Prostate Tissue Composition and MR Measurements: Investigating the Relationships between ADC, T2,Ktrans,ve, and Corresponding Histologic Features

Langer, Deanna L.; Kwast, Theodorus H. van der; Evans, Andrew; Plotkin, Anna; Trachtenberg, John; Wilson, Brian C.; Haider, Masoom A.

doi:10.1148/radiol.10091343

Cited by 246 publications

(219 citation statements)

References 40 publications

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“…to correlate negatively with the percentage area of nuclei and the percentage area of cytoplasm on histology [25]. The range of T 2 values in the PZ was thus greater than in the TZ.…”

Section: Discussionmentioning

confidence: 81%

Relationship betweenT₂relaxation and apparent diffusion coefficient in malignant and non-malignant prostate regions and the effect of peripheral zone fractional volume

Simpkin

Morgan²,

Giles³

et al. 2013

BJR

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Objective: To establish whether T 2 relaxation and apparent diffusion coefficient (ADC) in normal prostate and tumour are related and to investigate the effects of glandular compression from an enlarged transition zone (TZ) on peripheral zone (PZ) T 2 and ADC by correlating them with the peripheral zone fractional volume (PZFV).Methods: 48 consecutive patients prospectively underwent multiecho T 2 weighted (T 2 W) (echo times 20, 40, 60, 80, 100 ms) and diffusion-weighted (b50, 100, 300, 500, 800 s mm 22 ) endorectal MRI. In 43 evaluable patients, single slice whole PZ, TZ and tumour (focal hypointense signal on T 2 W images in a biopsy-positive octant) regions of interest were transferred to T 2 and ADC maps by slice matching. T 2 and ADC values were correlated, and PZ values were correlated with PZFV.

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“…to correlate negatively with the percentage area of nuclei and the percentage area of cytoplasm on histology [25]. The range of T 2 values in the PZ was thus greater than in the TZ.…”

Section: Discussionmentioning

confidence: 81%

Relationship betweenT₂relaxation and apparent diffusion coefficient in malignant and non-malignant prostate regions and the effect of peripheral zone fractional volume

Simpkin

Morgan²,

Giles³

et al. 2013

BJR

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“…Although MRI has been shown to be a valuable tool for PCa detection (10)(11)(12)(13), there is no clear consensus on the specific imaging biomarker that is most effective in distinguishing the aggressiveness of PCa lesions. In addition to MR spectroscopic and T2-weighted (T2-w) MR imaging, the apparent diffusion coefficient (ADC) from diffusion-weighted MRI has been confirmed to be valuable for differentiating PCa aggressiveness (14)(15)(16)(17). However, studies differ in the specific ADC value used to distinguish between the cancers.…”

mentioning

confidence: 99%

“…However, studies differ in the specific ADC value used to distinguish between the cancers. The features used have included ADC mean computed from a single slice region of interest (ROI) (15,16,18), ADC mean computed from the entire volume using different sets of diffusion b-values (all vs. fast vs. slow) (19), 10th percentile of the ADC computed from the entire lesion (20), 10th percentile and ADC mean (21), and ADC mean computed over the entire lesion (22). Furthermore, none of the aforementioned studies used more than five imaging features for the analysis.…”

mentioning

confidence: 99%

Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images

Fehr

Veeraraghavan

Wibmer

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

336

315

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Noninvasive, radiological image-based detection and stratification of Gleason patterns can impact clinical outcomes, treatment selection, and the determination of disease status at diagnosis without subjecting patients to surgical biopsies. We present machine learning-based automatic classification of prostate cancer aggressiveness by combining apparent diffusion coefficient (ADC) and T2-weighted (T2-w) MRI-based texture features. Our approach achieved reasonably accurate classification of Gleason scores (GS) 6(3 + 3) vs. ≥7 and 7(3 + 4) vs. 7(4 + 3) despite the presence of highly unbalanced samples by using two different sample augmentation techniques followed by feature selection-based classification. Our method distinguished between GS 6(3 + 3) and ≥7 cancers with 93% accuracy for cancers occurring in both peripheral (PZ) and transition (TZ) zones and 92% for cancers occurring in the PZ alone. Our approach distinguished the GS 7(3 + 4) from GS 7(4 + 3) with 92% accuracy for cancers occurring in both the PZ and TZ and with 93% for cancers occurring in the PZ alone. In comparison, a classifier using only the ADC mean achieved a top accuracy of 58% for distinguishing GS 6(3 + 3) vs. GS ≥7 for cancers occurring in PZ and TZ and 63% for cancers occurring in PZ alone. The same classifier achieved an accuracy of 59% for distinguishing GS 7(3 + 4) from GS 7(4 + 3) occurring in the PZ and TZ and 60% for cancers occurring in PZ alone. Separate analysis of the cancers occurring in TZ alone was not performed owing to the limited number of samples. Our results suggest that texture features derived from ADC and T2-w MRI together with sample augmentation can help to obtain reasonably accurate classification of Gleason patterns.

