher pathological stage whereas ADC metrics were not. Size, ADC.minimum, and ADC.ratio differed in tumors stratified by Gleason score.

KEY POINTS

• Among PI-RADS category 4 and 5 observations, size but not ADC can differentiate between tumors by pathological stage. • An observation size threshold of 15 mm and 19 mm optimized the accuracy for diagnosis of extra-prostatic extension and seminal vesicle invasion. • Among PI-RADS category 4 and 5 observations, size, ADC.minimum, and ADC.ratio differed comparing tumors by Gleason score.

Comparison of Prostate Imaging Reporting and Data System versions 1 and 2 for the Detection of Peripheral Zone Gleason Score 3 + 4 = 7 Cancers

OBJECTIVE

The objective of our study was to compare Prostate Imaging Reporting and Data System version 1 (PI-RADSv1) and Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) for the detection of peripheral zone (PZ) Gleason score 3 + 4 = 7 cancers.

MATERIALS AND METHODS

Forty-seven consecutive patients with 52 PZ Gleason score 3 + 4 = 7 cancers that were 0.5 cm³ or larger underwent radical prostatectomy (RP) and 3-T MRI between 2012 and 2015. Two blinded radiologists (readers 1 and 2) retrospectively assigned PI-RADSv1 sequence (T2-weighted imaging, DWI, dynamic contrast-enhanced MRI [DCE-MRI]) and sum scores and PI-RADSv2 assessment categories. A third blinded radiologist (reader 3) measured apparent diffusion coefficient (ADC) ratio (ADC of tumor / ADC of normal PZ) using RP-MRI maps. Sensitivity, false-positive rate, and overall accuracy were compared using McNemar test. Pearson correlation was performed.

RESULTS

Using PI-RADSv1, reader 1 detected 86.5% (45/52) of the cancers and reader 2, 76.9% (40/52) of the cancers. Using PI-RADSv2, reader 1 detected 78.9% (41/52) and reader 2, 67.3% (35/52). Reader 1 detected 7.7% (4/52) and reader 2 detected 9.6% (5/52) more tumors using PI-RADSv1 due to T2-weighted imaging score ≥ 4 or DCE-MRI score ≥ 3. Sensitivity was higher for PI-RADSv1 (p = 0.01 and 0.03, readers 1 and 2). False-positive rates were higher with PI-RADSv1 than with PI-RADSv2 (1.8% vs 0.9% for reader 1; 3.6% vs 1.8% for reader 2) without significant differences in false-positive rate (p = 0.41 and 0.25) or overall accuracy (p = 0.06 and 0.23). PI-RADSv1 sum scores correlated strongly with PI-RADSv2 categories (B = 0.78-0.93, p < 0.0001). The mean ADC ratio was 0.61 ± 0.14 mm²/s with no difference between visible and nonvisible tumors (p = 0.06-0.5). Interobserver agreement was moderate for PI-RADSv2 (κ = 0.41) and ranged from slight to substantial for PI-RADSv1 (T2-weighted imaging, κ = 0.32; DWI, κ = 0.52; DCE-MRI, κ = 0.13).

CONCLUSION

There was no difference in overall detection of cancers comparing PI-RADSv1 and PI-RADSv2; however, PI-RADSv1 sequence scores on T2-weighted imaging and DCE-MRI detected approximately 10% more tumors that were otherwise underestimated on DWI and using PI-RADSv2 decision-tree rules.

"Textural analysis of multiparametric MRI detects transition zone prostate cancer"

OBJECTIVES

To evaluate multiparametric-MRI (mpMRI) derived histogram textural-analysis parameters for detection of transition zone (TZ) prostatic tumour.

METHODS

Sixty-seven consecutive men with suspected prostate cancer underwent 1.5T mpMRI prior to template-mapping-biopsy (TPM). Twenty-six men had 'significant' TZ tumour. Two radiologists in consensus matched TPM to the single axial slice best depicting tumour, or largest TZ diameter for those with benign histology, to define single-slice whole TZ-regions-of-interest (ROIs). Textural-parameter differences between single-slice whole TZ-ROI containing significant tumour versus benign/insignificant tumour were analysed using Mann Whitney U test. Diagnostic accuracy was assessed by receiver operating characteristic area under curve (ROC-AUC) analysis cross-validated with leave-one-out (LOO) analysis.

RESULTS

ADC kurtosis was significantly lower (p < 0.001) in TZ containing significant tumour with ROC-AUC 0.80 (LOO-AUC 0.78); the difference became non-significant following exclusion of significant tumour from single-slice whole TZ-ROI (p = 0.23). T1-entropy was significantly lower (p = 0.004) in TZ containing significant tumour with ROC-AUC 0.70 (LOO-AUC 0.66) and was unaffected by excluding significant tumour from TZ-ROI (p = 0.004). Combining these parameters yielded ROC-AUC 0.86 (LOO-AUC 0.83).

CONCLUSION

Textural features of the whole prostate TZ can discriminate significant prostatic cancer through reduced kurtosis of the ADC-histogram where significant tumour is included in TZ-ROI and reduced T1 entropy independent of tumour inclusion.

KEY POINTS

• MR textural features of prostate transition zone may discriminate significant prostatic cancer. • Transition zone (TZ) containing significant tumour demonstrates a less peaked ADC histogram. • TZ containing significant tumour reveals higher post-contrast T1-weighted homogeneity. • The utility of MR texture analysis in prostate cancer merits further investigation.

Prostatic intraepithelial neoplasia-like ductal prostatic adenocarcinoma: A case suitable for active surveillance?

In contrast to typical prostatic ductal adenocarcinoma, prostatic intraepithelial neoplasia (PIN)-like ductal adenocarcinoma is a rare variant of prostate cancer with low-grade clinical behavior. We report a case of a 66-year-old African-American male with an elevated serum prostate-specific antigen who underwent multiparametric prostate magnetic resonance imaging (MRI) and MRI/ultrasound fusion-guided biopsies. Pathology demonstrated low-volume Gleason score 3 + 3 = 6 (Grade Group 1), acinar adenocarcinoma involving one core and PIN-like ductal adenocarcinoma on a separate core. Herein, we discuss the potential role of active surveillance for patients with this rare variant of prostate cancer found in the era of advanced imaging with multiparametric MRI for prostate cancer.

Whole-Tumor Quantitative Apparent Diffusion Coefficient Histogram and Texture Analysis to Predict Gleason Score Upgrading in Intermediate-Risk 3 + 4 = 7 Prostate Cancer

OBJECTIVE

The objective of our study was to evaluate whole-lesion quantitative apparent diffusion coefficient (ADC) for the prediction of Gleason score (GS) upgrading in 3 + 4 = 7 prostate cancer.

MATERIALS AND METHODS

Fifty-four patients with GS 3 + 4 = 7 prostate cancer diagnosed at systematic transrectal ultrasound (TRUS)-guided biopsy underwent 3-T MRI and radical prostatectomy (RP) between 2012 and 2014. A blinded radiologist contoured dominant tumors on ADC maps using histopathologic correlation. The whole-lesion mean ADC, ADC ratio (normalized to peripheral zone), ADC histogram, and texture analysis were compared between tumors with GS upgrading and those without GS upgrading using multivariate ROC analyses and logistic regression modeling.

RESULTS

Tumors were upgraded to GS 4 + 3 = 7 after RP in 26% (n = 14) of the 54 patients, and tumors were downgraded after RP in none of the patients. The mean ADC, ADC ratio, 10th-centile ADC, 25th-centile ADC, and 50th-centile ADC were similar between patients with GS 3 + 4 = 7 tumors (0.99 ± 0.22, 0.58 ± 0.15, 0.77 ± 0.31, 0.94 ± 0.28, and 1.15 ± 0.24, respectively) and patients with upgraded GS 4 + 3 = 7 tumors (1.02 ± 0.18, 0.55 ± 0.11, 0.71 ± 0.26, 0.89 ± 0.20, and 1.11 ± 0.16) (p > 0.05). Regression models combining texture features improved the prediction of GS upgrading. The combination of kurtosis, entropy, and skewness yielded an AUC of 0.76 (SE = 0.07) (p < 0.001), a sensitivity of 71%, and a specificity of 73%. The combination of kurtosis, heterogeneity, entropy, and skewness yielded an AUC of 0.77 (SE = 0.07) (p < 0.001), a sensitivity of 71%, and a specificity of 78%.

CONCLUSION

In this study, whole-lesion mean ADC, ADC ratio, and ADC histogram analysis were not predictive of pathologic upgrading of GS 3 + 4 = 7 prostate cancer after RP. ADC texture analysis improved accuracy.

Prostatic ductal adenocarcinoma: An aggressive variant that is underdiagnosed and undersampled on transrectal ultrasound (TRUS)-guided needle biopsy

INTRODUCTION

We sought to determine if prostatic ductal adenocarcinoma is undersampled and/or underdiagnosed at transrectal ultrasound (TRUS)-guided biopsy.

METHODS

With institutional review board approval, we searched our pathology database between 2008 and 2014 for patients with a diagnosis of ≥10% ductal adenocarcinoma on radical prostatectomy and available TRUS-guided needle biopsy specimens. Three blinded genitourinary pathologists independently examined the biopsy slides. The presence or absence of ductal adenocarcinoma was determined. Diagnostic accuracy was calculated using consensus diagnosis as the reference standard. Inter-observer agreement was assessed using Cohen's kappa coefficient.

RESULTS

Based on consensus review, 66.7% (12/18) biopsy specimens demonstrated ductal adenocarcinoma and 33.3% (6/18) demonstrated conventional acinar prostatic adenocarcinoma. The sensitivity/specificity for each reader (R) was: 83/100% (R1), 100/83% (R2) and 58/83% (R3) and the inter-observer agreement was only fair (K=0.32). Only two of the original needle-biopsy reports correctly identified ductal adenocarcinoma (sensitivity = 17%). The main limitations of the study are the relatively small sample size and the potential for selection bias since we could only examine patients who underwent radical prostatectomy.