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“…Langer et al described that ADC and T2 were inversely related to the percentage area of nuclei and cytoplasm and positively related to volume of luminal space. 11 One hypothesis for foamy gland HG PIN to mimic prostate cancer on MRI may be the presence of the abundant cytoplasm characteristic of this entity. This rare manifestation of HG PIN can be challenging to diagnose histologically and it is not to be confused with or treated as invasive foamy gland adenocarcinoma or classic acinar-type adenocarcinoma.…”

Section: Cuaj -Residents' Roommentioning

confidence: 99%

Case ‒ Foamy high-grade prostatic intraepithelial neoplasia: A false positive for prostate cancer on multiparametric magnetic resonance imaging?

Chandrasekar

Goldberg

Klaassen

et al. 2018

CUAJ

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The introduction of multiparametric magnetic resonance imaging (mpMRI) of the prostate, and specifically the introduction of diffusion-weighted imaging (DWI), has significantly impacted the diagnosis of prostate cancer and the management of clinically localized prostate cancer. Indeed, its localizing ability has now opened up opportunities to target focal lesions in partial gland ablation therapy as a treatment option for localized prostate cancer. With negative predictive rates of mpMRI approaching 90% in certain series,1 mpMRI has the ability to discriminate between clinically significant intermediate-to-high-risk prostate cancer and low-risk indolent disease. However, false positives can occur. In recent studies, lesions observed on MRI were classified as tumour on targeted biopsy in 47.6% to over 94% for tumours larger than 0.5 ml in volume.2,3 Herein, we present a case of a rare non-cancer, but putatively pre-malignant prostatic histology that was found on biopsies directed at a category 5 Prostate Imaging Reporting and Data System (PIRADS) v2 lesion.

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Prostate Tissue Composition and MR Measurements: Investigating the Relationships between ADC, T2,K^trans,v_e, and Corresponding Histologic Features

Cited by 246 publications

References 40 publications

Relationship betweenT₂relaxation and apparent diffusion coefficient in malignant and non-malignant prostate regions and the effect of peripheral zone fractional volume

Relationship betweenT₂relaxation and apparent diffusion coefficient in malignant and non-malignant prostate regions and the effect of peripheral zone fractional volume

Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images

Case ‒ Foamy high-grade prostatic intraepithelial neoplasia: A false positive for prostate cancer on multiparametric magnetic resonance imaging?

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Prostate Tissue Composition and MR Measurements: Investigating the Relationships between ADC, T2,Ktrans,ve, and Corresponding Histologic Features

Cited by 246 publications

References 40 publications

Relationship betweenT2relaxation and apparent diffusion coefficient in malignant and non-malignant prostate regions and the effect of peripheral zone fractional volume

Relationship betweenT2relaxation and apparent diffusion coefficient in malignant and non-malignant prostate regions and the effect of peripheral zone fractional volume

Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images

Case ‒ Foamy high-grade prostatic intraepithelial neoplasia: A false positive for prostate cancer on multiparametric magnetic resonance imaging?

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Product

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Prostate Tissue Composition and MR Measurements: Investigating the Relationships between ADC, T2,K^trans,v_e, and Corresponding Histologic Features

Relationship betweenT₂relaxation and apparent diffusion coefficient in malignant and non-malignant prostate regions and the effect of peripheral zone fractional volume

Relationship betweenT₂relaxation and apparent diffusion coefficient in malignant and non-malignant prostate regions and the effect of peripheral zone fractional volume