CONCLUSIONS

Prostatic ductal adenocarcinoma may be undersampled at TRUS-guided biopsy and in this study was under-reported in routine clinical practice. This highlights the importance of increased awareness of ductal adeoncarcinoma and the need for clear diagnostic criteria. These findings have significant clinical impact especially when determining candidacy for active surveillance protocols.

Emerging Role of MRI for Radiation Treatment Planning in Lung Cancer

Magnetic resonance imaging (MRI) provides excellent soft-tissue contrast and allows for specific scanning sequences to optimize differentiation between various tissue types and properties. Moreover, it offers the potential for real-time motion imaging. This makes magnetic resonance imaging an ideal candidate imaging modality for radiation treatment planning in lung cancer. Although the number of clinical research protocols for the application of magnetic resonance imaging for lung cancer treatment is increasing (www.clinicaltrials.gov) and the magnetic resonance imaging sequences are becoming faster, there are still some technical challenges. This review describes the opportunities and challenges of magnetic resonance imaging for radiation treatment planning in lung cancer.

False positive and false negative diagnoses of prostate cancer at multi-parametric prostate MRI in active surveillance

Abstract

MP-MRI is a critical component in active surveillance (AS) of prostate cancer (PCa) because of a high negative predictive value for clinically significant tumours. This review illustrates pitfalls of MP-MRI and how to recognise and avoid them. The anterior fibromuscular stroma and central zone are low signal on T2W-MRI/apparent diffusion coefficient (ADC), resembling PCa. Location, progressive enhancement and low signal on b ≥1000 mm²/s echo-planar images (EPI) are differentiating features. BPH can mimic PCa. Glandular BPH shows increased T2W/ADC signal, cystic change and progressive enhancement; however, stromal BPH resembles transition zone (TZ) PCa. A rounded morphology, low T2 signal capsule and posterior/superior location favour stromal BPH. Acute/chronic prostatitis mimics PCa at MP-MRI, with differentiation mainly on clinical grounds. Visual analysis of diffusion-weighted MRI must include EPI and appropriate windowing of ADC. Quantitative ADC analysis is limited by lack of standardization; the ADC ratio and ADC histogram analysis are alternatives to mean values. DCE lacks standardisation and has limited utility in the TZ, where T2W/DWI are favoured. Targeted TRUS-guided biopsies of MR-detected lesions are challenging. Lesions detected on MP-MRI may not be perfectly targeted with TRUS and this must be considered when faced with a suspicious lesion on MP-MRI and a negative targeted TRUS biopsy histopathological result.

Keypoints

• Multi-parametric MRI plays a critical role in prostate cancer active surveillance.

• Low T2W signal intensity structures appear dark on ADC, potentially simulating cancer.

• Stromal BPH mimics cancer at DWI and DCE.

• Long b value trace EPI should be reviewed

• Targeted biopsy of MR-detected lesions using TRUS guidance may be challenging.

Haralick texture analysis of prostate MRI: utility for differentiating non-cancerous prostate from prostate cancer and differentiating prostate cancers with different Gleason scores

OBJECTIVES

To investigate Haralick texture analysis of prostate MRI for cancer detection and differentiating Gleason scores (GS).

METHODS

One hundred and forty-seven patients underwent T2- weighted (T2WI) and diffusion-weighted prostate MRI. Cancers ≥0.5 ml and non-cancerous peripheral (PZ) and transition (TZ) zone tissue were identified on T2WI and apparent diffusion coefficient (ADC) maps, using whole-mount pathology as reference. Texture features (Energy, Entropy, Correlation, Homogeneity, Inertia) were extracted and analysed using generalized estimating equations.

RESULTS

PZ cancers (n = 143) showed higher Entropy and Inertia and lower Energy, Correlation and Homogeneity compared to non-cancerous tissue on T2WI and ADC maps (p-values: <.0001-0.008). In TZ cancers (n = 43) we observed significant differences for all five texture features on the ADC map (all p-values: <.0001) and for Correlation (p = 0.041) and Inertia (p = 0.001) on T2WI. On ADC maps, GS was associated with higher Entropy (GS 6 vs. 7: p = 0.0225; 6 vs. >7: p = 0.0069) and lower Energy (GS 6 vs. 7: p = 0.0116, 6 vs. >7: p = 0.0039). ADC map Energy (p = 0.0102) and Entropy (p = 0.0019) were significantly different in GS ≤3 + 4 versus ≥4 + 3 cancers; ADC map Entropy remained significant after controlling for the median ADC (p = 0.0291).

CONCLUSION

Several Haralick-based texture features appear useful for prostate cancer detection and GS assessment.

KEY POINTS

• Several Haralick texture features may differentiate non-cancerous and cancerous prostate tissue. • Tumour Energy and Entropy on ADC maps correlate with Gleason score. • T2w-image-derived texture features are not associated with the Gleason score.